As a new year and semester begins, educators and young coders have a great opportunity to set fresh personal and academic goals. Goals are not just about finding ways to stay motivated but they are about creating a strategic roadmap to success. In coding and computer science, setting clear and achievable goals is also crucial for enhancing skills, boosting confidence, and deepening technological understanding.

Will Crichton, at the age of 17, aspired to become a professional game developer. He blogged about his journey learning programming and software design fundamentals and how he found it difficult to advance his skills. Crichton realized the importance of setting specific goals and seeking guidance to overcome learning obstacles. Crichton's path illustrates how goal setting can drive personal growth and skill development in computer science. His goal-oriented approach made learning more engaging and relevant, proving that the key to effective learning in programming is acquiring knowledge and applying it to achieve meaningful objectives. (Read more about Will Crichton's learning journey here.)

The Importance of Goal Setting in Coding Education

Goal setting is especially vital for students in programming. It maintains a sharp focus, helps students hone essential skills like time management and determination, and fosters a mindset geared toward continuous improvement. Meeting these goals brings significant rewards in coding education, where technology and techniques continuously evolve.

Establishing goals is not just a routine task for students navigating the complexities of coding and computer science; it's an essential strategy for growth and achievement. Clear, well-defined goals transform the learning process, making it more structured and outcome-focused. They serve as benchmarks that students strive to reach, providing a clear sense of direction and purpose in their educational journey.

Steve Covey's "7 Habits of Highly Effective People," emphasizes the importance of having a clear vision and mission to accomplish tasks, setting goals in coding education should also use this method and focus on the end objective. This method, known as "Beginning with the End in Mind," is a powerful tool for personal growth and crafting enriching learning experiences for 21st-century students. By visualizing desired outcomes, we lay the foundation for a curriculum where goals are set and achieved through strategic planning and continuous assessment.

Leveraging SMART Goals in Coding Education

Incorporating structured goal-setting strategies, like SMART goals, can transform the hopes of budding coders into successful futures. SMART goals – Specific, Measurable, Achievable, Relevant, and Time-bound – offer a framework that promotes realistic and attainable goal targets. Technology is constantly shifting and growing, and students must swiftly adapt to these new technologies and methodologies; goal setting can help with this mindset.

By adopting a goal-setting mindset, educators can help to create a supportive environment for young coders that prepares students for a successful career in technology. This mindset helps to empower learners to break down complex coding concepts and projects into manageable tasks, track their progress, and celebrate their achievements, fostering a sense of accomplishment and a drive to tackle more advanced challenges.

Introducing Stretch Goals

Stretch goals are an extension of the SMART goal framework, designed to push students beyond their comfort zones and foster exceptional growth. These ambitious objectives are not always immediately achievable, but they encourage students to expand their skills and knowledge in coding. Stretch goals inspire innovation and creativity, prompting learners to explore new possibilities and solutions in computer science. By integrating stretch goals into coding education, educators can motivate students to surpass their perceived limitations, cultivating a mindset that is essential for breakthroughs in technology and personal development.

These tips can be seamlessly added into the curriculum to help students develop Goal Setting skills for coding and learning.

Enhanced Tips for Goal Setting in Coding

• Cultivate a Mastery Orientation: Motivate students to focus on personal challenges. This help them find ways to maximize their learning in areas of interest. Encourage kids to set goals that reflect their own aspirations and interests, fostering a deeper engagement with their learning journey. Also can be used for Holistic learning: set goals across various life areas, including academics, hobbies, social life, health, and long-term aspirations, to foster well-rounded development.

• Frequent Monitoring and Review: Regular assessments of goals and the progress are essential. Using tools like Goal Setting Templates, tally marks, or journals to track progress and tweak goals. Example: Implement journaling as a method for kids to record, track, and reflect on their goals. This tangible tool aids in monitoring progress and adjusting goals as needed. Set up a system for regular meetings or check-ins to monitor goal progress. This provides an opportunity for guidance, encouragement, and necessary adjustments to goals.

• Personalize the Goal-Setting Process: Acknowledge each student's uniqueness. Assist them in defining specific objectives aligning with their coding talents and career goals. No one goal fits them all. Encourage personalization. Help students set goals that are meaningful to them and aligned with their personal interests and academic needs. Guide them to prioritize a limited number of goals (one to three) to maintain focus and prevent feeling overwhelmed. Revisit and adjust these priorities regularly.

• Encourage Reflection and Self-Assessment: Regular reflection and thinking about thinking excercises helps students identify their areas of advancements, weaknesses and the overall learning journey. Encourage regular reflection on goals, including what works and what needs adjustment. Teach kids to be flexible and adapt goals based on their experiences and changes in circumstances.This reflection helps to develop learners perseverance and resilience.

• Integrate Goal Setting into Daily Learning: Embed goal setting into everyday life and their coding education. This helps establish a culture of continuous improvement and personal growth. Create an environment where kids can share their goals with peers and educators. Encourage mutual support and accountability in goal setting and achievement.

Benefits of Goal Setting for Aspiring Coders

• Improved Academic and Practical Outcomes: Use of proficient goal setting techniques can help to significantly build and develop coding and problem-solving skills. Research shows that effective goal setting can help to improve student learning. Holistic goal setting helps children see the interconnectedness of their coding goals with other aspects of their lives, leading to a more balanced and fulfilling approach to learning.

• Increased Motivation and Engagement: Accomplishing goals can help build motivation and encourage students to focus on specific achievements for coding projects. Meeting both short-term SMART goals and long-term stretch goals boosts kids' confidence in their coding abilities and in their capacity to achieve ambitious targets.

• Development of Essential Life Skills: Goal setting in coding cultivates resilience, time management, and problem-solving competencies, which are vital for success in technological careers.

• Enhanced Self-Efficacy: By achieving goals in coding, kids build confidence in their abilities, fostering a positive attitude towards learning and future challenges. When goals are set and achieved, students feel more in control and invested in their learning process. This empowerment leads to greater engagement and enthusiasm in coding activities.

• Cultivation of a Growth Mindset: Regularly setting and acheiving goals helps to motivate students to perceive challenges helps students develop a growth mindset, where they view challenges as opportunities for growth rather than obstacles.

Integrating structured goal-setting strategies, such as SMART goals and stretch goals can turn average coders into passionate life long learners. By teaching students how to embrace goal setting, educators can create a nurturing environment that enhances coding skills and equips students for a successful future. Goal setting helps to cultivates disciplined, goal-oriented professionals ready to innovate and lead in the ever-evolving tech landscape.

Resources

Crichton, Will. "Learning Through Goals in Computer Science." 22 Sept. 2016, [willcrichton.net/notes/learning-through-goals-in-computer-science/](willcrichton.net/notes/learning-through-goals-in-computer-science/).

Gonzalez, Jennifer. "How to Help Students Set and Track Goals." Edutopia, George Lucas Educational Foundation, 4 Jan. 2021, www.edutopia.org/article/framework-student-goal-setting.

Gonzalez, Jennifer. "Thinking Critically About Goal Setting." Edutopia, George Lucas Educational Foundation, 11 Jan. 2021, www.edutopia.org/article/thinking-critically-about-goal-setting.

Nordengren, Ryan. "Goal-Setting Practices that Support a Learning Culture." Kappan, Phi Delta Kappa International, 25 Oct. 2021, kappanonline.org/goal-setting-practices-support-learning-culture-nordengren/.

"The 7 Habits of Highly Effective People®: Habit 2." FranklinCovey, Franklin Covey Co., www.franklincovey.com/the-7-habits/habit-2/.

Artificial Intelligence (AI) is reshaping how we teach and learn to code. The challenge is to leverage AI not as a crutch but as a catalyst for deeper understanding and motivation in our classrooms. It is even more challenging trying to convince students of this. However, by aligning your teaching goals with the open use of AI in the classroom, teachers can guide students into using AI to empower their learning, not replace it. Integrating AI into the collaborative learning process can shift the student mindset from merely using AI for quick answers to leveraging it as a powerful ally for continuous improvement and skill development.

Here is how we can use AI to empower, not replace, the learning process in computer science education.

Decoding Documentation

Many students and newbie coders find documentation dense and intimidating. Use AI to help students navigate and understand technical documentation. AI can break down these documents into more straightforward explanations, making them more accessible and less daunting for learners. You can also use ChatGPT4 or ChatPDF to upload documentation, ask AI questions, and provide coding assistance.

Example Assignment:
Assign each student a Python library to investigate. Have the students upload the package documentation and "interview" the AI to learn about the library. Have students generate an example script and then prepare a presentation to teach other students about the library.

Exploring AI-Generated Code

Engage students with AI-generated code samples. Encourage them to analyze and improve upon these samples. This activity not only demystifies AI's capabilities but also stimulates critical thinking as students discern the strengths and weaknesses of AI-generated code.

Example Lesson
Use ChatGPT4 or another code generator to create Python Scripts for fun activities. Have students identify the Coding concepts, describe what the code is doing, or look for any errors or issues with the code.

Ethical Discussions on AI Use

Facilitate discussions on the ethical use of AI in coding. Have students reflect on the importance of understanding the code they write, even when AI assists them, and the ethical implications of relying too heavily on AI. Encourage students to consider the responsibilities that come with this powerful tool.

Example Discussion
Provide students with a safe space to use Generative AI and give students parameters to guide their use. Ensure that students cite or provide credit to code scripts that they have gotten from Generative AI and or online. Discuss the importance of ethical use in code.

AI as a Research Tool

Teach students to use AI to gather information on coding concepts or languages they are unfamiliar with. This encourages them to take initiative in their learning and share their findings with peers, promoting a culture of shared learning.

Example Assignment
Assign students with a task that requires using another language or an advanced topic. Have the students develop a plan to create or execute the activity. Students can use AI to research other examples, code snippets, Python Libraries, and other coding languages to build a "mood board" or in-depth plan for the task.

Debating AI Suggestions

Encourage debates or discussions around AI-generated solutions. Students can analyze different solutions proposed by AI, debate their merits, and decide on the best approach. This enhances their understanding of coding practices and fosters critical thinking and decision-making skills.

Example Lesson
Use a personal script or a student's code and generate a code snippet for the same app using Generative AI. Place the two scripts side by side and discuss the differences between the two codes. Discuss readability, functionality, and efficiency with the code. (Make sure to remove the comments in the Generative AI before the discussion.)

Peer Review Sessions with AI Assistance

Organize peer review sessions where students use AI to analyze each other's code. The AI tool can point out inefficiencies, bugs, or areas for optimization, which students can then discuss and work on together. This improves their coding skills and teaches them to give and receive constructive feedback.

Example Activity
Complete peer reviews with students. First, have the students review each other's code without the help of AI. Have students look for bugs and give feedback on the code. Then, have students upload their partner's code into ChatGPT4. Have them ask GPT for feedback and improvements for the code, then have them share their findings. Having students work on other students' code allows them to evaluate and learn new concepts from their peers and AI. The discussion and resharing after the AI reviews are an excellent opportunity for the students to discuss if the improvements or feedback are worthy and relevant.

Celebrating Creativity and Innovation

Highlight and celebrate when students creatively use AI in their projects. Acknowledging innovative approaches motivates students and emphasizes the importance of creativity in coding and AI applications. Help develop opportunities or "forced" creativity to demonstrate the benefits of using Generative AI for creative ideas.

Example Activity
Python Mashups powered by AI: Develop a "Wheel of Python Libraries" or two wheels! Create two separate wheels, each featuring a diverse range of Python libraries. Ensure the libraries are varied enough to spark interesting combinations, yet compatible for integration into a single project.Have students spin the wheel to select two different Python Libraries. Students use Generative AI to develop an app that uses the two chosen libraries. See if the AI can help generate the start of an app and have students add their flare.

Once completed, students present their projects to the class, explaining their thought process, the challenges they faced, and how they integrated the two libraries. This fosters a learning environment where students can share insights and learn from each other's experiences.

Real-World Problem Solving

Challenge students to use AI as a tool to solve real-world problems. They could use AI to optimize code for efficiency, solve complex algorithms, or even predict outcomes. Such projects show the practical application of AI in coding, making learning more relevant and exciting.

Example Assignment
Have students design an app to solve a real-world problem or issue they could automate with Python. Call it an @Al Sweigart-inspired "Automate the Boring Stuff" Hackathon. Let students generate code using AI as necessary. Ensure that the students have developed a complete plan prior and have the students draft their final product before using the AI. This will help mitigate total plagiarism and ensure students think through the solution first.

AI as a Personalized Tutor

Introduce AI tools that can serve as personalized tutors for students. These tools can explain complex code lines or concepts in a way that is tailored to each student's understanding level. This individualized approach can clarify doubts and strengthen comprehension, encouraging students to explore coding concepts more confidently.

Example Lesson
Give students code or have them generate a script. Have the students ask ChatGPT4 to explain every line of code to them. Have students present this code, run it, and explain to students what each line does. Students can teach other students "like a 1st grader."

Shared Learning Logs

Create a shared digital log where students document their learning experiences with AI, including challenges faced and insights gained. Peers can comment on each other's logs, providing additional perspectives and learning from each other's experiences.

Example Project
Reflection and Metacognition are great ways to encourage students to think about their learning. Have students create portfolios of their use with AI. Have students reflect on what they learned if AI was helpful, and provide other perspectives on their learning.

It's important to set realistic expectations about AI's role in coding. AI can be a powerful ally when used wisely. It can demystify complex concepts, provide personalized learning experiences, and open doors to innovative problem-solving approaches. It's not just about finding quick solutions but understanding, improving, and innovating. By integrating AI thoughtfully, we prepare students to be coders, thinkers, and problem-solvers equipped for the future.

1. Setting Clear Goals

Setting clear objectives is the first step to staying motivated. Ask yourself: What do I want to achieve with my coding skills? It might be building a specific project, mastering a new programming language, or contributing to open-source projects. Having a defined target gives you direction and a purpose to work towards. If adding twists and interesting activities for students is a motivator, aim to adapt your goals according to the school year. If the goal is too big, break it up and make smaller tasks that you can complete.

2. Embracing AI as a Collaborative Tool

Instead of seeing AI as a rival, view it as a collaborator. AI can take over repetitive tasks, offer coding suggestions, and assist in debugging. This allows more time for creative and complex coding tasks, making your work more engaging. Consider using a coding assistant instead of ChatGPT, and investigate ways AI can also be used in class to motivate your students.

3. Committing to Continuous Learning

The technology is ever-evolving. Commit to learning new languages, frameworks, and tools. This keeps your skills current and brings a sense of achievement and growth. Try to integrate new coding concepts into your teaching. This not only benefits your students but also reinforces your own learning. Look into using Python with hardware, such as Circuit Playground, Lego Spike Prime, or Drones.

4. Joining Communities

Participate in online coding forums or local meetups. Sharing experiences, working on joint projects, and networking with peers is incredibly stimulating and keep you connected with the coding world. Follow other Pythonistas that work on Python libraries that interest you. Follow tech blogs, podcasts, and news to stay informed about the latest developments in computer science and coding. This can spark interest in learning new technologies or languages.

5. Pursuing Personal Projects

Create small projects for yourself. This hands-on approach can be more engaging, rewarding and are highly motivating. They allow you to apply your skills to something you are passionate about, and the satisfaction of seeing your project come to life is unparalleled. With the help of AI, you can also develop projects that may have been previously out of your reach.

6. Balancing Your Work

Sometimes, you need a break from coding. If you are in a position to take a break from coding, do it. To avoid burnout, balance coding with other hobbies, exercise, and social activities to keep a healthy work-life balance. Pick up a fiction book and switch coding activities for different interests.

7. Celebrating Small Wins

Regularly look back at how far you've come in your coding journey. Every small achievement in your coding journey is a victory. Whether fixing a complex bug or grasping a new concept, take time to acknowledge and celebrate these milestones. On the Teaching Python podcast, we take time each episode to celebrate our wins and to help keep us motivated in our daily work.

8. Staying Curious

Approach coding with a curious mind. Experiment, tinker, and explore new ideas. This approach keeps the learning process exciting and engaging. Step out of your comfort zone and try to learn something completely new or more advanced. Dig deep into a Python library that you already know, explore it, and challenge yourself to do something new with that library. For example, Stephen Gruppetta does an amazing job at pushing the limits in Python Turtle.

9. Teaching Others

There is a reason why teachers teach. It is a rewarding experience that can boost your confidence and motivation. But sharing your knowledge with others helps them and reinforces your understanding. Learn something new, teach it to a colleague or student, or post it online. Remind yourself of the positive impact you have on your students. Your continuous learning can inspire and benefit them greatly.

10. Integrating AI into Learning

Use AI to generate code for something unique or a project you want to complete. Learn each line of the code and challenge yourself to improve the code and enhance your debugging and coding skills. Try to understand and improve AI-generated code or use AI to generate other project ideas.

Remember, it's normal for motivation to fluctuate. The key is to stay adaptable and find what reignites your passion for coding. Whether it's a personal project, community involvement, or the thrill of learning something new, there's always something to generate that spark. Embrace the moments, try some strategies, and continue to grow as educators and lifelong learners in coding and AI.

Effective classroom management is a skill most experienced educators possess. It establishes an environment conducive to learning, where students feel secure and focused. Research indicates that a quiet, well-managed class only sometimes equates to effective learning. Authentic learning, especially in dynamic subjects like coding, requires more than just discipline and silence. It demands an environment that fosters comfort, engagement, and active participation.

Extensive research in environmental design and cognitive science supports the idea that comfort significantly affects learning, human productivity, and creativity. These perspectives have led to significant shifts in the design of workplaces, homes, and recreational spaces over the past thirty years.

This article is a two-part series focusing on how environmental and cognitive processes can promote positive learning in computer science. Each part will offer ten tips to help you 'get it right.'

Coding is not just about understanding syntax or memorizing commands; it involves critical thinking, problem-solving, and often, collaborative work. Coding requires a highly interactive and flexible learning environment where students can experiment, make mistakes, and learn from them. The strategies in this series are tailored to the unique needs of the computer science classroom, ensuring that students learn the fundamentals of programming and develop the cognitive and collaborative skills essential for success.

Part 2: Cognitive Processes and SEL in Coding Education

This part focuses on the cognitive aspects of learning to code, integrating the principles of cognitive learning theory with Social and Emotional Learning (SEL) strategies. Awareness of cognitive processes enhances learning, the role of metacognition in coding, and classroom management. Teaching students how to think improves classroom management because students are more engaged in learning, build self-regulation skills, develop persistence, and increase agency and control over their learning. Incorporating these ten tips in computer science can help improve cognitive processes directly and indirectly.

1. Awareness of Cognitive Processes: Encourage students to reflect on their thinking. This involves guiding them to recognize and analyze how they process information, make decisions, and memorize. In Computer Science, ask students to explain the steps for an app in a computer science class. The student should be able to explain the functions or steps they choose and the order of the algorithms. This helps them understand their cognitive strategies and identify areas for improvement, leading to the development of more effective learning techniques.
2. Long-term Learning and Assessment: Students should understand that coding is a process and learning is a long-term investment. Just as "getting fit" is judged over time, cognitive science suggests that learning is best assessed over extended periods; finding opportunities to ​complete check-in periodically but assess minimally can encourage students' growth and understanding.
3. Encourage Metacognition: Understanding one's thought process is vital to problem-solving and debugging code. Teach students to think about their thinking and encourage student activities that promote active learning and reflection.
4. Recognize the Role of Emotions: Coding can be frustrating and difficult for some students. Acknowledging, addressing, and managing emotions in the classroom is essential, especially with young coders. Help students handle their emotions by discussing their feelings, validating them, and avoiding dismissing them. This can help to build their resilience and promote positive learning outcomes. Remember, we were all newbies once.
5. Create a Positive Environment: Encourage positive mindsets. Use the "Power of Yet" and help students change the words "I can't code" to "I can't code yet."
6. Avoiding Fractured Teaching: Coding is a process that can not be accomplished by cramming or studying. Teaching concepts with a spiral curriculum and revisiting past content regularly is essential to strengthen long-term retention and understanding​​. ​ "Embed revisiting into your practice, ensuring that students are given regular opportunities to look back at past material."(Boxer, 2021) Regularly reviewing fundamental concepts to solidify learning, using and typing functions repetitively, and coding a lot is easy to scaffold.
7. Scaffold to Build Confidence: Students may lack confidence in coding because they may not have mastered some skills and strategies. Fear of failure can hinder students' desire to code; however, if they experience success—even small successes—it builds their confidence. Scaffolding involves designing tasks that start at the student's skill level and gradually increase the task's difficulty once the learner reaches the next level. "As learners grow within their zone of proximal development and become more confident, they practice new tasks with the social support that surrounds them. Vygotsky maintains that learning occurs through purposeful, meaningful interactions with others."
8. Promote Collaborative Learning: Enhance students' social skills by facilitating group work in coding projects. Collaborative learning fosters a sense of community and is grounded in educational theories like Vygotsky's social development theory, which emphasizes the importance of social interaction in cognitive development. Through group activities, students exchange diverse problem-solving approaches, provide peer feedback, and articulate their coding processes. Such collaboration is instrumental in developing both coding proficiency and interpersonal skills.
9. Design Lessons that Matter: Introduce students to coding problems that have real-world applications. For example, ask students to develop a simple app that solves a common problem or contributes to their community. This can increase engagement and connections and help students see the broader impact of their coding skills. For instance, allow students to investigate the Flask library. Have them produce a website that they can later build upon. This website can house a portfolio for future college entrance essays or coding projects.
10. Debugging builds persistence: This is a fundamental skill in code and is one of the first skills that requires patience and immediate instruction for all new coders. This is a skill that is persistent at all levels of a coding program. Debugging helps to improve problem-solving and flexible thinking. In addition, when students debug their peers' code, it helps build a deeper understanding of coding principles. Teaching debugging builds confidence and helps motivate students to persevere through future difficulties in code. Consider developing a mindset where when students encounter a bug, the teacher guides the student through a systematic debugging process instead of providing the solution outright. This approach involves breaking down the code, understanding the logic flow, and identifying where the error occurs, which not only fixes the bug but also develops a deeper understanding of the code structure.

Creating an effective learning environment for coding extends beyond traditional classroom management. It encompasses the physical comfort of students, their emotional well-being, and an approach to learning that is active, engaging, and responsive to their needs. These ten tips provide a starting point for educators to cultivate a space where students can thrive in learning the valuable skill of coding.

Which of the ten strategies discussed resonates most with your teaching style, and how do you plan to integrate it into your computer science classroom? Are there particular challenges you anticipate in implementing this strategy?

Reources

Barrett, Peter, et al. “The Impact of Classroom Design on Pupils' Learning: Final Results of a Holistic, Multi-Level Analysis.” Building and Environment, vol. 89, 2015, pp. 118-133, doi:10.1016/j.buildenv.2015.02.013.

Boxer, A. “Improve Learning with Cognitive Science.” Royal Society of Chemistry, Oct. 2021, edu.rsc.org/feature/improve-learning-with-cognitive-science/4014475.article.

Edutopia. “A Comfortable Truth: Well-Planned Classrooms Make a Difference.” Edutopia, www.edutopia.org/article/comfortable-truth-well-planned-classrooms-make-difference.

Edutopia. “Creating a Space for Collaboration.” Edutopia, www.edutopia.org/article/creating-space-collaboration.

Fisher, A. V., et al. “Visual Environment, Attention Allocation, and Learning in Young Children.” Psychological Science, vol. 25, no. 7, 2014, pp. 1362–1370, doi:10.1177/0956797614533801.

Insights to Behavior. “The Impact of Classroom Management on Social-Emotional Learning.” Insights to Behavior, insightstobehavior.com/blog/impact-classroom-management-social-emotional-learning/.

Juan, Y.-K., and Chen, Y. “The Influence of Indoor Environmental Factors on Learning: An Experiment Combining Physiological and Psychological Measurements.” Building and Environment, vol. 221, 2022, 109299, doi:10.1016/j.buildenv.2022.109299.

Kurt, Serhat, Dr. “Vygotsky’s Zone of Proximal Development and Scaffolding.” Educational Technology, 18 Aug. 2020, educationaltechnology.net/vygotskys-zone-of-proximal-development-and-scaffolding/.

Office of Scientific and Technical Information (OSTI). “Indoor Air Quality, Ventilation and Health Symptoms in Schools: An Analysis of Existing Information.” U.S. Department of Energy, www.osti.gov/servlets/purl/828725.

RSC Education. “Improve Learning with Cognitive Science.” RSC Education, edu.rsc.org/feature/improve-learning-with-cognitive-science/4014475.article.

7pace. “Here's What Science Says About How Music Affects Your Productivity.” 7pace, www.7pace.com/blog/heres-what-science-says-about-how-music-affects-your-productivity.

Introduction

This two-part series explores the crucial role of environmental and cognitive processes in fostering positive learning experiences in computer science, specifically focusing on Python programming. Each part will offer actionable tips to create a thriving learning environment for your students.

Imagine these two classroom environments, both created in Dall-e. Which environment is more conducive to learning Python?

The Classroom Challenge

Traditional classroom settings can often pose obstacles to effective learning, particularly in dynamic subjects like coding. These limitations may include:

• Limited collaboration: Rows of desks restrict interaction and create a sense of isolation.
• Emphasis on quietness: The expectation of absolute silence can hinder the interactive nature of coding, hindering exploration and discussion.
• Uncomfortable seating: Traditional chairs often lack ergonomics, leading to physical discomfort and reduced focus.

Building a Better Environment

Extensive research in environmental design and cognitive science emphasizes the profound impact of comfort on learning, productivity, and creativity. By prioritizing comfort in your coding classroom, you can foster:

• Engagement: A welcoming and inclusive space encourages active participation and teamwork.
• Motivation: Reduced distractions and a comfortable environment allow students to focus on the learning process effectively.
• Well-being: Attention to physical and mental comfort promotes a positive learning experience.

Creating Comfort and Engagement: 10 Practical Tips

1. Build Community:

   • Foster group seating by arranging furniture in smaller clusters within the classroom. This promotes a sense of connection, belonging, and emotional comfort.
   • Encourage students to work together in these spaces, fostering collaboration and reducing feelings of isolation.

2. Teacher Location:

   • Move beyond the traditional "sage on the stage" approach. Position yourself closer to students, fostering accessibility and encouraging active learning through discussions and collaborative activities. This proximity also helps break down traditional boundaries and promotes a more inclusive learning environment.

3. Comfortable Seating:

   • Advocate for replacing traditional chairs with ergonomic options that provide better back and neck support, reducing fatigue and discomfort.
   • Consider introducing floor seating options, like cushions or beanbags, to cater to individual preferences and learning styles. Remember, variety is key to ensure inclusivity.

4. Diverse Learning Areas:

   • Create distinct spaces within the classroom to accommodate various activities, preferences, and learning styles. This could include dedicated areas for individual coding practice, group projects, focused learning, and group discussions.
   • Designate a central space with a large rug or flexible seating arrangements for group discussions, code reviews, or brainstorming sessions.
   • Provide movable chairs or stools to encourage flexibility during group work. Consider adding display screens for showcasing code or for better visibility.

5. Embrace the Outdoors:

   • When possible, consider incorporating outdoor learning experiences for a change of pace and increased creativity. Explore opportunities to conduct certain activities outside or provide students with flexible options for individual work environments.

6. Control Acoustics:

   • Minimize noise distractions by addressing potential sources like hard floors or walls.
   • Use sound-absorbing materials like carpets, curtains, or acoustic panels to minimize noise bleed between different learning areas.
   • Explore other options for damping sound and noise to create a more focused learning environment.Shelving with fabric storage boxes help minimize noise and provide orgranization.

7. Music and Productivity:

   • Acknowledge that individual preferences for music vary. While not suitable for everyone, consider incorporating instrumental or focus music for specific coding tasks. Offer periodic breaks with uplifting music during these times. Remember, silence is still crucial for tasks requiring total concentration.

8. Cultivate a Positive Classroom Culture:

   • Create a welcoming and inviting atmosphere by incorporating elements like plants or student artwork.
   • Encourage a sense of ownership and responsibility by greeting students individually and involving them in room design and maintenance tasks.

9. Prioritize Air Quality:

   • Ensure good indoor air quality by allowing fresh air into the room or using air purifiers. Fresh air is crucial for promoting alertness and focus, essential for mentally demanding tasks like coding.
   • Bring in plants that are known for removing harmful chemicals and improving air quality by filtering out toxins like benzene, formaldehyde, and trichloroethylene. These "air-purifying plants" not only enhance the aesthetics of your classroom but also contribute to a healthier learning environment.

10. Minimize Overstimulation:

    • Reduce potential distractions by carefully managing visual elements in the classroom. Ensure that any classroom displays are relevant to the current learning objectives and avoid unnecessary clutter.

Conclusion

By implementing these practical strategies, you can transform your coding classroom into a comfortable and engaging environment. This not only fosters positive learning experiences for your students but also empowers them to unlock their full potential in the exciting world of computer science.

Additional Resources

• The impact of classroom design on pupils' learning by P. Barrett et al. (2015)
• A Comfortable Truth: Well-Planned Classrooms Make a Difference by Edutopia (n.d.)
• Visual Environment, Attention Allocation, and Learning in Young Children by A. V. Fisher et al. (2014)
• The influence of indoor environmental factors on learning by Y.-K. Juan & Y. Chen (2022)

This resource is rooted in three learning theories:

Cognitive Load Theory (CLT)

Proposed by John Sweller, the Cognitive Load Theory(CLT) suggests that our working memory is limited. It is an instructional design theory emphasizing how the human brain processes and stores information. When we learn, we must manage this cognitive load to ensure it is not overwhelmed and learning compromised.

The Board of Knowledge lessens cognitive load by providing readily accessible information to the students. Students can quickly reference terms instead of relying solely on memory, allowing them to focus on internalizing essential concepts. Reducing the demands on learners' working memory removes unnecessary pressure from short-term memory. Students can focus on information that needs to move into long-term memory, like the order of the code or the connections, and less on terminology.

Zone of Proximal Development (ZPD)

As conceived by Lev Vygotsky, ZPD expresses the gap between what learners can do without help and what they can achieve with guidance. It is the space between a student's current ability and their potential. In this context, the Board of Knowledge acts as a "scaffolding" tool, often associated with ZPD, offering students a quick reference point that bridges their existing knowledge with new concepts.

Scaffolding is an instructional technique that guides students progressively toward a more robust understanding and, ultimately, greater independence in the learning process. Scaffolding supports students as they build new skills. As the student becomes more proficient in coding, support is gradually removed, allowing the student to work more independently.

By offering students the right tools, resources, or strategies (scaffolding) right when they need them, educators help learners move through their ZPD.

Dual Coding Theory

This learning theory states that verbal and visual data are processed distinctively. It is not about catering to different learning styles (they do not exist) but recognizing that our brain has two primary channels: visual and verbal. While scaffolding supports students in progressing from their current knowledge level to more advanced understanding, this theory suggests that both verbal and visual information are processed differently and that students can benefit from having information presented in both formats. Presenting information in both formats—like pairing terms with diagrams or symbols on the board—can enhance comprehension and recall.

When an instructor uses the most effective learning strategies, students can understand better. Making core concepts consistently visible through tools like the "Board of Knowledge" not only serves as a memory aid but also capitalizes on established educational psychology principles to facilitate more effective learning.

MindTools. (n.d.). Cognitive Load Theory. Retrieved October 31, 2023, from https://www.mindtools.com/aqxwcpa/cognitive-load-theory

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At the Teaching Python Podcast, we hold Python Tutor in high regard. Sean and I use it in our classrooms and for our own learning and understanding. We believe in the idea that just blindly copying code without understanding doesn't add to students' knowledge. However, when students truly understand their code and can make sense of complex topics, they become life-long coders.

Listen to these episodes first!

If you're just hearing about us for the first time, you may be tempted to start at the beginning with Episode 1. Don't! (it's not very good). Here's a curated list of our favorite episodes for first-time listeners.

• #48 Python Tutor with Philip Guo
• #68 Learning How to Learn With Barbary Oakley
• #65 Our Favorite Python Libraries
• #111 Generative AI with Eric Matthes
• #80 Reaching for the Stars with Dr. Becky Smethurst

What really matters in computer science

Journeying through the twists and turns of teaching middle school computer science has taught us that learning to code isn't just about syntax or algorithms. It's about problem-solving, embracing failures, celebrating victories, and, most importantly, it's about the adventure of discovery – all seen through the vibrant lens of the Python language.

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Recently, we decided to partner with Python Tutor in the original spirit of the "world wide web." Back in the early days, if you had a great site to share, you linked to it from your own website. That's it. There were no ads, no payments exchanged, no link tracking or weird cookies. Just sharing good stuff with the world.

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In the heart of every programmer is an artist, and in every musician, a coder is waiting to come out. EarSketch from Georgia Tech reveals a compelling overlap between coding and music.

The Melody of Learning

EarSketch provides learners with a hands-on approach to understanding coding concepts by creating music. It is a platform where coders can practice the basics of coding by creating music. It's not just about writing lines of code; it's about making your code sing, literally. This blend of music and coding is a great way to get kids hooked on code.

Making Music with makeBeat and fitMedia

Two core functions used on EarSketch are makeBeat and fitMedia. Both functions help make understanding functions and parameters easier to grasp through music.

Enhancing Songs with Loops

In programming, loops let us repeat actions. In music, they set the groove. Using musical/coding loops in Earsketch helps highlight the importance of repetition and modularity in music and code.

Skills and Fun: Striking the Right Chord

EarSketch is the perfect balance between coding skills and fun. By the end of their Earsketch journey, students develop:

• Cognitive Skills: Kids develop logical thinking, problem-solving capabilities, and understanding of core programming concepts.
• Creativity: Learners understand that coding can be both functional and expressive.
• Music Basics: Even without prior knowledge, they grasp fundamental musical concepts. They have a foundational understanding of beats, rhythms, and song composition.
• Motivation: The immediate feedback from music keeps students motivated.

EarSketch is a tool that merges the worlds of coding and music. Using the Earsketch library, kids learn about beats, variables, loop functions, and parameters. Through melodies, they discover the joy of coding. Through this platform, students learn coding fundamentals and see (and hear) their practical applications in a unique and engaging way.

LLMs, or Large Language Models, leverage the transformative power of encoding and context to understand and generate human-like text. The core technology of these models is the "transformer," a tool introduced by Google researchers in 2017 that revolutionized the way computers perceive and process language.

Unlike traditional models that evaluate language word-by-word, transformers analyze entire sequences. This enables LLMs to parse context more effectively, identify patterns with heightened accuracy, and generate or translate text with remarkable precision.

Context is essential because the meaning of words and phrases often shifts based on their surrounding content. By processing entire sequences, LLMs are good at understanding these contextual nuances, which, in turn, enhances their efficiency, speed, and scalability.

Read more at https://ig.ft.com/generative-ai/

Uniting Technology and Constructivism

Long before generative AI, the fusion of technology and constructivism was reshaping learning experiences. In an article titled "Constructing on Constructivism: The Role of Technology," the author Grant states that "A complementary relationship appears to exist between computer technologies and constructivism, the implementation of each one benefiting the other" (49). Technology and constructivism enhance learning by creating interactive and dynamic environments that foster critical thinking and problem-solving. But how effectively can technology and constructivist pedagogy be combined to promote learning and knowledge exploration?

My Intersection with AI and Constructivism

In my computer science classes, students don't just write code; they have an exploratory learning journey to learn code deeper. Teaching coding and using generative AI such as ChatGPT, has made me realize how closely the two align with the constructivism learning theory. It's a journey that reminds me of the power of merging technology and pedagogy. I often use a constructivist approach in my computer science classes, whether kids write code or interact with AI.

Just as constructivism gives learners control, generative AI offers users the power to shape AI's output. By crafting well-considered prompts, individuals actively shape the generated content, like students constructing their understanding of a subject.

In a recent 8th-grade project, students were encouraged to use Anaconda Assitant to create graphs and charts focused on the UNESCO Sustainable Development Goals (SDGs). Their task was not just to make a fact-replicating app but to use AI to display data and craft data-driven stories displayed through graphs. Although students could already graph using the MatPlotLib library, the AI assistant helped students use large datasets, data frames, and interactive charts to enhance the story.

In this project, students took charge of their own learning journey, incorporating principles of the constructivist approach. Using Anaconda Assistant, a generative AI, they didn’t just consume information but actively built their knowledge by creating graphs, crafting data-driven stories and coding concepts that were new to them. This not only honed their technical skills but also enriched their abilities to interpret and convey complex global issues through data storytelling.

The more they Code, the Better Coders they Become

In the computer science classroom, constructivism is a helpful approach that places learners at the center. Coding is not just about memorizing syntax and concepts; it's about understanding patterns, logic, and problem-solving of complex problems. Over the six years of teaching kids to code, it never gets old to see how students thrive when they dive into the code, embracing my belief that students only become better coders by writing more code.

While constructivist theory emphasizes student-led knowledge building, it doesn’t dismiss the importance of direct instruction. The central idea of constructivism is that students actively build their knowledge to engage with learning after explicit teaching has happened. Students need to tinker, debug, and find solutions on their own. This hands-on approach is where the real learning happens. Hands-on experiences and critical thinking are critical for learning and is not limited to coding classes.

A great strategy to emphasize in computer classes is "Peer Learning and Collaboration." I always use peer-to-peer teaching, where students explain concepts or solve problems collaboratively. This helps to ensure they not only "absorb" but also share knowledge in an iterative cycle. In class, students debug and edit student's code without my direct intervention. Discussing concepts with peers, reinforces and diversifies their understanding through teaching and explanation. Keep in mind that students are not allowed to type for other students. They must practice explaining to their peers coding concepts in an accessible manner, seeking new ways to explain concepts than was previously taught.

Constructivism fosters critical thinking and deep understanding as students struggle with concepts and build understanding. Just as authentic learning does not happen with only one prompt to ChatGPT, real learning does not occur when a teacher directly tells the students' answers. Genuine learning extends beyond direct answers and single prompts, emerging instead from active engagement with generative AI, coding, and other subjects.

The Demanding yet Rewarding Path

Using a constructivist approach, while placing students at the forefront of learning, demands a mindful and adaptive teacher. The teacher's intuition and personal connection with students helps to create a classroom environment conducive to learning. The teacher guides and facilitates learning, navigating the very active, and sometimes chaotic, process of meeting students where there are at. Although it is challenging to "let go" of the directionof learning, it fosters a genuine love for learning to code that stretches far beyond my classroom.

Constructivism and technology requires thorough planning, strategic adaptation to student needs, and isn’t an easy job. While this investment may seem scary, the rewards are tremendous. While constructivism might be seen as a slower teaching method, it fosters a deep, lasting understanding. This method starts with basics as more complex concepts are introduced to ensure sustained student engagement and progression in coding.

Self-discovery is at the center of constructivism. Students have agency, and guiding their learning empowers them to become independent thinkers. Through exploration, experimentation, and reflection, they construct meaning in a way that resonates with them. This process enhances comprehension and cultivates a love for learning that extends beyond the classroom.

It's important to recognize that constructivism isn't a one-size-fits-all solution. There should always be a balance of teaching methods used in class; by integrating multiple ways, educators can create a holistic learning experience for their students.

Looking toward the future, AI and a constructivist approach have great potential. As educators, the challenge and opportunity lie in harnessing AI not as a replacement for the human touch in education but as an ally that can help teachers cater to student's learning needs.

Embracing the Future while Holding the Essence of Teaching

How can the role of the teacher morph as AI continues to advance and become an even more integral part of the learning environment?

It is important to remember that while AI brings a wealth of resources and opportunities, the heart of education remains in the relationships we build in our classroom. Firthermore, the learning approaches that we incorporate in our teaching, are only as good as the effort we put into the planning and delivery.

Hein, George  E. “Constructivist Learning Theory | Exploratorium.” https://Www.Exploratorium.Edu/, Oct. 1991, www.exploratorium.edu/education/ifi/constructivist-learning.

Mcleod, S. (2023, June 15). Constructivism learning theory & philosophy of education. Simply Psychology. https://www.simplypsychology.org/constructivism.html

OpenAI. (2023). ChatGPT (September 25 Version) [Large language model]. https://chat.openai.com

Learning through Critical Thinking with ChatGPT

In a recent quiz, I asked my students, "Why is it important to understand context, concept, and content when using ChatGPT to code graphs?"

This question sparked a lively discussion in my class, reinforcing my belief in the critical importance of teaching practical applications like critical thinking, prompt crafting, and the role of AI as an educational tool. It also prompted my reflection on how to address the arguments of whether using and leveraging the power of AI in coding could be perceived as an academic shortcut to learning.

In today's AI world, integrating artificial intelligence is becoming increasingly significant. However, it's crucial to emphasize that AI in education should enhance, not replace, the learning process. Understanding Context, Concept, and Content are ideal for effective interaction with AI.

Context, Concept, and Content: Key Elements for Effective Interaction

Knowledge and skills will always trump mere information. However, empowering learners to apply what they've learned practically and meaningfully will lead to mastery and innovation.

For those new to ChatGPT, prompt engineering is fundamental. It involves crafting clear instructions to guide AI in generating relevant and insightful responses. Students can quickly use ChatGPT to answer basic questions, generate essays on familiar topics, or complete repetitive assignments. However, when students engage with ChatGPT on higher-level or more complex topics, a solid grasp of context, concept, and content becomes crucial. These three elements are intertwined and also essential for formulating prompts that yield meaningful responses.

• Context: Context, in any situation, refers to the surrounding circumstances, background information, or setting that provides a framework for understanding specific events, statements, or actions. Clearly defining the context is crucial when using generative AI. It ensures that the information provided is on point and suitable. This is especially crucial for tasks demanding a deeper understanding, such as coding original projects or discussing intricate subjects. Without a well-defined context, ChatGPT responses may be misinterpreted or inaccurate. The context helps the AI system decipher the user's intent, and provide more accurate answers, no matter the subject's complexity. Framing a question accurately helps to ensure that the AI is more likely to comprehend the intention behind the prompt and provide more accurate and relevant responses, regardless of the complexity of the subject matter. In essence, it demands a form of higher-level learning, emphasizing the need for students to possess a solid grasp of the topic at hand.

  ---

• Content: Content refers to the specific information, data, or material conveyed or shared within a particular context, often forming the substance or core of a subject or communication. Content forms the foundation and essence of a topic or communication. A clear understanding of both the input or information provided and the output from the AI is critical. This comprehensive understanding of content leads to precise and pertinent responses, empowering students to critically evaluate and effectively use the information provided by the AI.

• Concept: The concept is the fundamental idea or principle that forms the basis for understanding a particular subject or topic. A solid grasp of basic concepts is vital for effective interaction with AI. Knowing a topic's subject matter and concept is like having a blueprint. It's the foundation that helps to develop a prompt to ensure the AI's responses are accurate and fit the desired task.
  Students must understand the subject matter or concept to accurately interpret responses and identify hallucinations. Interacting with AI should involve an active exchange of information rather than simply accepting answers as they are. This skill requires practice and development, enabling students to engage with information more effectively and gain a deeper understanding of the material.

Coding: Balancing Patterns with Creativity

Coding at a fundamental level involves working with patterns and applying a touch of creativity to make the product unique. For instance, consider the context of how we were using AI in class to create graphs with a Python library like Matplotlib.

Figure 2: Anatomy of a Figure

The code is straightforward, and students can copy the code from the documentation posted online. Using this code involves only adjusting the x and y data, selecting the graph type, manipulating the labels and adding some color. With a few tweaks to the example code, a new visual representation takes shape. Yet, telling a compelling narrative with the data and truly understanding the data is the true challenge of the assignment.

Students need to understand the data, the subject of the data, and the intended direction of the data's story to make the graphs meaningful. The story may be hidden inside the interpretation of data, and even if AI can give a variety of responses or graphs, knowing the concept, context, and an understanding of the content is essential.

Here, the intersection of critical thinking and AI is invaluable. While AI systems can process vast amounts of data and perform complex tasks, their understanding of data is fundamentally different from human understanding. Human understanding involves interpretation, contextual awareness, empathy, and the ability to integrate knowledge with personal experience. While AI aids in data analysis, it may not always uncover the authentic narrative within the data.

As of now, understanding is a human trait. The ability to interpret patterns and the creativity to breathe life into the numbers need human insight. It is these cognitive abilities that set humans apart from artificial intelligence and machines.

Clarifying Misconceptions: AI as an Educational Aid

Using ChatGPT or generative AI as an educational tool should not be automatically labeled cheating in all scenarios. Instead, it should be seen and used as a tool for enriching the learning experience. When students use AI equipped with a clear context, a solid conceptual foundation, and an understanding of the content, they can actively engage with AI and the material, learning along the way.

It's important to recognize that AI can be a valuable tool. But while AI presents exciting new opportunities, it's crucial to acknowledge and address the legitimate concerns. One concern is the possibility of students 'skipping out' on the essential steps of the learning process, potentially missing the development of fundamental skills necessary for effective learning or there may be instances where students only partially grasp learning objectives. In such cases, explaining the underlying reasons for specific rules and approaches can instill a deeper respect for them.

Rather than serving as a shortcut, AI can act as a mode for deep exploration and comprehension. It enables students to focus on the process of problem-solving, fostering critical thinking and nurturing a more profound thought process.

Using AI in the classroom doesn't go without some rules. Not only do students need a clear understanding of when to use or not to use AI, teacher also need to remind students of responsible use, understanding privacy protection, equitable access, and transparency. We should ensure that we foster an inclusive learning environment and that we all uphold ethical standards when using AI while empowering students to use technology knowledgeably.

Leveraging ChatGPT in education is not an evasion of the learning process; it's an enrichment of it. By emphasizing the significance of context, concept, and content, we empower students to evolve into capable critical thinkers. Through prompt engineering, they can refine their communication skills, ensuring a more effective interaction with AI. Embracing AI in education is a smart step toward preparing students for a future that blends human intelligence with technological advancement.

How Can Stories in Primary Education Support Sustainable Development in Bangladesh? - Scientific Figure on ResearchGate. Available from: https://www.researchgate.net/figure/The-3C-Context-Content-and-Concept-scaffolding-approach_fig1_373283180 [accessed 30 Sep, 2023]

It was diverse in the outcome, demonstrating students' various abilities to process what they could read. Some students produced web apps in Dash or Github.io. While others created interactive graphs with dropdown menu features. And other students learned how to interact with 5000+ data points in a .csv. The students undoubtedly acquired skills throughout the project, but I couldn't help but wonder, did they become better coders from this project?

As we watch the emergence of more AI tools powered by ChatGPT that enable kids to code simple solutions, concerns and discussions about the content and considerations of K-12 coding courses should also continue. A recent article by Nisha Talagala titled "Implications For Training And Education" highlights that coding in a professional setting goes beyond what current AI tools can generate. These tools are valuable as co-pilots but do not replace the software engineering role. However, in the context of training and education, the situation becomes more uncertain.

Traditionally, programming training programs, including those in K-12 settings, have focused on contained problems. In my 6th grade class, it is not that much different. Trivial coding challenges allow students to practice primary skills to master topics. However, students may turn to ChatGPT to solve the problem when faced with slight difficulties. This statement is evident when witnessing coding solutions in a 7th-grade class. ChatGPT solves "Rock, Paper, Scissors" much differently than a student who has just learned to code!

Talagala referenced that fresh graduates are not expected to know how complex systems behave, while senior engineers are expected to possess such knowledge. And the challenge arises when ChatGPT and AI can automate tasks typically given to entry-level engineers. This raises questions about how these engineers will learn the skills that senior engineers possess and, more importantly, will junior roles be displaced. Much like the basics for fresh graduates, what constitutes an essential skill and content for today's K-12 learners, and what does not? Will the basics be displaced as well?

More than ever, education programs need to incorporate project-based learning, where students use trivial code snippets as a means to an end rather than the end itself. These challenges need to be unique and open-ended. There needs to be a shift in the focus from solely coding syntax and language proficiency to problem-solving strategies and critical thinking. We must encourage students to think about the problems they are solving and teach them how to take time to consider multiple approaches and plausible solutions. This form of instruction will take a lot more work from the teacher with planning and assessing. And these concerns apply not only to Computer Science teachers but to other curriculum instructors.

Teachers must encourage students to explore creative solutions and think outside the box. We must allow students to express their unique ideas and encourage experimentation. These projects will challenge educators in how they grade; mastery of basic skills typically lends itself to a very A/F grading scale; however, creative and out-of-the-box solutions are often subjective in their measure of success.

Highlighting the importance of collaborative coding and encouraging students to work in teams will also be essential skills to address. Promoting communication, sharing ideas, and learning from peers to simulate real-world coding environments is a lifelong skill applicable in real-world situations. However, teachers must develop ways to grade students accordingly and accept that students will develop strengths in different skills, and the results will be differentiated, as often seen in real life.

Furthermore, teachers should actively modify their course content to address the ethical implications of students' code 'made by AI'. This includes adding active discussions on privacy, bias, and responsible AI development to cultivate a sense of responsibility among learners. Or as Talagala puts it, "Effective, Efficient and Ethical" with AI. To achieve this, teachers must stay up to date with emerging technologies and tools like ChatGPT, integrating them into coding courses to enhance learning while developing coding principles. And this will require a lot of work and training on a daily basis.

And the question still remains, what coding principles are still relevant in this AI world? It is evident that teaching students to think algorithmically and develop logical problem-solving skills will remain important, even with the ever increasing availability of AI tools. It remains true that logic is the foundation for efficient coding and general problem-solving overall. However, this skill is also very systematic, which leads us back to an infinite loop of controversy and the opening of Pandora's Box. Like training an AI, developing logic takes a lot of practice with trivial coding challenges, which AI does efficiently, so where do we go from here?

A shift in mindset for students? And understanding that learning and the love of life long learning is what will keep us human and relevant? More discussions as to why we need to practice what we do is a must. In addition, an understanding of how AI works and how we can stay up-to-date with our thinking is also important. Or on the flip side, do we shift completely,? Do we accept that computers and AI will outperform us in specific roles, and hope that creativity and understanding of complex situations will consistently beat the computer? Focus on teaching the art of creativity and break down the barriers of classrooms and throw out the foundational knowledge and skills? As with the referenced opening of Pandora's Box which symbolizes the unintended consequences and complexities of using AI tools in school, we are at a place where both options offer a challenge and a world of possibilities.

As we stand at this crossroads, it's crucial that we continue these discussions and actively shape the future of coding education. After all, it's in these moments of reflection that we find the path forward.

Talagala, N. (Jun 1, 2023). Implications For Training And Education. Retrieved from https://www.forbes.com/sites/nishatalagala/2023/06/01/is-coding-educationas-we-know-itdead-how-large-language-models-are-changing-programmers/?sh=7ec5ceb43ba9

Reflecting on the "ChatGPT for Social Good" Unit: A Glimpse into the Future of Education

As I reflect on my last 8th grade unit, "ChatGPT for Social Good" I couldn't help but write this blog with some of my thoughts.

ChatGPT, generative AI, and other advancements in Artificial Intelligence are undeniably changing the future - of everything. Artificial Intelligence (AI) is now a pivotal force in transforming education. This transformative power of AI provides students with an abundance of information resources, allowing students to learn in a broader and more open environment. However, with these advances, there are also some concerns. Some educators fear that the traditional essence of teaching and how students should learn may be overshadowed by technology..

A debate in the educational sector is whether schools are losing their relevance and efficiency compared to modern AI-driven learning methods. and are we side stepping the essence of learning, or is it time to redefine our learning in light of these advancements in technology?

Here are some thoughts based on my research from various articles and online discussions.

Insights from Diverse Research

• Traditional schools provide a structured environment and an education covering various subjects and learning opportunities, providing a more holistic environment for learning. They offer an environment where students can foster their interpersonal skills and social interactions ensuring that all learners have a 'well–rounded' education. Although instruction, content, and mission vary in schools, this is a different discussion. THe introduction of artificial intelligence, particulary ChatGPT, can complement these traditional methods of education and incorporating it judiciously can provide diverse learning paths, personalizing education and making it more responsive to individual student needs (Yu, 2023).

• The world today is vastly different from decades ago, there is a premium of skills like critical thinking, creativity, collaboration and problem-solving. In the 25 years that I have been teaching, I have seen a progression from long days of gathering research in libraries and books, to using information to construct new products and creative solutions. The skills from decades past have undeniably changed. While AI, including tools like Chat GPT, provide a convenience and streamline various tasks, including research and writing, it also introduces changes in human behaviors, such as reading, comprehension, and communication patterns. There is an evident need for schools to ''adapt'' and evolve learning techniques quicker to keep up with the rapidly changing technology and the skills necessary to be 'better' than technology.

Emerging Educational Platforms

• The onset of AI tools has effected many sectors, including education. With the rise of distance learning and blended models, tools like Chat GPT can significantly enhance educational outcomes. Options for alternative education and online courses where learners can acquire knowledge independently or in new venues is an obvious route. Micro-schools, e-learning platforms, and other educational resources offer flexibility, personalized learning experiences, and access to a vast array of resources, sometimes lacking in the traditional school system. Educational leaders can leverage AI and emerging Web3 technologies to create personalized learning system. These tools offer students a chance to provde student agency, promote equity in learning, and address global challenges effectively.

• Generative Technology has the potential to enhance learning experiences and provide access to vast amounts of information faster and more efficiently than a single educator in a classroom. Although online tools, educational apps, and virtual reality can supplement traditional classroom learning, most schools can't afford these resources, nor are these tools used regularly by those schools that can afford the technology.

#### The Indomitable Spirit of Social Learning

• The social aspect of schools will always be the winning criterion. Any new generative AI education product team must focus on developing a product that will meet the learner's needs in a non-sociable system. Traditional schools provide opportunities for children to develop interpersonal skills, collaboration, and cultural understanding skills. How can generative AI be transformed to include these important learning moments?

#### Equity in Education

• Schools are designed for everyone; whether they are the best or not is a different story. A primary focus for new ed-tech platforms will be providing equitable access for all students, regardless of their background or socioeconomic status. We should remember the need for social equity as educational technology progresses.

The Road Ahead

As technology rapidly changes, the question of whether schools are becoming less relevant and less efficient compared to other learning methods is very complex and debated and a question that needs to be discussed NOW. AI experts are talking about the growth of AI in terms of months, NOT decades. Generative AI has the potential to enhance learning experiences, provide efficient access to information and transform education for all. Still, we must stay focused on the importance of social interaction and equitable access for our learners. Finding a balance between traditional and innovative education will be the tipping point for our future learners.

Reources

"Education is about to radically change: AI for the masses." Getting Smart, 16 Dec. 2022, https://www.gettingsmart.com/2022/12/16/education-is-about-to-radically-change-ai-for-the-masses/.

Wang, Y., Li, Y., & Liu, Y. (2023). Reflection on whether Chat GPT should be banned by academia from the perspective of education and teaching. Frontiers in Psychology, 14, 1181712. https://doi.org/10.3389/fpsyg.2023.1181712

We made it through, now what?

As we did in the past, it is time for us to reflect on how things went in the first quarter, what activities were successful with this year’s group and what things need to be modified.

Reflection is a powerful tool. And during this period of “Post Online Learning,” it is even more essential to take a moment to reflect on all that has happened during this chaotic or sometimes stressful time. Reflection helps us sift through all the emotions we experienced during these moments and identify, label, and sort these experiences.

For @teachingpython, it is a time to evaluate our new group of students and adjust our activities. During our reflection, we use Rolfe et al’s Reflective Framework to look back on our process and goals.

There are a series of supporting questions under each label to help capture details and guide our thinking.

Miro has a great template of this Reflection Protocol, and it works well when working with collaborators.

What? Describe the events

• What didn’t work well?
• What could be improved?
• What was the experience for the teacher?
• What was the experience for the students?
• What were the reactions to learning?

So What? How did this affect your learners?

• What worked well?
• What did not work well?
• What outcomes did we want to achieve?
• What outcomes were not accomplished?
• What connections did students draw from the experiences?

Now What? What possible changes can you make

• What adjustments could we make?
• What new activities can we add to change outcomes?
• What things will we do differently next quarter?

Reflection does not have to be as structured as this, however, the protocol really helps to set a precedence on our thinking. Once you get in the habit of going through the questions, the process flows naturally.

What things are you doing that need reflection? Whether it is the end of the quarter or just an end of a unit. Give it a try!

Google has fixed this issue and allowed Google Colab to be added to Google Workspaces for Education. See their announcement on Twitter, as well as the support article for enabling Colab in your organization.

I have to say that I was impressed with the speed at which the Colab team worked to resolve this issue. You can see the thread on the GitHub issue with lots of engagement from the team.

I am leaving the rest of the article in place with the alternatives to Colab in case you can't use it in your classroom.

Huge thanks to the Colab team for fixing this and keeping this tool in classrooms for learners and teachers!

Sean

One of my favorite apps that I discovered when I became a computer science teacher was Google Colab. Since my students were already very familiar with Google Docs, the concept of a Jupyter notebook within the Google Drive ecosystem was a very natural step for all of us. Students preferred the easy to use interface and we even started creating most of our class assignments using notebooks.

But then a few weeks ago, it all came to a grinding halt.

What's happened

Starting in September 2021, students in K-12 schools began receiving warnings that their access to Google Colab was denied. Increasingly frustrating was that the issue was inconsistent across student accounts. One student could be happily coding away, while the student sitting next to them was unable to access their notebooks. At our school, our technology admins could see that Google Colab was enabled as a marketplace app for all students.

After opening a GitHub issue on the Google Colab project, representatives for Google clarified that access to Colab was disabled starting on September 1 for students marked as being under the age of 18.

From cperry-goog:

We were impacted by the recent change which prohibits access for Education users under 18 to services without an on/off control in Workspace: https://support.google.com/a/answer/10651918?hl=en

We are working to improve access to Colab for Education users in the long run, though I cannot give solid timelines at this time, I am prioritizing this work. For the time being, note that the access policy does not apply to accounts not administered by institutions. As a workaround to allow students to access notebooks, you could also consider using one of our related products, Kaggle Notebooks: https://www.kaggle.com/code

Based on this information, it appears that Google for Education is driving the prioritization of Google Apps and Services that have the correct on/off control in Workspace.

Further, according to this article from TechCrunch, the push to restrict access for Google Workspace for Education students under the age of 18 is part of a broader push to tighten access for minors.

How we were using it

It may not seem like a big deal since there are so many alternatives to code in Python, but Colab had quickly become a core part of our lesson delivery, especially during the COVID-19 pandemic.

For example, a typical week on my computer science classroom might include an interactive coding session where we would teach concepts, a "choice board" homework assignment where students would complete various tasks, and a "class challenge" where the students would have a limited amount of time to figure out how to fix a piece of broken code or solve a coding puzzle.

Each of these assignments worked well in the Colab environment.

• Interactive coding sessions could be started in a matter of minutes without any installations or dependencies
• Assignments could be created in Colab and students could make a copy of the assignment and complete their portions either as text for answers to prompts or code cells for their coding solutions
• Class challenges were easy to standardize knowing that dependencies were met and students could easily upload a screenshot of their final code into our LMS

Alternatives to Colab

As teachers, we've explored a variety of different tools for lesson delivery and coding environments. There are a wide variety of alternatives to Colab available depending on your needs.

Kaggle

kaggle.com

• Cost: Free tiers available
• Ease of Access: Easy to start (see caution below about privacy policy)
• Educational Institution offering: None at this time
• Control: Owned by Google

As cperry-goog mentioned in his response to the GitHub issue, Kaggle is another Jupyter-based coding environment owned by Google. As noted in the response, Kaggle's privacy policy strictly prohibits the use of their services for students under the age of 13 and requires verifiable parental consent for students between the ages of 13 and 17.

JupyterHub

jupyter.org/hub

• Cost: Free, requires server
• Ease of Access: More challenging technical setup and configuration
• Educational Institution offering: Open-source, none
• Control: Open-source, managed by institution

Another option is to set up your own JupyterHub server. While this gives you full control over the server environment and configuration, this can be daunting for your average K-12 computer science teacher. Additionally challenging is the coordination with your school or district's technology department to ensure security and policy compliance. But if you can overcome these challenges, there are quite a few third party packages and extensions to Jupyter like NBGrader that allow you to automate parts of your teaching process.

Replit

replit.com

• Cost: starts at $35/mo per teacher or $750/yr for K-12 institutions
• Ease of Access: Simple sign up, web-based
• Educational Institution offering: Replit Teams for Education
• Control: Run by Replit

This web-based coding environment continues to grow with features. Students can code in multiplayer mode for realtime collaboration, complete assignments using automated test code for grading, and even use graphics packages like Turtle in the browser. Replit runs virtual environments that act more like remote IDEs rather than Jupyter notebooks. While environments can be downloaded, shared, and even committed to Github, they cannot be exported to ipynb format if you require that kind of portability.

Mu Editor / Thonny / IDLE

codewith.mu
thonny.org
IDLE

• Cost: Free/open-source
• Ease of Access: Download & install
• Educational Institution offering: N/A
• Control: Locally installed, open-source

Of course, you could just forget all this silly web-based Python nonsense and just write and run local Python code. There are several great beginner-friendly Python editors - my favorite is Mu. The downside is that they require more effort to download and install, but they run locally and fast. Once you outgrow them, you'll start looking at more advanced IDEs like PyCharm or VS Code.

VS Code Notebooks

code.visualstudio.com

• Cost: Free
• Ease of Access: Advanced setup of multiple programs and packages
• Educational Institution offering: N/A
• Control: Locally installed

Although it's the most complex installation and setup, downloading VS Code, installing Python locally, and pip installing Jupyter will get you a pretty advanced setup. You don't have to run a JupyterHub server, everything is freely available online, and you can customize the offering as much as you need.

On the downside, you may end up in a spiral of dependency management, virtual environments, and ongoing updates that may cost you more time in the end.

Call to Action

So in the end, what can we do?

1. Tell your Google Workspace for Education rep to bring back Colab
2. Explore & use alternatives like Kaggle, Replit, or locally-managed servers
3. Create workarounds

Some domain admins have tried creating Organizational Units that mark students as over 18 while they are taking the computer science course. Other educators have asked students to use or set up personal Google Accounts for Colab.

Unfortunately, educators in the K-12 space are stuck waiting for Google to restore access to Colab. And students who spent hours or days creating code in Colab will have to wait for Google to give them access back to their own code.

So now we wait...

-- Sean

• Code-A-Pillar - This eight-segment robot is sure to get your youngest learner having fun and into coding. This bot has eight segments of coded parts that will send the robot in the direction pictured. Place the segments in a specific order, and watch how the segment lights up during each action. Kids get an early understanding of sequencing, problem-solving by doing, and critical thinking.

• Dash - This quirky bot loves to roll around and make fun noises as the learners code them. Dash has so many advanced features that are used to teach a wide variety of computational thinking skills. In addition, this hearty bot is versatile, comes with four free apps and a wide variety of cool add-ons for more playing fun. Learners can practice learning about loops, sequencing, command algorithms, and conditions. For a slightly more advanced bot with different dialogue, check out Dash’s friend Cue. Cue offers a bit more than Dash, with an interactive AI feature, text-based coding in Javascript and Wonder, and a plethora of jokes and responses.

• Spike Prime is one of our newest friends, and they have stolen my heart. These bots are super sturdy and allow for a variety of bot friends to be designed and coded. With a superb integration with Python, what more can a Pythonista ask for in a bot? How about a solid curriculum to boot? Lego Education provides many ideas and lesson plans that will help you integrate computer science with engineering, science, math, social-emotional skills, and more. Students can follow along with typical lego instructional guides or get creative and build their own creations. The Spike Editor is super sleek and straightforward, and the sidebar service menu of quick Python commands helps students recall and use Python to code their bot more efficiently.

• RoboMaster- Want a bot that will get students in the door of your Robot club? Then the RoboMaster is your bot. Sleek, modern, and full of appeal, the Robomaster has everything you need to intrigue learners. This omnidirectional moving bot has speed and can be coded in Scratch or Python! Learners can practice high-level math and Physic concepts and AI technology. With a large set of commands, learners can program light effects, movements, and so much more.

• AWS DeepRacer We love this bot! With a virtual feature and some background knowledge of machine learning and AI, AWS scores big on this bot! AI is here to stay, and with six sample projects included on the AWS website, you can have this bot moving and rolling around a designed track in just a few hours of ML training. This bot does take some learning, though. I have spent some time learning on the AWS Machine Learning Foundations Course, and it has been beneficial for my understanding of python and Artificial Intelligence.

In Part 1 of this series, we hacked the hand sanitizer dispenser and got it talking to Home Assistant as a binary sensor. For this part, we'll work on a couple of useful automations in HA that will collect data and make it fun for students to sanitize.

By the end of this part, you should have a sensor that shows today's dispenses, an automation that makes Alexa speak and some lights flash, and even an interface to a local MQTT broker to send and receive data with other devices.

Making Alexa Speak

To make Alexa speak, I needed to send her notification commands using the excellent Alexa Media Player plugin for Home Assistant. The best way to install this was using the HACS project.

Adding Yeelight

I had a couple of Yeelight RGBW bulbs left over from a project last year that I wanted to integrate. This is an officially supported integration for Home Assistant. I put one of them into a lamp by the Amazon Echo and used the WhatsApp effect to flash the bulb green when the dispenser is triggered

Dispenses Today

Next, I wanted to track the number of dispenses per day. I used the history_stats component for HA to add up the number of dispenses that day. The config entry tracks the number of times the dispenser went from OFF to ON since midnight that night.

  - platform: history_stats
    name: Sanitizer Dispenses Today
    entity_id: binary_sensor.sanitizer_dispense
    state: 'on'
    type: count
    start: '{{ now().replace(hour=0, minute=0, second=0) }}'
    end: '{{ now() }}'

The Actual Automation

Helpers

I created a simple dropdown helper to keep track of the quips for Alexa to speak. The input_select is used to keep a dropdown list of possible quips. The most recently selected quip is chosen as the current option on the dropdown.

This makes it really easy to add and remove quips from the system as you get tired of them. You can also use Alexa's SSML tags to add inflection, emotion tags, and even interjections.

Automation Steps

The automation itself is triggered when the sanitizer_dispense sensor is set to moving. From there, several steps occur.

1. The random quip is selected from the input_select.quips dropdown.
2. The quip is sent to the Alexa Media Player's notify service.
3. The Yeelight is sent the WhatsApp effect
4. The Twitter integration sends the most recent quip to the Findeiss 1 Twitter account (@FindessO).

Full YAML file

Here's the full YAML file. Once you create a new Home Assistant automation, choose the option from the three-dot menu on the upper right and choose "Edit as YAML." Paste the following into the box and change the names of the devices to match the ones you set up in previous steps.

alias: Sanitizer Dispensed
description: ''
trigger:
  - type: moving
    platform: device
    entity_id: binary_sensor.sanitizer_dispense
    domain: binary_sensor
condition: []
action:
  - service: input_select.select_option
    data_template:
      option: |
        {{ state_attr("input_select.quips", "options") | random }}
    entity_id: input_select.quips
  - data_template:
      data:
        method: speak
        type: announce
      message: |
        "{{ states('input_select.quips') }}"
      target:
        - media_player.pc_s_echo
    service: notify.alexa_media
  - data:
      effect: WhatsApp
    entity_id: light.findeiss_1_table_lamp
    service: light.turn_on
  - service: notify.f1_twitter
    data_template:
      message: >-
        Someone used the hand sanitizer and I said "{{
        states('input_select.quips') | striptags }}"
mode: queued
max: 20

Tracking Historical Data with InfluxDB and Grafana

It's pretty easy to set up InfluxDB to track time-series data using the Supervised verison of Home Assistant. For more information, the Home Assistant documentation is very thorough. While you're at it, adding Grafana is a great way to come up with detailed visualizations.

Once you've added InfluxDB using the Superviser panel, make sure that you have your entities included in your configuration.yaml file. If you're running on a storage-limited device like a Raspberry Pi, then it's helpful to limit the number of recorded streams to just the ones you care about.

influxdb:
  host: a0d7b954-influxdb
  port: 8086
  database: homeassistant
  username: homeassistant
  password: !secret influx_db_password
  max_retries: 3
  default_measurement: state
  include:
    entities:
      - sensor.f1_sanitizer_dispenses_today
      - light.findeiss_1_table_lamp
      - binary_sensor.sanitizer_dispense
      - binary_sensor.east_doors
      - binary_sensor.west_doors
      - counter.printer
      - sensor.findeiss_1_temperature
      - sensor.findeiss_1_humidity

The Finished Project

This project has been running for the majority of the school year and I'm pleased to say that it works very reliably. I've even added a second Raspberry Pi to my setup that displays the Home Assistant dashboard on one of our classroom TVs.

Over the past year, our dispenser has been used 2,838 times. Hopefully that's killed a few COVID-19 bugs. 😀

Digital Citizenship refers to the responsible, ethical, and safe use of technology and the internet. It equips students with the skills and behaviors needed to navigate the digital world while respecting the rights and privacy of others. Good digital citizenship involves understanding online etiquette, protecting personal information, using technology responsibly, and contributing positively to the online community. As educators, it is our responsibility to empower students with the knowledge and skills of digital citizenship, ensuring they become proactive and thoughtful digital citizens who use technology for good and promote positive digital interactions.

We sometimes make assumptions about students' technology skills, assuming they are proficient users due to their daily use of cell phones and computers. However, they might be competent information consumers, and students may need guidance to become more mature content producers. The responsibility of teaching digital citizenship should not fall solely on Computer Science classes but should be integrated into all core subjects.

Although the coding curriculum lends itself easily to incorporating many digital citizenship skills, even the best Computer Science course may focus less than you think on directly teaching these critical skills.

Mike Ribble's post on "Digital Citizenship in Schools" outlines these three key categories: Respect, Educate, and Protect, each encompassing vital elements. Respect involves advocating for equal digital rights and appropriate online conduct. Educate focuses on communication skills, digital literacy, and responsible digital commerce. The Protect category emphasizes understanding digital rights, safety, and personal well-being in the digital world. By incorporating these elements into our curriculum, we can empower our students to be active and thoughtful digital citizens who use technology to contribute positively to the world and advocate for the causes they care about. "Essential Elements of Digital Citizenship."

In this blog, we will explore the importance of teaching digital citizenship in computer science classes, focusing on the three essential categories: Respect, Educate, and Protect, to equip our students for a brighter and safer digital future.

Here are some easy ways to teach these distinct categories of digital citizenship.

Respect

When students are coding, we open the door to the world. Access to produce, scrape, share, and build programs that can do amazing things is at their fingertips. However, not all playing fields are equal. Teaching students to respect their power and what can happen online should be a constant in any computer science class. Equal access and digital rights, appropriate conduct on social media, and understanding digital property rights and ownership are always at the forefront!

Here are a few examples to help students build respect online:

• For helping students learn how to interact appropriately online, look into starting a Discord Channel, joining the Python Discord, or joining Twitter.

• To teach equal rights, follow the projects Call for Code, create a project focusing on the Social Good topic, or have students research great entrepreneurs in the tech-for-social-good sector. These companies use "digital technology to tackle some of the world's toughest challenges."

• For using other coder's programs, have your students cite their source code in docstrings or have them make GitHub accounts and clone the programs. Teach students that code is out there for use, but reproducing it and claiming it as your own is not okay.

Educate

Educating students on communicating online, using digital materials, and being influential consumers is a considerable skill and takes a community to help students develop. And we can do our part in CS Classes too.

Here are a few examples to help students become more literate online:

• For choosing the right tools, introduce your students to multiple editors and have them evaluate which editors work best for their needs. Have students investigate libraries from the Python Package Index and look for a library that can complete a specific job.

• To find and evaluate the best tool, have them build literacy by searching for a particular solution to an abstract problem and analyzing the search results.

• To be strong digital consumers, have students design a maker/tech project. Incorporate a materials list and budget requirement so that students need to search for the best and most economical materials online to build their project.

Protect

Safety online and offline is always our priority, but as teachers, we need to ensure that we also model it in all classrooms. Taking care of our online digital footprint and our offline personal health should be everyone's job.

Here are a few examples to help students become healthier digital users:

• One thing that is difficult to do when teaching coding is not using the computer. However, there are a few options that you can do to help instill healthy use online. Use time blocks for work. Allow students to take a break after 25 minutes of work, encourage students to walk away from the screen for five minutes, and rest their brains and body. There are also unplugged activities. Many activities promote CS topics without using the computer online; check out https://csunplugged.org/en/ for a few examples.

• For teaching about security, discussing the importance of keeping passwords secret or using complex passwords is essential. A fun activity is to help students code a password generator. While coding it, you can discuss the importance of longer passwords and not using common words. You can discuss 2-factor authentication and add some AI programs to the course.

• Students need to understand how websites use data collected from Internet searches, phones, and computers can put them at risk. Discussing Machine learning is a fun entry point in seeing how websites use this data to collect information about the user. In addition, Common Sense Media has an excellent example lesson that can be modified and enhanced.

By prioritizing digital citizenship in our curriculum, we equip students to leverage technology for positive change and become responsible tech users. It is our role to nurture proactive and positive digital contributors who utilize technology to create a better, more inclusive world. Taking an active part in teaching digital citizenship skills is very important in the computer science classroom, ensuring that tomorrow's leaders are well-prepared to harness technology for the greater good.

"Practice makes perfect."

"10,000 hours to be an expert!"

"Repetition, repetition, repetition!"

These adages have echoed through the corridors of time, emphasizing the importance of repetition in mastering a skill and I remember them vividly from my childhood. To be good at anything, you need to do it over and over again. Full stop.

Educational pedagogies, philosophies, and teaching styles evolve and become jumbled and intertwined over time. Educational reform movements emerge, and often, old teaching methodologies get overlooked on the sideline. Amoung these changes, certain methodologies like PBL, AGILE, MYP Approaches to Learning, standards-based education, and "playful learning" have emerged as effective means of teaching. All of these might seem very distinct, but with a closer look there is a common thread. They all have one thing in common; the simple fact that each follows a basic recipe that allows students to drill their learning and practice repetitively. This iteration—whether through project-based learning, AGILE methodologies, or student-led discovery—enables learners to correct misconceptions and build on their knowledge foundation.

True learning is characterized by the act of 'doing,' confronting mistakes, and reflecting on the outcomes. Students must write a lot, fix writing errors, and manipulate their words to become better writers. Readers must read as much as possible, slow down their thoughts, and struggle over new words and concepts regularly to become expert readers. Athletes must practice daily, train their muscles, fall, and sometimes lose to develop their skills. Furthermore, developers must write many lines code, fix thousands of errors, iterate continuously, and rack their brains to solve problems to become expert coders. Regardless of the discipline or hobby, there's no shortcut to expertise—consistent, deliberate practice is key. Practice does make perfect, or at least closer to it.

An alert learner must practice time after time, day after day, to commit a skill to the long-term memory. However, it's essential to differentiate between mere repetition and deep practice. While repetition can embed skills in our short-term memory, deep, attentive practice is what truly ingrains them in our long-term memory. With deep practice comes neural development. Daniel Coyle, in his book "The Talent Code," eloquently puts it as, "Practice makes myelin, and myelin makes perfect." (The Talent Code 2009.)

)

Active learning, where you challenge your neural pathways, is what solidifies knowledge. "Systematically firing" your neurons during active learning exercises helps to build the coating that solidifies your neural pathways. You must always be in the "sweet spot" of learning to build neural connections. The sweet spot is activated during activities defined by Bjork as "desirable difficulties," opportunities that require neurons to fire and struggle. That struggle, while often frustrating, is a critical component of effective learning.

Yes, the struggle is real!

Coyle provides a vivid example of deep practice by asking us to imagine navigating an unfamiliar dark room. You begin to explore, feel around, bump into things and possibly fall. You get up and explore more, circling the room multiple times. Eventually, bruised and full of adrenaline, you begin to build a mental image of the room, and eventually, you can walk it "quickly and intuitively." You practiced this learning little by little, over and over. And more importantly, you could feel and visualize the process as you learned. It was often painful, but this feeling helped you to learn more. This, in essence, is the deep "myelin" learning and is a testament to the power of drill and practice.

By definition, 'drill and practice' goes beyond rote memorization.'Drill and practice' is one of the most critical learning methods you can apply when learning how to code. It's an instructional method characterized by systematic repetition to perfect a skill or procedure. It is not rote memorization of syntax or concepts or repetitively practicing the same things over and over. But more than just repetition, it is an awareness that the learning is happening as you practice. It is this "feeling" of connection, repetition, struggle, and alertness that keeps your learning productive. The next time you embark on mastering a new concept or skill, embrace the struggle, relish the learning moment, repeat what you studied and practice what you learned.

Remember it is not only about the product but also the journey.

Happy 'Myelin' Learning!

Coyle, Daniel. The Talent Code. New York, Bantam, 2009.

The term' drill and practice' is defined as a method of instruction characterized by systematic repetition of concepts, examples, and practice problems. Drill and practice is a disciplined and repetitious exercise used to teach and perfect a skill or procedure. As an instructional strategy, it promotes knowledge or skill acquisition through systematic training by multiple repetitions, rehearse, practice, and engages in a rehearsal to learn or become proficient. Similar to memorization, drill and practice involve the repetition of specific skills, such as spelling or multiplication. Developing or maintaining one's particular skills, the subskills built through drill and practice should become the building blocks for more meaningful learning. https://www.brainscape.com/academy/drill-and-practice-in-education/

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Pattern recognition is a fundamental skill that holds great importance in Computer Science education. In 2016, a study by Rittle-Johnson et al. investigated the impact of teaching pattern recognition in early mathematics education. The findings revealed that cultivating students' ability to identify patterns and fostering strong pattern awareness had a positive influence on their comprehension of more complex math concepts in subsequent years. Basic pattern awareness suggests that the brain actively engages with concepts and endeavors to establish connections between previously identified patterns. This, in turn, boosts students' confidence in dealing with advanced math topics.

Engaging with patterns and making connections not only aids comprehension but also enhances the retention of concepts. Pattern awareness is a staircase-level skill with complexity that increases as the difficulty of the concepts increases. When students become good at identifying simple patterns, they began seeing these patterns and applying them to concepts elsewhere. Therefore, drawing deeper connections with the subject area.

The Cognitive Theory of Pattern Recognition Techniques states that patterns are dependent on a person's knowledge or experience. When dealing with patterns, increasing experiences and information can help the brain seek out templates or other prototypes in long-term memory. (This topic has helped stem machine learning topics regarding pattern recognition in computers. To read more about pattern recognition, click here: https://www.analyticsvidhya.com/blog/2020/12/patterns-recognition-the-basis-of-human-and-machine-learning/ )

Applying this technique to concepts taught in Computer Science is a great way to help students identify patterns in the specific coding language and transfer the knowledge to other Object Oriented languages. "Over time, exposure to these problem-solving situations gives us a subconscious familiarity with their essential nature that we can hardly articulate in words, but which we can easily put into action. (NOVA, 2013)"

An effective way to introduce pattern recognition in Computer Science is by using the concept of objects and methods. Even in the first few days of teaching students to code, showing how methods are applied to an object can help students progress as they learn more complex Python concepts. Helping students see the pattern between an object and the methods applied to an object helps them build the baseline understanding of how the relationships between them work in an object-oriented programming language without introducing OOP.

Below are five tips on how you can begin teaching patterns using Objects and methods.

1) Repeat and Highlighting

One of the first things to do after printing "Hello World" is to teach the students variable names and 'how to' assign a string data type. However, do not just type a variable and write a string. Try to have a specific way of repeating and highlighting the existing pattern and making a routine for future code-along activities. In our coding class, we refer to each data type as an object and reference the variable name interchangeably when referring to data types. (This simplifies things for Newbies.)

2) Active Teaching

We focus a lot of our attention and time in the early weeks, reading each python line of code aloud as if we were saying it in a sentence. We read both from right to left and left to right, ensuring that each symbol is correctly identified, seen, and spoken. This active teaching strategy helps to commit the language recognition to long-term memory.

For example:

This line of code will read:
[right to left] -- "the string Kelly is assigned to the object/variable, 'first underscore name' or
[left to right] -- "the object with the variable name, 'first underscore name' is assigned to the string Kelly.

I often interchange the words variable and object to reinforce that these are variable names, and we use them as placeholders. I try not to commit to the word variable or the object at this point but stick to saying both. However, identifying these as objects makes it easier to talk about applying a method to an object. (Remember these are 10/11-year-olds coding for the first time.)

3) Tangible metaphors

It is essential to associate the pattern with something familiar or tangible to a new coder. For example, if we use a metaphor for an object they know, like a piece of bread, when we start to discuss methods, it is easy to explain that a method can be applied to an object. We can use bread as our object, and 'Toast' is our method. We can apply the "toasting" method to the bread to change it. We can also apply the "buttering" method to a piece of bread to change it to 'buttered bread.'

Did you notice how the object has a method applied to it? This reminder helps students make connections when we transition from strings to lists or dictionaries.

4) Identify syntax patterns

The other pattern to highlight when working with objects and methods is the syntax and specifically the parentheses. Calling attention to the parentheses at the end of the method will prepare the learner to consider later what can happen inside the parentheses of the methods.

For example, when we append a list or apply the method append to a list object, we can fill in the parenthesis with the object we want to append. Identifying the parentheses early on in a string method like .lower() calls attention that this is a pattern in Python.

5) Always reinforcing the Basic Pattern

Calling attention to other instances that require understanding objects and methods, is when we work with libraries such as the turtle library or the pillow library.

For example, often expert coders 'import turtle as t' or 'from turtle import *.' However, I prefer not to teach these at first and show students only 'import turtle.' (You can also use the 'from turtle import Turtle' option, and it helps to accomplish the same pattern without needing to explain turtle.Turtle())

This import helps enforce the rule that students need to use the object turtle with a new name; thus, when we apply methods to the turtle, we can make it 'move.'

Keeping to the basic patterns reinforces that a 'method is applied to an object,' and the object is 'turtle.' Using the import and naming turtle as t may lead students away from seeing patterns. Furthermore, can also identify new names of turtles as Bob or Sally for more turtle fun. This helps to call attention to the pattern that existed when working with strings and lists and other data types. We also can reinforce the argments within the parenthesis.

These are just a few of the ways to teach pattern recognition in early Python coders. The simple things you do when teaching the basics of Python can make a huge difference in students understanding later on. Helping students see the patterns with the grammar and syntax of any language can help students see the bigger picture. This solid knowledge base provides a template for coders when moving to more complex topics such as objects and functions.

Resources

Rittle-Johnson, Bethany & Zippert, Erica & Boice, Katherine. (2018). The roles of patterning and spatial skills in early mathematics development. Early Childhood Research Quarterly. 46. 10.1016/j.ecresq.2018.03.006.

"The Science of Smart: The Virtues of Confusion." PBS, Public Broadcasting Service, 19 Feb. 2013, www.pbs.org/wgbh/nova/article/the-science-of-smart-the-virtues-of-confusion/.

Youguo Pi, Wenzhi Liao, Mingyou Liu, and Jianping Lu (2008). Theory of Cognitive Pattern Recognition, Pattern Recognition Techniques, Technology and Applications, Peng-Yeng Yin (Ed.), ISBN: 978-953-7619-24- 4, InTech, Available from: http://www.intechopen.com/books/pattern_recognition_techniques_technology_and_applications/theory_of_co gnitive_pattern_recognition

Bonwell and Eison (1991) described Active learning as a "process of engaging students in "doing" activities". It is a multimode process of delivering topics, knowledge and engaging students in a deeper understanding of topics. Active learning is a unique technique but sometimes it is difficult for students and teachers to begin. (To learn more about Active learning check out The Center for Teaching at Vanderbilt article Active Learning

There are many reasons why active learning is not used often in classrooms:

• Teachers must change their roles as knowledge experts to experienced mentors.
• Active learning lessons take more time to plan and to teach.
• Active learning requires students to transition their role as passive recipients into active risk-takers in the learning process, and this is sometimes a difficult transition for students.

Active learning takes commitment, and it is often easier to slip into a 'content expert role' in a computer science course. Instructors can get hooked into demonstrating cool tricks and code chunks that seem to flow with ease; and teachers can cover more topics in a shorter period of time. However, students may be quickly copying the instructor's code, but they may not have time to process or "chew" into the topics.

Although computer science teachers may feel that the students are engaged with code alongs, the lessons' copying and coding techniques may resemble old-school lecture and note-taking activities from other curricula, resulting in less learning than originally planned. This lecturing resembling activity can result in computer science classes becoming a face forward, rote learning experience instead of an active one.

So how can Computer Science teachers change necessary code-along sessions into highly engaged active learning experiences?

The code-along activity can become an incredible active learning experience. It can be a high engagement activity that propels student understanding to a new level. A typical "I code, and you copy" event becomes a brainstorming, questioning, discussion, demonstration, and highly motivating experience! (To learn more about Active learning activities check out Queens University Course on Active Learning Strategies. )

So how do you start planning for an active learning code-along? (If this is your first time using active learning exercises, make sure you know your students, have established rapport, and student norms are explicit.) Consider these questions as you are preparing your active learning lesson.

• When preparing an active learning lesson, these questions are useful for planning:
• What is the most important thing to remember is your lesson's objective?
• What is the goal of the lesson?
• How will you know that learning happened?
• What will you assess?
• What do the students already know?
• How long will the lesson take?
• What level of understanding do you want to achieve?
• What are the desirable difficulty levels for the students?
• What activities will you use to teach the concepts?

Let us use simple functions as an example:

• Objective: Functions can be used to repeat an activity in your code and use them successfully to complete a specific repetitive task.

• Prior Knowledge/Activities: Sample exercises, definitions, example code

• Goal: Develop a generic "app" that has multiple functions.

• Assessment: Students will manipulate the final code and add their flair.

• Lesson duration: 45 minutes

• Level of Understanding: Understand the importance of functions, can see the benefit to using them, can use basic functions in code.

• Hook(Brainstorm): Ask students what to make: Give suggestions, a contact app, a friends app, a birthday info app, etc. The hook helps you connect on a topic that interests the students, and by providing some suggestions, in the beginning, you can guide the suggestions to ensure that functions will work well with that topic.

• Possible Activities:

  Think aloud: Work together as a large group, one student explains one step on how to complete the app, and another student writes out the steps needed(in Pseudocode) to make the app. Ensure that you call on as many students as possible.

  Peer Instruction: The Teacher starts by asking a question, What would be a good name to define the function for _____? Give students few minutes to make a function name for all the steps designed during the think-aloud. Then call on students to define the function's name with "pass" and write these down for the code. Guide the names that are not descriptive, and check syntax.

  Work together in groups: Assign a function for each group to write a docstring for. Share.

  Pause procedure: Use the pause procedure to add wait time between posing questions and waiting for a response. Students will often wait and allow the teacher/coder to code for them. Be prepared to wait extra time initially and make sure that the same students are not solving all the coding challenges.

  Demonstrations: The Teacher begins coding on a particular function, demonstrates how to look up library methods and functions, for example, using the datetime documentation, or the Teacher can force code errors and challenge students to fix the code.

  Retrieval practice: Code some, and wait. Seek out responses and quick check-ins for students to recall previous concepts. For example, Teacher says, "This function needs a keyword argument. Why do you think this is true?" Have students recall what a keyword argument is, have them explain why and their reasoning."

These are just some activities that can be incorporated easily into a code-along lesson during Computer Science. What other ways can you turn your code-along activities into something more active?

Game, Prodigy. “8 Active Learning Strategies and Examples [ Downloadable List].” Prodigy Education, [www.prodigygame.com/main-en/blog/active-learning-strategies-examples](www.prodigygame.com/main-en/blog/active-learning-strategies-examples)

https://users.cs.jmu.edu/adamses/Web/CS430/Lectures/p52-mcconnell.pdf

https://cft.vanderbilt.edu/wp-content/uploads/sites/59/Active-Learning.pdf

"A human being should be able to change a diaper, plan an invasion, butcher a hog, conn a ship, design a building, write a sonnet, balance accounts, build a wall, set a bone, comfort the dying, take orders, give orders, cooperate, act alone, solve equations, analyze a new problem, pitch manure, program a computer, cook a tasty meal, fight efficiently, die gallantly. Specialization is for insects." — Robert Heinlein

I was at the right place at the right time, and now I am a coder. This is not the case for everyone in the educational system who teaches coding. Most people are often surprised when I mention that I only began coding three years ago. I did not come into coding of my own "free will", though the reason I am still at it and why I love it, would no doubt cause some surprise.

Anyone who wants to develop a specific skill set, for example, learning to play an instrument, has to maintain a focused and intense effort to rack up as many hours of practice as possible. This deliberate effort is guaranteed to allow a person to develop expertise in the subject. However, if one procrastinates, one is unlikely to achieve success, nor will one be able to "catch up" to others who started sooner and were more diligent and focused.

There is a direct correlation; the more effort one puts in, the more likely one is to succeed. This focused learning concept is not rocket science, nor is it a newfound method for learning something; so how come, then, more of us are not experts in our fields? Why are we all not specialists in something?

Epstein highlights stories of the world's most successful athletes, artists, musicians, inventors, forecasters, and scientists, and throughout these epic stories, he proves that generalists, not specialists, are destined to surpass the greatest in the field. Generalists frequently set their path late, and they manifest numerous interests rather than concentrating on a singular one. They are also more imaginative, sprightlier, and far more relevant than their more focused peers.

Barbara Oakley, who wrote "Mindshift", also believes in the power of "second career" learners. Those that learn an opposite skill enhance their confidence and career prospects.

Is it possible that everyone learning to code later in life can achieve the same goal? I believe so.

Does one need to be a programmer and only code for a career? No, but you could if you wanted to.

I am no different from most educators who have a passion for learning. There is a desire to understand what is unknown and research more, and learn deeper in our obsession. I say obsession in a truly positive manner.

Nevertheless, is staying a specialist in only one field always the best option? How can we, as teachers, embrace lifelong learning if we do not struggle to learn something new throughout our lives? What new skill can you learn today that is completely opposite of your current role and may require you to struggle and fail?

What can you do that will surprise you?

For all those who say, "I can't code" or "You can't teach an old dog new tricks." I challenge you!

When I started to code, I really did not appreciate the powerful change that was about to occur, not only in my teaching but also in how I think and solve problems. After reflection, I identified moments where both my weaknesses and strengths benefited me; an understanding of the power of 'switching gears' between my passions and work; and a realization that a new way of encouraging students needed to be adopted.

The Benefits of your Weaknesses

Learners come in all 'shapes and sizes.' I learned quickly during my pre-med Biology program that I was not a good memorizer. It took a lot of effort for me to recall things. However, in some courses, like Anatomy, I excelled because it had a lab associated with them. I remembered muscle groups and bones from the lab and dissection exercises because I was 'doing' the investigation. Being active in your learning helps your brain to recall and process as you learn. Active learning is defined as "any approach to instruction in which all students are asked to engage in the learning process.

Mastering content or a new role in your job is possible. If you have the luxury of learning it at your own pace, wonderful. If you have a deadline, do not stress. Steady and consistent learning with positive growth is attainable. I like to remind myself of a quote from the book High Expectations Teaching, "Smart is something you can get." Take your time to digest new material at your own pace.

Always identify your strengths and weaknesses in learning. Look for ways to use your strengths to minimize, while still growing, your weaknesses. When I learned how to code, I took every possibility to talk code out and code as I learned. I also wrote things down a lot. I needed to "do" in order to learn.

When I started to teach code, I encourage the students to write a lot of code. In a one-quarter course, my 6th graders roughy type 8000 - 15,000 lines of code. People are surprised by how much my students learn. I know that part of their success is due to their "doing of the work!"

I am a very slow reader. I take every opportunity to read as much as possible and various types of reading material. To improve a weakness, you need to practice that weakness intentionally and faithfully. When you code or try to solve coding problems, it is essential to sift through reading material to develop a solution. My reading weakness is offset, yet still practiced by my strength in information and media literacy skills. I can locate valid and reliable information that is easier to comprehend. I improve my reading and research skills and become faster at finding the right information and still process what I read efficiently.

Focus on your weaknesses not because they set you back but because they help you find new ways to succeed. In Mindshift, they discuss the fact that bad memorizers are often very creative, just because you cannot commit things to memory as quickly as others, do not stress, you have a strength in you that they may not have. Use your creativity to enhance how you learn and work.

Ability to Switch Gears

One of the concepts that really played a critical role in my learning was my work environment. In the MOOC course, we discussed how the people you hang out with can strongly influence who you become. For me, this is a resounding, 'YES, I agree!" I would add that having two opposing environments in your life can be beneficial to your work and health.

Learning to code takes a commitment to learning. This is especially true if you are trying to make a career shift as a developer. You may feel that you need to learn everything you can, all at once, to try to catch up with those who have been coding for years. At times imposter syndrome may kick in, and you push yourself more. "Go! Go! Go!"

Trying to learn too much at one time is counterproductive. You need to switch gears and surround yourself with the right people. Your environment for learning is critical to your success.

At work, I tend to surround myself with active learners and do-ers. These are people who take courses for the experience of learning and not just the degree. People who take on projects because they learn by doing; people who read books to better understand life and who always push themselves to improve, not only because they have to, but because they are committed to becoming life-long learners. These people are continually pushing the limits and motivate me to always try to outperform my current self. Surround yourself with colleagues or peers that inspire you and help you improve.

At home, I am surrounded by family who reminds me that switching off and slowing down provides me more time to play, read magical stories, and create new things and crafts. They remind me that less is more, and the freed-up time makes space for more fun, love, and creativity. Switching off provides time for me to focus on my health and well being. And it gives me the added benefit of allowing my brain to organize all that information that I learned during the day.

These opposing lifestyles help to create positive environments that contribute to productivity and success. I like to think of it as an "extended 8 hour Pomodoro method" of work and focused learning with "extended 5 hours" of play and diffused learning. Switching gears and learning multiple things will help you grow your knowledge stack and 'broaden your passions.' Your environments can be various too, and not just at home.

Take a look at the environments where you live and work. Are they conducive to growth and improvement? Do they expose you to new areas that will encourage development? If not, change your environments,

Adopting a New Pedagogy

When I was little, I loved everything about porpoises. I wanted to be a marine biologist. I loved being on the boat in the middle of the ocean. People who loved me encouraged me to follow my passion, all except my Marine Scientist godfather, said, "Don't follow your passion, let that be your hobby. Being a Marine Biologist who only works with dolphins may be too specialized; you need to make sure that you have a backup plan."

Follow your passion. It is a common statement that many adults tell children. It is well-intentioned, but it can cause a bit of a stifle in the future. This also applies to adults. Following one passion is not bad, but it does not allow you to broaden yourself. To expand in areas and develop skills that may become your passion one day. Having a job where you are specialized or only know one thing can backfire on you and leave you questioning what next.

Don't encourage students to just "follow their passions". Encourage them to find many passions. Encourage them to find a love in learning and investigating new things, and developing the topics they love.

Picking up a hobby and learning something new can help you grow as a learner and help you in your current career. Take some online courses, learn new topics, pick up a new hobby or craft, or read various books. You never know how learning a new skill can brighten and open up your future. As quoted from the Mindshift course, "With the disruption of the new information economy comes plenty of new opportunities. Be prepared for a lifetime of learning!"

Resources

Mindshift: Break Through Obstacles to Learning and Discover Your Hidden Potential
by McMaster University https://www.coursera.org/learn/mindshift/home/welcome

Mindshift: Break Through Obstacles to Learning and Discover Your Hidden Potential Paperback – April 18, 2017

Human beings do not live in the objective world alone, nor alone in the world of social activity as ordinarily understood, but are very much at the mercy of the particular language which has become the medium of expression for their society. It is quite an illusion to imagine that one adjusts to reality essentially without the use of language and that language is merely an incidental means of solving specific problems of communication or reaction. The fact of the matter is that the real world' is to a large extent unconsciously built up on the language habits of the group... We see and hear and otherwise experience very largely as we do because the language habits of our community predispose certain choices of interpretation."
Edward Sapir (quoted in [Whorf 1956])

This quote emphasizes the fact that the languages we speak directly influence the way in which we view the world. This is true not only for natural languages, such as the kind studied by the early twentieth century American linguists Ed- ward Sapir and Benjamin Lee Whorf, but also for artificial languages such as those we use in programming computers.

Excerpt from Oregon State book, OOP Thinking Chapter 1)

How do we get our students to start thinking about Object Oriented Programming while still teaching procedural coding practice?

Object Oriented thinking, a term that we have adopted in our classroom and curriculum, is a term that means moving from procedural thinking in coding basics into a more object/method process of thinking. Object Oriented programming concepts such as classes and instances are challenging topics for beginners to comprehend, but by reframing and helping students identify patterns, you can make learning OOP easier. Object Oriented thinking is a great way to get students to start thinking about Python objects, methods, and jobs in preparation for the transition into more complex OOP code.

Understanding Object Oriented Programming as a new coder has always been something that has failed to make sense to me. I can copy it. I can read about it. However, when it comes to writing classes or preparing my students for more OOP, I struggle to do it. Finding ways to teach students why a sprite is a way it is with a dunder init function, or how to think about writing classes without just copying someone's code is difficult. Moreover, I do not think I am alone.

When I first started coding, I googled OOP. I read a lot. I know Python is an OOP language, a language based on objects. Got it! When writing code from books, readers are instantly thrust into copying classes of rockets or other objects to move around a screen. You can replace class names and then call the code your own, but how much is really learned?

How much of what is copied makes sense enough to write an original program? I would wager that most students do not get it.

"The mind unlearns with difficulty what it has long learned." -Seneca

Objects have methods, and different instances of objects exist.

Creating a new class creates a new type of object. This allows for new instances of that type to be made.

The DRY method, don’t repeat yourself, of using Classes and instances allows us to limit repetition within code, and reduce redundancy.

We learn something. We use it daily. It becomes second nature and it makes sense to us. Therefore, it must make sense to everyone, right?

Wrong!

OOP languages make sense to many developers or lifelong coders but it is often difficult to find ways to explain it to new coders because it is difficult to "unsee it once you learn something. " And sentences like this one from, Geeks for Geeks make no sense to a beginner but seem very logical to an experienced coder.

"Creating a new class creates a new type of object, allowing new instances of that type to be made. Each class instance can have attributes attached to it for maintaining its state. Class instances can also have methods (defined by its class) for modifying its state."

It is difficult to see what new learners are unable to see. It is often hard to remember and teach the "stuck" feeling when you cannot remember what kept you from not 'seeing' the objects in the first place. A long-term coder who has mastered OOP concepts sees the patterns while a new coder fails to make the connection.

It wasn't until I started to see the patterns and connections that classes and methods made sense.

How do we get our students to start thinking about Object-Oriented Programming while helping them to transfer to a less procedural coding practice?

Teaching students about classes is not as easy as we think it to be. It is not a simple ' I code, you code'; they got it. It is a lot different than the procedural paradigm of coding. After 4-6 weeks of coding, students can generally write basic original programs on their own. The procedural method is easy for students to understand and mimic because it has been learned before, in science, in narrative writing, and in other courses. Write what you need to do from top to bottom and read it from left to right.

You see it in a beginner's code every day and as they progress to using more complex code in their turtle programs.

What if, during the early stages of teaching students to code, procedural instruction of coding is intertwined with OOP thinking?

To make real use of object oriented programming, we often need to teach students how to see the world in a new way. The way a programmer thinks about solving a problem is typically the way that the code will be developed. Transitioning the way we teach problem solving and designing code can help a student feel more comfortable with object oriented programming.

By introducing this way of thinking, students can begin to imagine pieces of code as objects that have jobs(procedures) and methods of doing their job. Furthermore, more complex concepts, such as objects, are introduced, and refactoring code throughout instruction can help students use terminology and skills necessary for OOP. Starting students with the refactoring of procedural code and identifying more object-oriented thinking can help students "unlearn" the need to make all code procedural and understand that they may need to use OOP to do cool things.

This video from Linkedin, offers insight into how students can see code in a more procedural cookbook way versus through objects and methods. These metaphors help to create mental images for the two thought processes of coders. Its simplicity and visuals offer learners and teachers a good starting point for Object Oriented thinking. Moving between procedural and object oriented paradigms happens as the code becomes complex and the need to reduce redundancy becomes obvious.

Four tenets to designing lessons that promote object oriented thinking

Teachers put a lot of time into designing lessons that help to develop skills in students. The collective skills that a coder needs to develop in order to produce original code are complex. It is not a simple task and requires a wide variety of skills that are intertwined. A few basic tenets can be used to help students develop a more object-oriented way of thinking.

The first tenet is to teach students how to read code both "top to bottom-left to right" as well as "right to left and bottom to top."

For example:

greeting = "hello"

Procedural:

The variable "greeting" is assigned to the string "hello".

OOP thinking:

Thinking: The string "hello" is assigned to the object called "greeting"

For example:

Procedural:

Reassign the greeting variable to another variable name and make it title case.

OOP thinking:

Apply the title method to the String object to capitalize greeting and assign it to "title_greeting"

The second tenet is to use language that will help students communiate and develop a more object oriented way of thinking.

The information in provided in inline quotes and is repeated to the students. It is used to reinforce the language of object oriented coding.

For example:

Procedural:

import turtle as t #always write this to import turtle

t.forward(100) #make t move

OOP thinking:

import turtle #import turtle library with all the functions and methods

bob = turtle.Turtle() #assign the turtle object turtle from the Turtle class to an object named "bob"

bob.forward(100) #apply the method .forward() to make turtle move give it parameter for distance

I like to tell my students:
"The turtle module is a library full of all kinds of functions and methods that some cool coder programmed for us. These cool coders wrote all kinds of libraries with objects, classes, and methods, so that all we need to know how to do is read the documentation and write the essential lines of code.

I follow up with:

• Different ways of doing something to an object exist in code.
  • We can apply functions and methods to make an object react.
• Objects exist in Python, and we apply methods to them.
  • .lower(), .append(), .keys()

The third tenet is to point out the patterns and repeat often.

Throughout the course, I like to help students see patterns.

The patterns that exist in code are beautiful. Lining up different types of objects and methods in code can help students identify patterns easier. Using color and writing on whiteboards also helps. The basics of code and identifying a few easy patterns can help students understand more code complexities later on.

For example:

Methods are applied to the objects. Students can see this with string, list and dictionary methods easily.

The fourth tenet is to use mental images and comparisons with ordinary objects.

• Objects can be different things, just like objects in our lives.
  • strings, lists, dictionaries, turtles are the same as chair, car, cookies, and games
• There can be many objects of the same data type.
  • We can put many lists, strings, and turtles in our code. Just like we can have many types of chairs, cars, cookies, and games.

Helping students to start visualizing, and comprehending the patterns in code is a great way to help them comprehend OOP.

These four tenets are a good start for developing OOP thinking. There are many more techniques such as desiging and developing solutions that can also help with the mindset.

In addition, keeping these questions in mind as you develop lessons can help you plan more effective lessons for more object oriented thinkers:

• How can I explain things better to my students?
• How do I ensure that eventually, they will "see" objects and never unsee them?
• When do my students need to know and understand classes and instances?
• When is the right time to teach them this?

What other questions exist? How do you you get your students to start thinking about Object Oriented Programming while still teaching procedural coding practice?

OOP Intro Chapter 1 Thinking Object Oriented. http://web.engr.oregonstate.edu/~budd/Books/oopintro3e/info/chap01.pdf.

Stone, Olivia Chiu. “Object Oriented Thinking - Python Video Tutorial: LinkedIn Learning, Formerly Lynda.com.” LinkedIn, 27 Nov. 2018, www.linkedin.com/learning/programming-foundations-object-oriented-design-3/object-oriented-thinking.

The best thing about Python is that there are many Python libraries and projects that facilitate teaching complex topics in other curricula. From data science and graphs to probability and math to analyzing text, Python makes learning complicated concepts unique!

Analyzing extensive or lengthy text is one skill that is common in both English and Humanities courses. Students often have difficulty finding meaning or comprehending text. However, two python libraries useful for "scraping" the web and understanding language are Beautiful Soup and the NLTK project.

The NLTK project library is "a wonderful tool for teaching, and working in, computational linguistics using Python," it is "an amazing library to play with natural language." Overall, the NLTK library helps the computer to analyze written text.

Literacy experts have determined that readability for multiple ages increases when a sentence is 15 words or less. This code allows the user to select sentence length and the number of sentences to extract from the text to produce text that is easier to read and comprehend the text's overall meaning.

This project from the book Real Python Projects is an excellent example of how these two libraries work together and can help English teachers, teaching reading comprehension skills and analyzing text.

In this well explained and elegant project, each function is defined and explained.

The program gets a text from a website (requests library), tokenizes it into smaller sentences, removes stopwords or words with little meaning, and then looks for words with a higher frequency.

In Vaughan's example, he uses Martin Luther King's "I have a dream" speech. This speech is also useful in school and is a great activity to use in January to highlight Dr. Martin Luther King's birthday. It is also an excellent example to demonstrate how the NLTK library works. (To read more about the NLTK library, check out this tutorial from Data Camp, "Text Analytics for Beginners."

Projects like these are great ways to incoorporate authentic assessments and projects into any classroom.

In Computer Science class, designing quality learning experiences meaningful to our students is the ultimate goal. Developing ways to accurately evaluate students' learning using real-world situations that are applicable yet challenging is the underlying focus.

This is part two of a blog series that takes a deep dive into authentic assessment components and what entails quality assessments. Authentic Assessments in education are a complex topic full of multifaceted features.

Grant Wiggins asks a great question in many of his assessment articles. One question that permeates is, "What is a true test?" In Wiggins's explanation, a "true assessment" not only measures intellect but should also be a replica of performance that professionals experience every day yet differentiated to the appropriate age. The assessment should not measure a checklist of the average abilities that other students can achieve and the rote content from a text but should be less superficial, less recall of a single performance, and mirror the real-world goals.

When designing an authentic assessment for Computer Science, we first need to identify what are the actual tasks that we want our students to be good at by the end of the course. The "test" of proficiency in code should not be completed at the end of teaching each concept or done because we need another grade in the gradebook. A well-designed assessment is similar to a programmer's daily role to get the job done.

It is sometimes difficult to know or understand a professional programmer's role if you have never been a programmer. Therefore, designing activities that mirror authentic jobs in the field may be difficult. However, with proper research and discussion with other professionals, we can devise the student's learning experiences more accurately. Look for the skills needed as a programmer as well as the content and knowledge. Also, depending on the students' age, specialization in a particular field, such as front-end design or Machine Learning, or web development, maybe a primary focus of skills. If students are younger, focus on developing computational and soft skills, such as learning new concepts and applying them to other problems, communication skills, problem-solving, or asking good questions. The specific coding language may be a perishable skill for some students' future; however, focusing on durable skills can help ensure authenticity to the real-world experiences.

Grant refers to a concept known as "evidence of knowing." As educators, we must first decide the activities students will be good at and the proficiency level we wish them to reach before assessing them. What is it that we want them to do is the primary focus.

Knowledge is vital for students to obtain during instruction. Computer Science teachers have a curriculum filled with content that needs to be understood and recalled frequently to succeed. However, the ability to recall information is not an authentic assessment of a programmer. For example, knowing that a list is mutable, used to store and access various data types, be nested, and looped through is fundamental for a student to obtain and know; however, assessing these facts' by regurgitation is not a valid assessment. Students should use this knowledge to determine when a list is beneficial for solving a unique problem in an authentic challenge.

Here are three tips when designing authentic, true test assignments.

• Look to do: As you dissect the curriculum, look for areas in the learning that focus on recall and disconnected "dysfunctional habits" and switch them for more process-focused, connected, and active activities that allow students to "do" the learning. Software developers research, design, test, evaluate, identify, determine, maintain, communicate and write code. It is a job that is always "doing" something. If most of your curriculum is watching, listening, or reading, switch those activities for more active learning activities.

• Use what is there: Developers look for areas to modify existing programs or upgrade existing code. Use former students' code or your own code, and have students improve upon it. Can they make the code more pythonic? Simplify repetitive code? Or can they take two pieces of their own code, to make a "mashup," to create a new seamless product? One of favorite 6th grade activities is to have kids mash together a turtle library project with another project they have completed.

• Make it a PBL: Design open-ended assessments that solve a problem. Project-Based Learning allows students to solve a problem in a variety of ways. Even if you do not have time to complete a true PBL assessment, use some of the structure to design open-ended projects where students have agency and create various solutions. For example, use inspiration from Caines Arcade and have students create their own arcade with the Microbits.

If designed well, the learning should be messy, require students to decide, and be more connected to areal-life situations. It is only after this learning that a "true test" of learning can be made.

"Authentic Assessment." Center for Innovative Teaching and Learning, [citl.indiana.edu/teaching-resources/assessing-student-learning/authentic-assessment/index.html](citl.indiana.edu/teaching-resources/assessing-student-learning/authentic-assessment/index.html).

Wiggins, Grant. "A True Test: Toward More Authentic and Equitable Assessment." Phi Delta Kappan, vol. 92, no. 7, 2011, pp. 81–93., doi:10.1177/003172171109200721.

In the Computer Science class, designing quality learning experiences meaningful to our students is an ultimate goal. Developing ways to accurately evaluate students' learning using real-world situations that are applicable yet challenging is the underlying focus.

This blog series will take a deep dive into authentic assessment components and what entails quality assessments. Authentic Assessments in education is a complex topic full of multifaceted features.

Most research shows that development and assessment that is authentic can raise learning outcomes in students. Therefore there are many aspects for teachers to consider when developing these types of assessments.

For this blog series, I will use the Meriam dictionary's short version defining authentic assessment and Grant Wiggins's conceptual explanation for clarification on the topic.

According to Meriam dictionary, authentic assessments are _"a set of methods or techniques for assessing the academic achievement of a student that includes activities requiring the application of acquired knowledge and skills to real-world situations and that is often seen as an alternative to standardized testing." _

Additionally, _"Wiggins (1990, 1992, 1993) emphasized that tasks should mirror real-world activities and assess students' "habits of mind" (1993)." Tasks are not authentic, necessarily, just because they are similar to real-world tasks, but they must mirror the complexity, collaboration, and high-level thinking necessary for the most intellectual of professional problem-solving and decision-making. The assessments act as instruction and skill-building opportunities, not merely as tools of evaluation." _ (Defining Authentic Assessments, 2012)

To read more on Grant Wiggins's clarification of the topic of Authentic Assessments.

Every student progresses at their own pace. When setting expectations for students, you must develop adaptable, challenging situations and, most importantly, show compassion for their individualized learning paths.

The best place to start demonstrating high expectations in the classroom is to be the teacher who believes that all students can achieve. This should be a primary goal.

Send a Clear Message

A confident and passionate teacher trusts the process and attempts to instill this passion in students. The message is clear and consistent. Students know the teacher's intentions and that learning, not the grade, is the focus. Students understand that the teacher's role is that of a facilitator of their knowledge and not a giver of information. The expectation is that it is the student's job to learn. The ownership of learning is on the student, and this message is clear and consistent throughout the course..
Read more on How to Develop High Expectations in Teaching.

Establish the Mindset

Another quality is to set a growth mindset in the classroom.

In our classroom, we have this sticker. The progression from "I won't to I will" is an excellent reminder that a growth mindset is necessary to learn. It is one of the most critical foundations in developing expectations of growth in the classroom. Getting students to believe that their abilities are not static and that learning requires hard work and commitment is vital to developing their growth mindset. All students can learn, and students need to hear this and believe in the words that we choose to use in class.
Read more about Mindset

Empower Students

Teachers must also instill self-empowerment in their learners. Every child is equally capable of being successful. Practicing heutagogy and learning ways to build agency and choice into the classroom provides a concrete path for high expectations. The self-determined learner understands that there is a path for developing competencies and capabilities. Learning to code is not something that originates from cramming or memorization of vocabulary concepts.
Read more about What is Heutagogy

Give accurate and consistent feedback

Use "wise feedback" to promote growth and improvement, making sure to state your expectations explicitly. The phrase, "I am giving you this feedback because I have high expectations, and I know you can reach them." This statement is used when completing code reviews or "assessment reviews. Then direct feedback is given versus the immediate answer. How can the code be improved and what resources can the student use to improve upon the assessment. (Breaking the Cycle of Mistrust, 2014)

Hard Work pays off

The ability to learn is not linked to an innate ability. Learning is challenging, and learning that comes easy is NOT always real learning. Avoid praising only high academic achievements; switch the praise to individualized achievement. Stress proficiency in the learning process, not just completing the tasks. Teach strategies on "how to work hard in learning," not just working a lot. Provide students with the skills needed to solve coding problems and devise opportunities for students to "work hard" on challenging tasks.

"Nothing in the world is worth having or worth doing unless it means effort, pain, difficulty… I have never in my life envied a human being who led an easy life. I have envied a great many people who led difficult lives and led them well."― Theodore Roosevelt

Real-world coding tasks require a specific technique for completion. When solving coding challenges, a high level of coding knowledge and syntax is used. Programming takes commitment to improvement and time spent on iteration. When designing Authentic assessments in Computer Science, try to replicate the patterns in the real world. Setting high expectations for students is a great way to prepare them for authentic assessments. There is a difference in the quality of work when the expectations are NOT to "just get it done" versus doing what you can to learn and understand. Developing a growth mindset early on can help. Empower students and be prepared to provide them with the skills and critical feedback they need to succeed.

Grantwiggins, and Grantwiggins. “Authenticity in Assessment, (Re-)Defined and Explained.” Granted, and..., 26 Jan. 2014, grantwiggins.wordpress.com/2014/01/26/authenticity-in-assessment-re-defined-and-explained/.

“Hard Work and High Expectations: Motivating Students to Learn: KidSource Online, Inc.” Hard Work and High Expectations: Motivating Students to Learn | KidSource Online, Inc., kidsource.com/education/hard-work-and-high-expectations-motivating-students-learn#sthash.a5dkz8BG.dpbs.

Napper, Kristine. “The Necessity of Having High Expectations.” Edutopia, George Lucas Educational Foundation, 26 June 2019, www.edutopia.org/article/necessity-having-high-expectations.

“Practical Assesssment, Research, and Evaluation: Vol 17: Iss 1.” Practical Assesssment, Research, and Evaluation | Vol 17 | Iss 1, scholarworks.umass.edu/pare/vol17/iss1/.

Saphier, Jon. High Expectations Teaching: How We Persuade Students to Believe and Act on Smart Is Something You Can Get. Corwin, a SAGE Publishing Company, Learningforward, RBT, PDK Phi Delta Kappa International, 2017.

“What Is Heutagogy?” Heutagogy Community of Practice, 5 Mar. 2013, heutagogycop.wordpress.com/history-of-heutagogy/.

The "click" is a magical moment that every teacher awaits. Sometimes referred to as the "a-ha moment," it is defined as the "moment of sudden realization, inspiration, insight, recognition, or comprehension."

It is a beautiful time when light bulbs come on, and learning happens. It is a moment most teachers anticipate and one we strive to repeat. For most teachers, predicting the exact time for every student's click is difficult, and ensuring success with all students, although desirable, sometimes impossible. However, if specific instructional techniques and learning paths are applied, one can devise a plan that can have a more substantiated success rate.

Every quarter, I tell students that computer science may seem like the most demanding and challenging class ever; however, it is not far out of reach. The hardest thing that they have to do is to "Trust the process." It is a lot to ask of 6th-grade students, but I believe so much in the process and work hard to improve upon it each learning rotation. From qualitative research and reflection, I have found that the' "click" typically happens in weeks four to six of the course.

Every student is different. Learning varies for all brains. Therefore, it has been challenging to identify the exact strategies and order that guarantee learning for all my students; however, a few techniques have proven beneficial to the learning process. These techniques and learning theories are relatively reliable, and using a combination of them helps ensure that learners can learn. The caveat is the word "learners," or those that want to learn.

Here are the top three strategies I use to promote learning in my computer science class:

Spacing, Repeating and Interleaving

My College Anatomy and Physiology teacher told us every day in class, the only way to learn is by “Repetition, repetition, repetition.” This concept stuck with me, not only because he said it with a solid Latino accent, but because he was right!

Learners must repeat items enough times for the neural connections to become "used" and fused. "Neurons that fire together, wire together." (Stevens, 2019) However, it is not enough to have rote learning and regurgitation over the same item day after day. Memorizing rote topics is a useful technique and does help learners retain vital vocabulary and concepts, but real learning does not happen outside of the context. Implementing a spiraling approach in the instruction, with both rote and contextual repetition mixed in, helps promote neural connections.

Space topics out throughout the course to allow a period of interleaving of new concepts. Every lesson becomes a different representation of the same subject as new concepts are weaved into the process and taught within a new context. The repetition of this process repeatedly throughout the course allows the brain to "mix up" related topics and gives the neurons time to rest. (Read more about interleaving here: The Scientific American)

A straightforward first dialogue repeated throughout the first 3-5 weeks is this type of conversation.

“What is this piece of code?
It is an object.
“What type of object is this?”
It is a string.
How do we know it is a string?
It is surrounded by quotes.
“Let’s apply a method to this object and assign this string to the variable name...”

The dialogue is trivial; it happens in the first two classes of computer science. However, I repeat this when teaching print statements, input functions, items in a list, dictionaries, methods on objects, and every time we see a string.

When teaching computer science, concepts appear in various situations but typically with the same patterns. Things that seem trivial to you may be the one thing that may deter retention for a student.

Showing topics in various contexts allows students to connect to many concepts, repeating these patterns in the brain, allowing neurons to wire together in multiple patterns. Find ways to interleave these concepts with different activities, graphing flow charts, reading articles on other topics, playing Minecraft, or completing a Gimkit or online quiz game.

Mental Images

Throughout the course, look for ways to help students make mental images with new vocabulary and knowledge. Dual coding theory, hypothesized in 1971, states that images and texts could help support the memory of new complex items. Although some doubt lies within this theory, many learning specialists confirm that using mental images to help learners understand topics is critical to advancing understanding.

Some studies show that a person that can “see” an image in their mind, learns two and half times faster than those that do not. Helping students visualize the complexities of what happens “behind the scenes” of everyday objects helps them make connections to code. (Read more about mental images in learning here: Using Mental Imagery)

When coding, the use of only words and conversation tends to be the norm. Find ways to “draw” the concepts out on the whiteboard. Making graphs, sketches, or using physical components while teaching helps students “see” the code clearer in their minds.

One simple example is the explanation of inputs and outputs. Students are instructed to think about an electronic object in their home that requires them to “do” something in return for something happening. Students tend to visualize a remote or perhaps their Alexa or even their computer login. Have students sketch out the flow chart for this activity, assigning an input, decision branch, and output. The flowchart can have structure and correct form or allow students to draw the chart so that it makes sense to them. This simple activity leads us into many opportunities to discuss input functions, buttons, sensors, and conditional statements.

Desireable Difficulties

It is natural to learn from opportunities that challenge us. Desired Difficulties in learning are opportunities designed to be more difficult than average and should take longer than usual to solve. These activities require thought and often challenge the brain to access both long and short-term memory.

The hardest part of using desirable difficulties in class is trusting the process. Most teachers and students want the learning to be more comfortable and take a shorter amount of time. However, when learning is hard, more errors and mistakes happen. Students can become frustrated that they are confused, or feelings of lack of abilities can happen. However, Dr. Robert Bjork and Dr. Elizabeth Bjork propose that learning occurs when there is a struggle to solve and slow down the learning process. What may appear as students not learning promptly or being successful is the opposite.

Learning that

a) requires time to process,
b) accesses different parts of the brain, and
c) promotes thinking differently about a solution,
creates different learning pathways and long-term retention of knowledge for all learners.

(Read more about desirable difficulties here: Desirable Difficulties in the Classroom)

Every week I try to provide opportunities for students to process and challenge their minds. There are many opportunities for this to happen in a computer science class. One way is to incorporate what I use to dub “5-minute challenges”. These weekly challenges are short coding problems designed to reinforce learning but are new and slightly different from what students have already seen.

Initially, I limited the amount of time on “5-minute challenges” as not to “waste” opportunities for class instruction; however, now, students are given more time to process and work through the solution. Moreover, learning opportunities are not wasted, even though more class time is used. The challenges are often complicated, but most students can solve them when given time to process and seek the solution.

"If I, as a teacher could get a student to generate an answer rather than my giving it to them, they'll remember it much better later on, but they have to be able to generate it by virtue of what they know already and the cues the instructor would give them. They have to succeed at the generation." - Dr. Robert Bjork

The best part of these challenges is that solutions can vary, thus providing opportunities for class discussions afterward and the thought process on how the problems were solved is shared.

Many learning theories have proven to help learn how to learn. Using a combination of them throughout a course can help to improve click moments for all students. To find out more, look into cognitive science strategies in learning.

Have fun reading and trust the process.

Resources

“‘Desirable Difficulties’ Can Lead to Deeper Learning and Better Retention.” "Desirable Difficulties" Can Lead to Deeper Learning and Better Retention | Tomorrow's Professor Postings, tomprof.stanford.edu/posting/1419.

Conyers, Donna Wilson and Marcus. “Brain Movies: When Readers Can Picture It, They Understand It.” Edutopia, George Lucas Educational Foundation, 13 May 2014, www.edutopia.org/blog/brain-movies-visualize-reading-comprehension-donna-wilson.

“Neurons.” How Do I Learn, www.washington.edu/howdoilearn/neurons/.

Pan, Steven C. “The Interleaving Effect: Mixing It Up Boosts Learning.” Scientific American, Scientific American, 4 Aug. 2015, www.scientificamerican.com/article/the-interleaving-effect-mixing-it-up-boosts-learning/#:~:text=Instead, your brain must continuously, that interleaving strengthens memory associations.

Stevens, Alison Pearce. “Learning Rewires the Brain.” Science News for Students, 3 Dec. 2019, www.sciencenewsforstudents.org/article/learning-rewires-brain.

Sumeracki, Megan. “Learn How To Study Using... Dual Coding.” The Learning Scientists, The Learning Scientists, 1 Sept. 2016, www.learningscientists.org/blog/2016/9/1-1.

“UCLA.” Bjork Learning and Forgetting Lab, bjorklab.psych.ucla.edu/research/.

“Using Mental Imagery Processes for Teaching and Research in Mathematics and Computer Science.” International Journal of Mathematical Education in Science and Technology, Vol. 00, No. 00, 15 July 2009, 1–13

When the semester or year ends, consider what could have been better about that marking period? How can the curriculum be improved for the next group of students? Reflecting on past courses and discussing change opportunities are essential for promoting students' quality experiences and good practice.

Reflection regarding curriculum design and learning outcomes should always be at the heart of curriculum planning. Becoming part of the "quality culture" where improvement is the only option, feedback is critical, and alignment to standards and goals are a significant focus is a full-time endeavor.

Whether you are just starting or teaching Computer Science for years, your first step when completing a curriculum reflection is to identify, list, and answer a few essential questions. These questions are guides for developing ideas and areas of concern to plan and modify the curriculum. It is good practice to keep the learning expectations at the forefront and remember what knowledge is the most important to retain?

I like to list as many questions on paper, regardless if they need immediate answers or not. This should become a checklist for curricular review and a great reminder of why and how to teach.

1. What is the final goal?

Keep your end goal in mind always, regardless if it is only a unit redesign or multiple courses combined. What is the one thing that students will remember 10 or 20 years from this date? What is the Big Idea? Why is this meaningful to the students?

"If an idea is “big” it helps us make sense of things. So, an idea is not “big” merely because it categorizes a lot of content. “Change,” “relationships,” and “number system” certainly encompass an enormous amount of knowledge and understanding, but these concepts don’t contain much insight or direction beyond their definition. They aren’t particularly powerful or illuminating on their own as concepts. On the other hand, “For every action there is an equal reaction” is a powerful idea about change: we can use it to study, organize, make sense of phenomena, and predict changes in motion. " - Grant Wiggins

2. What concepts are critical to know? How can new and current topics be incorporated into the curriculum? "How can we keep the content current and find effective teaching materials that create a student-centered learning environment? "

Understand that not all the content can be taught in one course. What content is critical to know yet also allows students the opportunity to expand should they desire? What are the building blocks you will need to make a solid foundation of learning?

3. How are students acquiring knowledge of the content?

Make sure the delivery of content is active. Do not become the sage on the stage when the content is complicated or "hard to learn." Passive learning is not the same as active learning. Active learning gives the teacher foresight into students' understanding; constant and constructive feedback is a large component of active learning. Find ways during active learning to assess each student and do not rely on the same type of assessment every time.

"But how do we get from transmission of information to construction of meaning? Such a change can entail a consider able shift in roles for the professor, who must move away from being the one who has all the answers and does most of the talking toward being a facilitator who orchestrates the context, provides resources, and poses questions to stimulate students to think up their own answers. " - Allison King

4. What tools or resources will students need to enhance their learning?

Tools help support the curriculum. What will students need to use in order to learn optimally? Will videos be made? Which editors will allow ease of learning?

5. What happens if a student already knows the content? How will we choose to respond when students do not understand or do not learn as expected?

How you choose to differentiate topics with students can set the pace for the entire year. Always have a plan for students that are beyond the scope of the content currently being taught. How can you extend the topic and still give the student opportunities to engage with the course's social aspect? Plan for students that struggle; set aside time to provide help. Look for alternative ways to explain complex topics and in different modalities.

6. What skills outside of the content should be part of the curriculum? What skills are the best for each specific age group?

Keep in mind the skills that you are trying to develop. How are you explicitly teaching and assessing those skills? Avoid assessing the skills that have not been taught or assuming that skills acquisition was at the same rate for every student.

7. What projects will be meaningful to learn? What type and variety of assessments will be used? What are we doing to ensure that our students are always learning?

Students learn best when assessments and learning require cognitive and social opportunities. Look for areas where the teacher is the giver of knowledge and find ways to change those lessons. Students require cognitive and social activities to learn optimally. The direct transfer of knowledge from the teacher to the student does not happen passively. Student learning is about knowledge creation, the transformation of experience into skills, and the application of qualifications to solve a problem that, in practice, is recognized as being competent.

8. What authentic assessments will keep students engaged and connected? What is the best language for the student? Is it inclusive?

Design coding activities within a context that students will understand. Try to embed them into situations that apply to student's lives. Each group of students is different. Be ready to be flexible and look for ways to connect the content to the student group's context and the individual student. The learning changes over time and space very quickly.

9. What activities allow knowledge creation and application of current knowledge at the same time?

Learning is a mixture of activities. What knowledge do the students already have in their "toolbox," and how can the lessons help students develop and merge existing knowledge and new knowledge successfully?

10. How can feedback be used to improve student's learning?

Providing quality and timely feedback improves learning. Feedback also allows students to learn from their mistakes? Students not only need feedback, but they must learn how to use it as well to improve. Find opportunities to give a variety of feedback time in your lessons and for grading. Design lessons that allow time for peer editing and improvement. Seek out assessments where feedback is critical to the assignment.

Lastly, develop a personal learning community. Find people within your community to discuss content and learning activities. Encourage peer and mentor observations. Seek out people to help you reflect and evaluate your teaching strategies and content. Embrace change and redevelopment of your curriculum.

Resources

^{Chapter 6. Feedback: The Long View—Does Feedback Improve Learning http://www.ascd.org/publications/books/116066/chapters/Feedback@-The-Long-View%E2%80%94Does-Feedback-Improve-Learning%C2%A2.aspx#:~:text=Increase%20students'%20interest%20in%20feedback,with%20obvious%20value%20and%20interest.}

^{From Sage on Stage to Guide on the Side https://faculty.washington.edu/kate1/ewExternalFiles/SageOnTheStage.pdf}

^{Improving Students’ Learning Outcomes - Curriculum and .... http://www.oecd.org/education/imhe/43977531.pdf}

^{Online Teaching Resources: Where in the WWW are They .... https://journals.physiology.org/doi/full/10.1152/physiol.00003.2007}

^{What is a Big Idea? https://www.authenticeducation.org/ae_bigideas/article.lasso?artid=99}

After instruction and 'code alongs,' I always assign supporting articles and texts from online sources to enhance student knowledge. The texts are often online and consist of short tutorial articles, code explanations, or hardware projects. The intended reading assignments are assigned to help strengthen coding knowledge and build more skills. However, these activities were never without a "fight" and often did not produce the expected outcomes.

As I replicated lessons each quarter, I began noticing a pattern with students. Moreover, scorn began to develop for the ever so familiar and anticipated, "I am so confused!" statement after reading an excerpt or webpage tutorial.

Instead of supporting the learning and enhancing the lessons, the text assignments appeared to be hurting the learning and hindering progress. I began to think that students could not read! And was desperate to change strategies.

"Could not read" may be a slight exaggeration. Students were capable readers of fiction and had many opportunities to develop comprehension with DRA tests in the lower school. Also, students could read the assigned text and, for the most part, state what they read. However, after further investigation, I determined that students were reading but not comprehending or processing the assigned informational text. Their information literacy skills were not well developed for informational text and reading tutorials online.

"Literacy is the ability to read, write, speak and listen, and use numeracy and technology, at a level that enables people to express and understand ideas and opinions, to make decisions and solve problems, to achieve their goals, and to participate fully in their community and in wider society. Achieving literacy is a lifelong learning process." -Defining Literacy Literacy Advance

Many computer science tutorials, regardless if they are online or in books, are heavy in text and new vocabulary. Even Python kids' books are heavy in new vocabulary, making the informational text challenging for many students to use.

"To become proficient in critical thinking – at least in a literate society – students need to be able to handle text. The text may be long, complex or both. To make sense of it, students cannot skim, rush ahead or continually get distracted." -Naomi Baron

Information literacy skills, are the skills needed to identify, find, evaluate, and use information effectively. A deficiency in these skills makes it difficult for students to comprehend text if the student cannot understand a minimum of 80% of the words. (Check out this interesting website to understand what 80% comprehension feels like.)

Students often developed their coding knowledge during code alongs and by watching screencasts and video tutorials. However, their competence of both the subject's knowledge when they read about it and the skills to develop more knowledge from reading, was low. I decided to make a focused intent to improve their literacy skills.

Activites to Promote Information Literacy

Over the years, I modified the lessons. I started implementing activities and strategies to help students engage with informational text and build their literacy skills. Here are a few activities that can help increase students' skills when reading.

• Have the students read, read, and read some more. By increasing access to informational text, students will become more comfortable and competent in deciphering unknown or new vocabulary as they read.

• Take snippets or shorter paragraphs and photos from web pages and copy them into documents. Reduce the number of hyperlinks and instead list webpages in a resource section at the end of the document. This technique reduces distraction from the clickbait and focuses their attention on the text alone. Also, it allows you to use photos to support the new vocabulary. and organize the text that is not critical to the learning.

• Have students practice with potential vocabulary words out of context. Have students explain the definitions to partners and give them opportunities to become familiar with vocabulary. Eric Matthes created Python Flash Cards, this type of rote learning helps familiarize students with new python terms, such that when they see the word in an informational text, their brain will identify it as a word they may know.

• Give students more time with informational text. If the text's length takes approximately 5 minutes to read, double the time and make sure students read the text more than once.

• Teach comprehension strategies explicitly while modeling how to read informational text. Show students techniques such as "skim, scan and deep reading" and identify new words in a sentence. Show students how to translate one sentence at a time and provide them with procedures for processing new vocabulary while reading.

• Always assign informational text for authentic purposes. Ensure that the text they read is both practice for developing competence and text that develops knowledge for an activity that they need to complete.

• Using a "Find, Read, Do Explain" technique allows students to engage with informational text, complete an activity, and lastly, explain the activity in their words. This technique helps students comprehend and commit new vocabulary to short-term memory.

These are just a few activities that can be used in the classroom to improve literacy skills with coders. Using techniques daily in class will help students develop their programming skills, provide students with lessons on developing their lifelong learning skills, and develop competency and knowledge in other subject areas.

"The more that you read, the more things you will know. The more that you learn, the more places you'll go.” ― Dr. Seuss, I Can Read With My Eyes Shut!

Critical thinking is a skill that is essential in schools. Combining other skills such as analyzing, evaluating valid and reliable information, and synthesizing it to obtain an educated answer makes critical thinking so fundamental for students to grasp early on in their education.

It is critical for successful learning and is a skill used for life. Developing these skills helps to create lifelong learners who are curious, independent, and have broad interests.

A good learner knows that only memorizing and regurgitating knowledge may help one develop book smarts; however, a person who can formulate a new answer after gathering multiple sources of information is critically smart. Learners who bury themselves in quality research, weed out opinions, cipher through documentation, and develop an answer grounded in truth is a person guided to find the most accurate solution to a problem.

What is Critical Thinking?

Critical thinking is best described as a habit of mind, a way of thinking. It is a process that requires the use of logic to solve a problem. It is the thinking of intellect and derives from a continuous need to improve upon the answer.

Defining the skills embedded within critical thinking is difficult without first identifying what it means to be a critical thinker.

A critical thinker knows how to ask the right questions. They apply the Right Question Technique or QFT by default, without knowing about QFT. This type of thinker knows that vital questions must be raised, addressed, and formulated clearly and precisely. As we know, “A problem well-stated is half-solved.”

Effective critical thinkers know that all aspects of a problem need to be explored and there are always hidden facts that may need to be hashed out. Being able to clearly identify the problem helps critical thinkers solve complex problems.

A critical thinker knows how to break large problems into smaller bite-size pieces. This type of thinker knows that complex problems happen in every facet of our lives. Therefore, this type of thinker has developed patience and grit that helps in becoming an effective problem-solver.

How can you Develop Critical Thinking through Coding?

As a learner, before you can explore the skills of critical thinking, the opportunity needs to exist. A learner needs to have the content and the desire to apply the skills.

"Critical thinking relies on content, because you can't navigate masses of information if you have nothing to navigate to." -- Kathy Hirsh-Pasek

Learning to code or program is an area where learning how to think critically is inevitable. Studies conducted at Carnegie Mellon show that programming is beneficial to cognitive development and that starting to code early is an excellent basis for children when learning how to learn.

Here are a few reasons why learning to code is beneficial to your brain.

• A person who codes is a person who develops their critical thinking skills daily. For programmers, encountering a complex issue occurs every second and although every coding problem may be different, there is a system to solving problems.

• One of the reasons coding develops critical thinking is that coding can be messy. When you code, you need to try many different solutions for your programming problem. Good coders can analyze which program works the best. You are guaranteed to make mistakes. Learning is not linear and coding is not a linear task either.

• Coding teaches you to use critical thinking skills to debug coding errors. And failure IS an option in programming. With every coding error, you have the opportunity to fix the issue and build upon more skills.

• A person who codes has to simplify complex problems. Every problem is made up of many smaller problems. Solving these small problems provides a workout for the brain. Programmers get continuous experience with critical thinking and breaking down problems, so much that professional programmers often can solve complex coding problems even when they are away from their computer.

• A person who codes knows that asking the right questions can help to solve problems easier. Coding helps to build inquiry skills.

• A coder develops the critical thinking skills that allow him/her to build a repertoire of information that can be transferred and reapplied in different concepts. Connections are made and problems become easier to decipher.

In this keynote presentation for Creacode's Home Alone Conference, Sean and Kelly summarize the importance of defining and developing critical thinking skills.

Critical thinking is not “just thinking,” but it is a process of actively evaluating and applying the information to improve upon a process. Students develop many critical thinking skills when they learn to code. This quote is a favorite of mine and sums up the need to think to learn to think critically.

"Critical thinking is thinking about your thinking while you’re thinking in order to make your thinking better." -- Richard W. Paul

_{1 Charles Kettering, the famed inventor and head of research for GM quoted, "“A problem well-stated is half-solved.”}

Guest Podcast Appearances

• Teaching Python in the Middle School with Test and Code
• Beginners and Experts Panel with Talk Python to Me
• Learning and Teaching Python with #vBrownBag
• Teaching Python and Finding Resources for Students with Real Python
• Episode #143 Spike the Robot, Powered by Python with PythonBytes
• Pybites: How Codechalleng.es is being used
• Teaching Python Podcast on the Podcast PythonBites_
• 10 Minute Podcast with Vicki Davis

Keynotes and Presentations

• FCIS 2019 Administrators Conference: Preparing for the School of 2024: AI, Machine Learning, VR and AR
• What we learned from teaching kids to code: Live Curious, Go Beyond Conference; Monterrey, Mexico(https://youtu.be/Q96boF8Whj4)
• ISL Learning Loft: "No, really. Why coding?"
• Keynote: Innovation Institute: From Good to Great: Pushing the Boundaries

• Interview with Real Python
• PyDev of the Week: Kelly Schuster-Paredes
• Py Dev of the Week: Sean Tibor
• Adafruit Hand Sanitizer

In the world of education, Bloom's Taxonomy is a household name, a foundational tool that helps teachers shape their lessons and assessments. But have you ever wondered how it truly applies to the dynamic journey of learning and teaching Python?

If you are an educator and haven’t encountered Bloom’s taxonomy at least once, it is a rare occurrence. While studying for an Educational Undergraduate Degree, most teachers complete assignments on Bloom’s taxonomy. The projects and activities help undergrads quickly recognize, identify, and develop lessons from one of many pyramid-shaped charts’ with colorful levels. I remember writing multiple essays and ensuring that my educational pedagogy showed that Bloom’s was at the heart of my lessons.

For those of you not in education, Bloom's taxonomy was a framework developed by Benjamin Bloom and his collaborators. It is simplistic in design and identifies six major categories: knowledge, comprehension, application, analysis, synthesis, and evaluation. These categories have been modified over time, but the principle remains the same. Bloom’s taxonomy is one of the most widely used systems that presents learning in a clearly defined set of learning processes. It ‘helps guide’ teachers in developing higher-order thinking skills in the curriculum and the classroom.

Bloom’s taxonomy was designed as such so that teachers could identify these objectives on the continuum and move lessons and assessments from a straightforward process to a very complex concrete or abstract one.

When I first learned about Bloom’s taxonomy, Bloom layered the categories in a pyramid shape with the categories listed above one another, designating a hierarchy in learning throughout the pyramid. Its design implied that a student must first have a strong foundation of knowledge to comprehend a topic and comprehend before synthesizing. While this is true in some situations, many institutions have realized that application and creating can be a part of the learning or the knowledge gathering phase. These learning steps are not as separated or hierarchical as once drawn.

Over the years, Bloom's taxonomy has been revised, edited, turned into objectives, and redesigned to show suggestions from multi-layered activities, apps to use to meet Bloom’s taxonomy objectives, and some revisions show the goals as “grouped objectives.” Regardless of the modification, Bloom’s taxonomy is a useful tool to help a teacher and learner identify a learning trajectory.

Making Connections

During a recent course on the “Science of Learning,” I encountered a cognitive science misconception known as the “GI Joe fallacy.” At the end of every cartoon episode of GI Joe, a child would always end the episode with “Now I know!” and GI Joe would say, “And knowing is half the battle!” This statement, by GI Joe, is the heart of the fallacy phenomenon. Cognitive scientists explain that although knowledge of topics is desired or recommended during the learning process, there is always a varying degree of rational thought, comprehension, and emotional knowledge that can affect decision making. Scientists propose that regardless of whether we know something, we can sometimes skew decision-making and analytical thought.

Upon further study by psychologists, sometimes what we think we know isn't always perceived or seen as accurate, and that “knowing is half the battle” does not necessarily mean that you understand or that you know the truth.

That got me thinking, how do Bloom’s taxonomy and the GI Joe Fallacy apply to my learning Python or how I teach Python. It boils down to “Knowing isn’t half the battle, nor is gathering knowledge an indicator that we understand.”

Newer Versions of Bloom's

Thinking about and using Bloom’s taxonomy in Computer science and coding is a helpful tool for both the teacher and the learner. I found this rearranged version of Bloom’s taxonomy that shows the top three levels as equally important.

I have been teaching Python for 2.5 years. I feel reasonably confident that I know the Basics of Python. I can evaluate student code for errors and efficiency. For example, I can teach functions, explain the concepts to my students, teach them how to code simple functions, put functions into more complex code, and explain to kids how to put functions into their code. I can even follow along with complex code. But one time, after coding and teaching functions for two years, I happened upon a simple but necessary explanation of functions, and something happened, a lightbulb came on, and an “OMG! Ah-ha!” followed!

This moment happened to me the other day! I was watching my colleague teach functions, the same thing I have taught before. It was a simple lower-level thinking lesson on Bloom's taxonomy scale, but it caused me to have this surprise “a-ha” moment. It was then when I realized a critical analysis of my learning path. I had cycled back into a knowledge/comprehension phase and made a significant connection to the current topic. What I knew before wasn’t half the battle of my real understanding of functions. I had missed something supercritical to understanding how to use functions.

I felt a “spark,” and I realized that I reached a point where a reliable neural connection had finally happened. I have been teaching the concept of functions for a few years, but what was it, and how did this linking of neurons finally solidify? How could a simple knowledge exercise spark my brain into a “synthesis “reaction? Was I suddenly able to understand and visualize a more involved piece of code and solve it?

Last summer, I took a course called “Learning How to Learn” with Barbara Oakley, and during this course, Barbara discusses these moments called “meta moments”. I have witnessed them with students many times and have become accustomed to designing situations for students. However, I do not recall remembering a moment like this happening to me in adulthood. I felt the neuron connecting two pieces and the knowledge solidifying. I identified that ‘click’ or ‘ah-ha’ moment and have been trying to explain the incident to other adult learners, so that we can replicate it.

Bloom's taxonomy started as a pyramid and has had so many mutations over the centuries. Teachers have listed out verbs, apps, and diagrams side-by-side in a circle; however, many educational theorists believe that the concept is durable and timeless regardless of the modification.

However, I agree with the University of Michigan, that Bloom's taxonomy is like the design cycle where ideation, research, prototyping, creation, and evaluation, cycle back and forth. This version of Bloom’s taxonomy shows the thought process that is needed when teaching and learning Computer Science.

Knowledge is gained at different entry levels depending on the concept, the skill, the topic, or the learner. And the depth of the knowledge does not need to be vast, nor does it need to be all-inclusive before creating, evaluating, and analyzing. However, it does need to cycle through in a quick Scrum or Agile learning approach.

Using this version, let’s investigate my “ah-ha” moment. I can recall facts and basic concepts. I can define, call functions, and add parameters and arguments to create useful functions in code. I can evaluate student code and analyze other codes to identify errors. I remember, understand, apply, create, evaluate, and analyze. I have completed my level of higher-order thinking skills. However, I gained more knowledge during this process and cycled back to the remembering and understanding stage. By completing these “higher-order thinking skills,” I was better able to understand functions deeper. But it is only after these stages where I can go back to understanding and remembering the concept better. I have evaluated and analyzed so that I can finally understand.

It is by following this pattern that my skills are growing. And it is this pattern that simulates in my teaching. When we teach a new subject, it is not essential to divulge every concept or insist on every idea is understood. It is only necessary to ensure that the learner is consistently cycling with information that he/she manipulates, transforms, and ingrains it on neural connections.

When a learner can now make explicit pictures in their mind, or design a metaphor, they develop an understanding that cannot be replicated by merely reading or copying code. For example, I like to think of functions like getting a phone number from someone. A phone number is a way to repeatedly getting in touch with someone; however, if you do not use the phone number or “call” the number, you cannot talk to that person. Functions are transactional.

Indeed, one can put together a more involved piece of code by copying it from a book. We can learn everything about the code and state what each line does, and build up a repository of information. But computer programming is more analytical than memorizing. SO start small, learn bites, not chunks, and truly understand it from a simple knowledge base.

Grow upward through the pyramid and get to know a topic. Do not be afraid to learn in small chunks. Do not challenge yourself to know everything at once but challenge yourself to play and apply those higher-level thinking skills to smaller bites of information. As we adapt Bloom's Taxonomy to the dynamic landscape of coding, we discover that the journey of learning and teaching Python is an ever-evolving adventure, where 'aha' moments are waiting to spark our understanding.

"The eye sees only what the mind is prepared to comprehend."

- HENRI BERGSON, French Philosopher and Educator

While promoting a more in-depth understanding, a teacher will encourage students to use many skills. Students reflect on what helps build content knowledge, and teachers direct students to employ methods independently and build on what they already know.

Using the same skills that an adept teacher applies in the classroom, such as metacognition, can help one become a better learner. Metacognition helps guide you to change basic facts and vocabulary understanding into a deeper conceptual understanding of any topic.

In Part one of this three part series, we identified the need to list what concepts we may already know or what connections you can make to a new study topic. This
video by Django Girls does a great job of showing how to connect everyday understandings to new learning topics. Moreover, it helps solidify the importance of being able to explain complex topics with everyday concepts. Explaining the Command line with metaphors that connect to topics we already understand is a product of truly understanding a topic.

How can more metacognitive strategies improve the transfer of declarative knowledge into conceptual knowledge and make things stick!

Part Two: Getting “meta” with your learning: What do you want to Learn?

During the learning process, it is critical to identify the information you wish to learn. In a classroom/mentor situation, the teacher helps the student identify the gaps in what is known and what needs to be learned. A student who is aware of what they know or doesn’t know can better break down their learning process independently.

Like a student who is aware of their learning gaps, an independent learner, using the skimmed information in the “What I want to know” stage,
K-W-L chart, can apply critical learning strategies to identify the next moves.

Let us explore how:

I was in a unique situation where I was learning a topic simultaneously as I was teaching it. I was a “learner, doer, and teacher.” In learning how to teach python, I had to learn how to code it.

I was in a unique situation where I was learning a topic simultaneously as I was teaching it. I was a “learner, doer, and teacher.” In learning how to teach python, I had to learn how to code it.

I identified a learning path quickly, not only because of the tools I had as a teacher but also because of a specific need. I had to teach it.

However, that did not mean I was initially very successful.

My learning and teaching adapted as I learned more complex topics in Python. At the beginning of the learning process, most of the learning was declarative. “This is an integer, string, and float. These are functions. Here is an IDE.” Declarative

Being able to identify, define, and explain important concepts is crucial. Although declaring gained knowledge is a good start, making connections and explaining the concepts is a little trickier. Even more importantly, What about writing code? Furthermore, this is typically the asserted learning goal. “I want to learn how to code.”

Let us look at why this statement is too broad to be metacognitive.

What is it that you want to learn?

Identifying the ‘what I want to learn’ portion can sometimes be difficult when you are on your own. Most books on the market contain the same basics of coding Python. Learn the basics here. Learn to code in 30 days. The vocabulary is the same, the concepts roughly in the same order. The basics of python become the basics of turtle, and voila! You are a coder. Well, not really.

Getting Meta about learning can help, but it takes time, practice, effort, and awareness of the need. Without a teacher or mentor around to guide you, you are the person responsible for asking the questions to yourself? Learning is a process. It is not a static or closed-ended goal. Metacognition reminds us to be fluid, and that we must be in a constant state of progression in our learning.

It is time for another list. In this critical stage of learning, you not only identifying the path of learning, but you also set a goal. The goal must always adapt and progress. As an independent learner, it is up to you to keep tabs on the learning path and identify the gaps between what you thought you knew and what you need to learn. You need to advance at a rate that keeps you at a comfortable level of struggle. You are responsible for monitoring your comprehension, and you must remember to self-evaluate regularly.

“Learning is a process. It is not a static or closed ended goal. Metacognition reminds us to be fluid, and that we must be in a constant state of progression in our learning."

Do not waste your time writing out concepts and vocab words in this stage. Make learning goals. For example, as I started, my first goal was small, code Rock, Paper, Scissors without a tutorial, and explaining every line in the program. I needed to know this program forwards and backwards because I needed to debug my students’ errors without research or time wasted in class. At the time, I had only been learning Python for three months. Coding Rock, Paper, Scissors was an enormous feat.

When you are learning in a silo, learning to debug on a grand scale does not happen. I needed to invent ways to be prepared for my students. Practicing writing the code without a book or trying to solve code challenges can be an alternative. Look at issues on Stack Overflow and see if you can help replicate some fundamental questions asked. Alternatively, look at the Stack Overflow questions and code the solutions. Choose or identify the concepts suggested that make the most sense to you.

As I worked towards achieving my goal, I watched tutorials on how to code other activities; however I did not watch videos on RPS. I learned how to “Flip a Coin”, coded Michael Kennedy’s Birthday App, and practiced writing basic concepts such as for loops and conditionals over and over.

“One learns from books and example only that certain things can be done. Actual learning requires that you do those things.”

– Frank Herbert

Frank Herbert took six years to research and write his novel Dune. An equally long process is learning to code. Coding requires one to put in the effort, do the code and research the concepts.

Taking notes or writing things down is another way to “do” things during learning. Use inline comments, multiline comments, or a Colab document as places to write notes about code. I define every major code snippet to ensure that I can recall the concepts I have learned. You do not need to use these “notes” to study from; in fact, you will outgrow them quickly. However, writing down things helps your brain to make more connections to previous concepts and code.

To keep tabs on your learning, learn to ask yourself questions, draw flowcharts or write code snippets by hand, find a person to practice reciprocal teaching to, or if it is just you, write blog posts explaining your code. Learning requires cognitive and social activities that can help your brain move from procedural knowledge into conceptual knowledge. Find ways to discuss, do, and interact.

As you start to understand Python’s core concepts and syntax, your learning shifts more into procedural knowledge. This is when vocabulary, definitions, facts and the interrelationships between them, start to connect and conceptual knowledge starts to develop. Your “What do I want to learn?” goal should begin to shift and you should consider shifting into the next phase of the metacognitive process prior to cycling through the process again. This is the point where you should pause to reflect on the learning journey. Reflection!

A teacher knows that learning is a path full of collecting knowledge, transforming it with skills, and learning to apply both to solve a problem. As an independent learner, you need to be your guru of reflection. In Part 3 of the Metacognitive process, we will look at identifying what you learned. However, before we do, list out what you want to learn and then go conquer your learning!

‘By three methods we may learn wisdom: First, by reflection, which is noblest; Second, by imitation, which is easiest; and third by experience, which is the bitterest.’

–Confucius

1. Hacking the Dispenser
2. Configuring Home Assistant for Automation
3. How do we know it's working?

Note: this turned into a very long and detailed explanation of my project, so I've broken it up into three parts. This part focuses on the actual hacking of the hand sanitizer dispenser. Part 2 will show how to use Home Assistant to automate actions in the classroom. Finally in Part 3, we'll try to understand if it's actually working to change student behavior.

Carrots vs. Sticks

Last year before COVID-19, my classroom's hand sanitizer dispenser sat with dead batteries for months. I'm not even sure if it would have worked if we had new batteries. For obvious reasons, this year my classroom came equipped with a shiny new hand sanitizer dispenser, with the goal of getting every student to sanitize or wash their hands at least once every two hours.

Over the first few weeks of school, I noticed that very few students sanitized their hands unless I told them to. As the CDC has noted, frequent hand washing and hand sanitizing is one of the best ways to prevent the spread of COVID-19.

My marketing/technology brain spun to life as I pondered this problem. How can I get my students to want to sanitize their hands? If I have to remind them, then it all depends on my reminders. This has a lot of drawbacks, like I often forget to remind them with everything else I'm doing, they might try to avoid it, and we have no data-driven way of knowing if my reminders are effective.

Just like that shaving soliloquy in The Hunt for Red October, I asked myself "How do you get middle school students to WANT to sanitize their hands?"

The answer I came up with was twofold: first, make it fun. Then, make it easy for students to see themselves in the data.

Home Assistant to the Rescue!

My idea was to make it so that when the dispenser activates, some lights in the room would flash colors, Alexa would say something funny, and students would be able to see how many times the sanitizer was used that day.

The trick was figuring out a way to automate all of this in an easy way. While I could roll my own solution using pure Python, there was a platform already designed for this. I had even already trained myself on how to use it.

My quarantine project during COVID was to automate more of my home using the Python-based Home Assistant project (formerly known as HASS) and I realized it would work very well to bring all of these parts together in a relatively easy way for the classroom.

I dug through the storage bins in my room and found a Raspberry Pi 4, some Yeelights and even an ESP8266 NodeMCU board that I could wire up to the dispenser. To make it easy to swap out boards, I added a 3-pin JST PH connector to the system to make it easy to plug in the NodeMCU.

Parts List

• Luminoso Clean Hand Sanitizer Dispenser
• ESP8266 NodeMCU
• JST-PH 2- & 3-wire connectors
• Amazon Echo
• Raspberry Pi 4
• Yeelight
• Unused Lamp from my daughter's room

Wiring up the Dispenser

The dispenser was the most hands-on hack and the biggest question mark for me. How would I know if the dispenser was activated? It turns out that the dispenser works with an IR sensor that detects when a hand is under it, just like a touchless water faucet.

When the dispenser activates, it runs a motorized mechanism that dispensed a certain amount of alcohol-based hand sanitizer gel. Importantly for our project, it also briefly turns on a UV LED that shines on the person's hands. Using a multimeter, I was able to trace the leg of the dispenser's microcontroller chip that turns on the LED. Then, I made up a three-wire JST-PH wiring harness that connected to that leg and the dispenser's power supply.

I had to solder a wire directly on the leg of the microcontroller to get the LED signal. Be very careful with this connection and take your time. I tinned the wire with a bit of solder to make sure I didn't add too much.

For the power connection, the dispenser uses a standard 2-wire JST connector. I made a Y-connector out of a male and female 2-wire connector that also connects to the positive and negative wires on a 3 wire connector. This allows me to plug the battery connector into the female and the male end into the dispenser board without changing any other connections. The three wire end is routed through a hole drilled in the side of the electronics enclosure, then plugged into a three wire connector soldered directly into the NodeMCU.

The ESP8266 communicates over WiFi, which tends to be power hungry. For now, I've plugged the dispenser into mains power so I don't have to worry about draining the battery prematurely.

Setting up Home Assistant

Now that I had my dispenser hacked together, I needed to set up the Home Assistant server on the Raspberry Pi. For this, I mostly followed the standard setup instructions. In addition to the standard setup, I added the ESPHome addon to make it easy to setup and control the NodeMCU.

Pros for using Home Assistant in the Classroom

• Cheap (Runs on a Raspberry Pi)
• Open Source (and frequently updated!)
• Wide array of relevant integrations:
  • ESP8266/ESPHome for hacking the dispenser
  • Yeelight lightbulb for signaling the dispense
  • Amazon Echo for making announcements

Setting up ESPHome

ESPHome makes it easy to connect microcontrollers to a Home Assistant server. It's really full-featured, even including the ability to send firmware updates over WiFi to your boards. I configured the ESP8266 to act as a binary sensor, meaning that when the light was on, it would send an ON message to the HA server.

esphome:
  name: tibor_sanitizer
  platform: ESP8266
  board: nodemcuv2

wifi:
  ssid: !secret wifi_ssid
  password: !secret wifi_password

  # Enable fallback hotspot (captive portal) in case wifi connection fails
  ap:
    ssid: "Tibor-Sanitizer Fallback Hotspot"
    password: "MeUPw7DTWxFi"

captive_portal:

# Enable logging
logger:

# Enable Home Assistant API
api:
  password: !secret api_password

binary_sensor:
  - platform: gpio
    pin:
      number: D2
      mode: INPUT_PULLUP
    name: "Sanitizer Dispense"
    device_class: moving
ota:
  safe_mode: true
  password: !secret ota_password

The key entry here in the config file is the binary_sensor gpio entry that tells the ESP8266 to monitor the D2 pin for the sanitizer's UV LED signal. When that light turns on, it will send a message to the Home Assistant server that the sanitizer is ON.

Testing Communications

Now that we have Home Assistant and ESPHome setup, we can test to make sure that the sanitizer is still working and that it's communicating with Home Assistant.

First, you'll have to add the dispenser as a new integration. If you don't already see the dispenser pop up as a new sensor on the network, you can go to Configuration->Integrations and press the Plus button in the lower right side of the screen to add the sensor.

Follow the prompts and name the device in the dialog box. When you're finished, you should have a new Home Assistant entity for the dispenser that you can monitor for state changes.

When the sanitizer activates, you should see the state of the entity change from off to on, then back to off when the LED shuts off.

Summary

Whew - that was a lot of hacking, soldering, and nerve-wracking disassembly of the dispenser, but it should be communicating with your Rasberry Pi. When this part is finished, you should have a dispenser that functions just as before, but now sends a message to your local Home Assistant server when the dispenser is activated.

In Part 2, we'll use Home Assistant to automate lights and make Alexa say funny things to the students. Our goal will be to make it so that students can't wait to hear what she'll say next.

Finally, in Part 3, we'll look at the data collection side of this and hypothesize ways to further increase student usage. We'll also look at ways to use the data to prove that it's increasing student usage of the dispenser.

Having different tricks up your sleeves, like an experienced teacher, can help you when you start to learn how to code. These tricks allow you to develop the metacognitive skills of learning how to learn. And knowing these strategies will help you analyze your learning material, reflect on what you are learning, and direct your path for learning.

In this three-part blog series, we will investigate three phases in a learning process, develop your metacognitive studying techniques, and focus our attention on improving your learning strategies. Whether it is your first day of coding or learning another skill for your career, using these processes can help you assess your learning journey and improve your coding knowledge.

Part One: What do you know?

When you first start to learn how to code, or if you want to learn a new concept in Python, your first thought is to turn to the Internet. Also, every experienced programmer recommends reading books, listening to podcasts, watching videos, or starting a course. Sometimes, if you are lucky to have one, you turn to a mentor. Regardless of the resource, usually, your main objective is to get a baseline understanding of new concepts, familiarize yourself with code snippets, and acknowledge any new vocabulary. You probably think that this step should be your first dive into the learning process.

However, you probably did not realize that the moment right before you opened the internet was a powerful opportunity for your learning process to be improved. So how do you engage this?

Let us look at it through a student-teacher scenario.

The process is dependent on what type of teacher you prefer to have instructing you. How a teacher chooses first to introduce a new topic of study to students depends on the teacher’s style or pedagogy. The deliverer of content, the “Sage on the Stage” person, is one type of teacher. This type will deliver the information required during your learning path. The Sage will tell stories that help you connect alternative concepts to the new topics being presented. Your role as a learner is to listen and visualize these connections. You are only a consumer of someone else’s knowledge. When learning independently, the experienced author, video, or tutorial has replaced the ‘sage’. Unfortunately, it is difficult to find quality resources that present concepts and the connections that your brain needs. However, a good “Sage on Stage” teacher knows that it is impossible for learning to happen without connection. Students need to experience connections to concepts to provide both a context and relevance, of meaningful and authentic learning.

However, as great teachers know, although sometimes entertaining, ‘Sages on stages’ do not always make the best educators!

Donna Ogle developed the KWL Chart in 1986, and the tool intended to help students activate their background knowledge before reading a nonfiction text. But over the years, this “tool” has been modified and used to help learners trigger and activate an understanding of different subjects and concepts. It is a great activity that every seasoned teacher should know, and every learner should try to apply. It is rooted deeply in the process of metacognition and focuses on being reflective and mindful of your learning process.

The KWL chart is divided into three parts but serves four functions.

• Assisting learners in activating prior knowledge,
• Setting an intention for the learning,
• Linking new information to previous knowledge, and
• Helping the learner to keep track of the learning process.

Let’s dive into using the KWL chart and how I have used it to learn Python.

There are many versions of the KWL Chart; the basis and the strength of it lie with three essential questions:

• What do you Know?
• What do you Want to know?
• What did you Learn?

Identifying “What do you Know”: How do we apply the first part of the KWL method; what do you know?

If you are new to coding, you may not think you know much; however, this task may surprise you. If you have coded before or are working on solving a unique problem or task, you may have a more robust understanding of your current knowledge. In either case, list out what you know is true. Wrestle with the things that you do not understand. Try to tease out where you should start. You can use bullet points, sketches, lists of words; just get it all out of your head. List out books you have heard of, authors, courses that your friends have suggested. The list should be extensive.

Having an awareness of what we know helps our brains to assign meaning and find substance. We need to be aware of things in order to recall or comprehend it. The stimulation of asking questions, and engaging in a brainstorming activity requires your brain to start to categorize and chunk the information you already know to be true.

In the brainstorming process, I do recommend you skim a few books. The books serve two purposes. First, they help you identify that most coding books are very similar in the topics and context; however, some may approach it very differently. And secondly, they may not fit your learning preference. For example, I once read a book called “Explain the Cloud to me Like a 10-year-old”. This book was easy to read and helped me get a general understanding of what the cloud is and does. However, when it came to python coding, I liked reading Finxter Coffee Breaks and Python for Kids as my first book. Two completely different styles of writing, but both served the purpose. I didn't know how to code, and interestingly enough, I didn't code along with any of these books, but I liked the explanations, the code snippets, and from reading over the code, I was beginning to gain basic knowledge of what I already knew about Python.

As you build your list, focus on what you already know first. Do you already know a language? Do you know about the importance of syntax in languages? Are you familiar with the concepts of conditionals in math? Are you good at breaking down large tasks? Can you understand how a program flows? As you begin to read through your first book, identify the connections you can make to things you already know. Making connections between new concepts and concepts with similar attributes will help your brain make more connections. Furthermore, these joyous moments will help you when confidence is low or if you need to create relationships with other topics later on.

There are very few teaching tools that are as effective as they are easy to use. And what is even better, they are super to use when you are teaching yourself to code! The initial discovery of vocabulary helps the learner identify what is already known or what connections are made.

"To be a successful problem solver, focus first. We get stuck in problem solving when we don’t first prepare our brain by focusing on the basics. Don’t just dive into problem solving without studying the explanations first. You need to lay some basic trails on the focused pinball table.”

Barbara Oakley

As you are skim reading, you may realize that a book, is just ‘not for you.’ You may decide to switch up, do it. Do not let a book that you can’t connect to, stop you from learning how to code. More importantly, the more books you can quickly skim can help you gather different perspectives on learning how to code.

So go for it, list out what you already know!

“Learning is finding out what you already know. Doing is demonstrating that you know it. Teaching is reminding others that they know just as well as you. You are all learners, doers, teachers.”

― Richard Bach

Introduction

One of the things that I realized as I was beginning to learn Python is that my strength as a teacher would come in very handy. A teacher’s “tool belt” is earned through years of grit, dedication, and intention. Teachers often don’t realize all the tools they have accumulated until there is a need. But we call upon these skills, not only for our students but also for self-guided/independent learning. My tools helped me identify and guide my Python learning journey. And being able to locate quality resources would prove to be critical to part of my success with coding.

In this three-part blog series, we will investigate three phases in a learning process, develop your metacognitive studying techniques, and focus our attention on improving your learning strategies. Whether it is your first day of coding or learning another skill for your career, using these processes can help you assess your learning journey and improve your coding knowledge.

Before We Begin: The Importance of Resources

Using different resources help you to decipher complex topics and then construct a new picture in mind. Teachers know that finding resources is only half of the battle. An adept learner has to sift through the resources that work best and process the concepts consumed during the learning. And this is just one of the skills that most teachers have in their tool belts.

Teachers know that deep learning begins with establishing a baseline of knowledge and carefully scaffolding new concepts to build brain connections. While teaching for deeper understanding, a teacher will encourage students through many skills. Students need to be reflective of what guides them during the process of building content knowledge. Teachers are always directing students to employ these methods independently and build on what they already know.

"An adept learner has to sift through the resources that work best and process the concepts consumed during the learning."

The Importance of Mindset

Adopting a positive mindset is continuously encouraged. Teachers recognize that learning is a journey of twists and turns, interlaced with mistakes and opportunities to fail forward. Therefore, it is best to guide students to embrace a positive mindset early on in the learning path. Once the growth mindset is accepted, a student will be more prepared to identify “fails” and use techniques to learn and fail forward faster.

A teacher knows that learning is a lot of finding out what you already know, understanding how to take in new concepts, discovering how a learner learns, and realizing the best learning method for students.

These tactics are tried and true methods that many teachers have researched, developed, and perfected to help keep their students along the positive learning path, despite their occasional twists in the wrong direction. These teaching techniques allow learners to continue to develop lifelong learning skills necessary for self-teaching and daily problem-solving!

The Importance of Learning Like You are a Teacher

Like an experienced teacher, having different tricks up your sleeves can help you when you start to learn how to code. These tricks allow you to develop the metacognitive skills of learning how to learn. And knowing these strategies will help you analyze your learning material, reflect on what you are learning, and direct your path for learning.

Now, Let's Begin with Part 1

When you're ready, let's get started with Part 1 of The Metacognitive Process: What Do You Know?

You Might Be Teaching a 6th Grader How to Code If...

Teaching 6th Graders How to Code: A Humorous Journey

Revised Paragraph:
I have been teaching 6th graders to code for approxiamtely five years now, and it sill presents a unique blend of challenges and laughter. Most of our Lower School students use Chromebooks and in the Middle School students switch to using Macbooks. This tranistion is a huge leap for our 6th graders. For many, it's their first encounter with a full-fledged computer. Teaching 6th grade can be difficult, but it is also very endearing.

Over the years, I have come to appreciate the humor in navigating the predictable hurdles. Teaching quarter classes, calls for a lot of repetition, and it is a situation where you either laugh or cry. I choose to laugh—often quietly to myself. Each coding lesson "feels like a scene that could fit into a comedy show", only with syntax errors and infinite loops instead of "comedic tropes," all delivered in a tone suitable for school.

Watching these young coders tackle variables, loops, errors and functions "mirrors their journey into their teenage years," marking a life full of mistakes and successes and unusual changes. My role as an educator has evolved from being a coding teacher to becoming a source of patience and encouragement, guiding them through the coding world with a patient smile, even on challenging days.

By embracing the chaos, finding humor in our journey, and reflecting on our collective experiences, I have realized that the essence of teaching goes beyond merely transferring my knowledge to them. It's about fostering an environment where mistakes are learning opportunities, laughter is therapeutic, and every challenge is a chance to grow—not only for the students but also for myself.

This is the core of education, and in these moments of shared struggles and triumphs, I wouldn't want it any other way.It's not just about the jokes that fill the room but also about adopting a lighthearted approach to ease the inevitable mishaps that accompany learning coding—a subject both intricate and strict. Here's my comedic take, inspired by Jeff Foxworthy's style, on the challenges and hilarities of teaching coding to 6th graders.

1. Installation Woes

You might be teaching a 6th grader how to code if...

...your lesson starts and your students ask, “What's an application and how do you install it?”

On the first day of every quarter I "embark" on the challenge of helping students install an editor from the internet. A task that consistently, without fail takes an hour long!

Explaining that an application is an app is a conversation in itself. Privacy and Security settings, moving the application into the application folder, and many more topics happen after this question. I could avoid this lesson, and it is a tempting idea and download the apps for them, but mastering these tasks is an essential skill. It's about more than just doing the task; it's about equipping students with the tools they'll need to navigate their new computers after they leave my class.

2. Multiple Versions of Everything

You might be teaching a 6th grader how to code, if...
...your students have twelve versions of the Mu editor installed in their downloads.

After installing the Mu Python editor, the infamous .dmg file (and sometimes multiple rogue files) is always lurking somewhere, ready to be accidentally clicked on. Again.

Mac users, you know the struggle! Students often stumble upon the .dmg, launching "already" installed Mu, and bingo - another version joins the collection.

But hey, these moments are opportunities! We demystify cryptic file names, build tech-savvy youngsters, and perhaps earn a few "wow, you're amazing!"s along the way.

3. The Ever-Broken Editor

You might be teaching a 6th grader how to code, if...
...every class features a cry of “It's broken!”

Even with guidance, some students never quite master the installation process, this sometimes leaves "the Mu editor feeling a bit lost."

Usually, kids come to me with a "broken editor" but the "broken editor' isn't isn't broken and isn't saving files in the mu_code folder because they either they did not install it correctly, or the student decided that it was too much work looking for the mu_code folder or the Mu Application and moved them to their desktop or their files are scattered everywhere.in their computer.

This is a complex situation for 6th graders from the start, but after a little help, we identify the real problem. The "editor is broken and it won’t save files" issue is an easy fix- Mu just needs to live in the Mac Application folder and the students need a bit more time, understanding file storage issues.

4. The Lost File

You might be teaching a 6th grader how to code, if...
...your frequent response to “my file is gone” is a slightly sarcastic “Where did you save it?”

Switching from Google Drive's auto-save to manual saving your own files is a tough lesson to learn.

Students coming from a Chromebook experience are in the habit of using the awesome Google Drive features. The ‘automatic save’ even when it is an ‘Untitled document ’ can be a hard habit to break. I am always reminding students that they need to save their files, and more importantly name the file! This is a great opportinity to teach file nomenclature and consistency. It is another great lesson on how to teach both Mac users and Microsoft users about locating their files and folders.

When using the Mu Editor, files should save in the mu_code folder.

5. The Mystery of File Locations

You might be teaching a 6th grader how to code, if...
...a normal response from you, that sounds very much like a typical parent response is: “I don’t know where your file is. Where did you last see it?" All delivered with that familiar "I don't know where your shoes are".

For sixth graders (and most middle school students) remembering where they saved their files is a novel concept when they're used to just dumping everything in Google Drive. Sixth graders use of folders storage and storage pathways is very limited. Therefore, saving files on a device is often a new experience for our kiddos. I need to show students that files are stored in directories on their computer and there is a pathway to their files.

This lesson pops up throughout the quarter. It is incredible to think that our "digital natives" often know so little about their computers!
Knowing where you save files is a must when working with editors and python files.

6. Closing Applications

You might be teaching a 6th grader how to code, if...
..“yes, it's okay to exit out of Mu” becomes your end-of-class mantra.

Closing applications and ensuring their work is safe is a constant source of anxiety. Closing applications might seem like a simple task, but for budding coders, it can be a source of worry. This is also a great time to discuss "local" versus the "cloud". Students do not understand the difference from storing files on their computer versus storing them in an external server.

They may fear their work will vanish into the digital ether if they click the "X" button.

7. Creative File Naming

You might be teaching a 6th grader how to code, if...
...their files are named thingy.py, supcode2.py, or ajefhkaehrihroe.py.

Naming conventions are evidently not their strong suit.

As a 6th grade teacher, actively checking in on how your students name their files is a thing. Not because teaching nomenclature is a highlight of 6th grade, but because it persists into adulthood. For my sanity, I attempt to help students name files appropriately, so that we can locate their file later.

Like good documentation, naming conventions exist for a reason.

8. Magician of Shortcuts

You might be teaching a 6th grader how to code, if...
...you feel like a magician when showcasing shortcuts for their computers and coding in the Mu editor.

Their amazement at basic shortcuts is both heartwarming and hilarious.

In the Mu editor, some of my favorite shortcuts are CMD+A(ctrl+a), CMD+K (ctrl+k)or CMD+D (ctrl+d) and my favorite thing to say is, "Remember, coders are lazy!"

It's always rewarding to hear students say, “Wow! How did you do that?” or “Oh my gosh, how did you type that so fast?”

Teaching shortcuts whether coding or not can help your 6th graders learn to be more efficient. And sharing one or two shortcuts a week really can help the students learn, use and remember them.

9. The Never-Ending Uptime

You might be teaching a 6th grader how to code, if...
...you constantly remind them to shut down their computers.

With the 'always on' culture, they're often clueless about force quitting or handling an endless loop they accidentally created.

What else can I say except yes, students (and teachers) never shut their computers down and yes, they do not know how to shut down applications or force quit their applications.

Teaching simple troubleshooting techniques can save you a lot of time and headaches in the future.

Furthermore, teaching your students that it is okay to close down or shut down is a great habit to help them get into. It is also a good social-emotional skill of reminding kids to "shut-down" and take a break from tech sometimes.

10. Google-Fu Skills

You might be teaching a 6th grader how to code, if...
...their Google searches are long-winded questions like, “how do I write a variable named guest_name and then ask the end user what their name is and then print it out?” (This is an actual Google search done by a 6th grader. No lie!)

"Great coders know how to Google!" is a daily chant in my class.(6th graders are not allowed to use AI in our intro/foundations course of CS.) With Generative AI taking over the world, knowing how to ask for the right "thing" is important, whether using Google or and AI tool.

I model how to search for topics or words that we do not know/understand, both online and on generative AI software like(Flintk12 a 'safe' environment for students under 13 year olds) and we discuss how to break down large topics into smaller, easier to search concepts and words.

In all seriousness, teaching 6th graders to code, with all its challenges, is truly rewarding. And yes 6th graders are needy, naive and inexperienced computer users, they really grasp the concept of coding in 9 short weeks. Every class is filled with moments of laughter, surprise, and learning for both of us.

If you're an educator in this space, perhaps you can add to this "You might be teaching a 6th grader how to code if..." list!

(This article was originally posted Sept 2020, and revised March 2024. I used ChatGPT and Gemini to help me reformat with titles and to give feedback for clarity.)

Image created by https://wonderai.app/

Fast forward to today: I have taught hundreds of students how to code in Python, launched a podcast about it, and even attended PyCon and made friends from around the world in the Python community. You can do it too!

If you are looking for a place to start and need a little help, here are my five top tips for teaching coding when you are a coding newbie.

#1. Order lots of books!

I'm not saying that all the books you order will help you learn Python, but as a teacher, having a lot of resources to fall back on can give you a little extra confidence. I recommend getting a full bookshelf of resources that are designed for all levels of Python. Make sure that you get some books that are designed for kids, such as Python for Kids by Jason R. Briggs, Python for Tweens and Teens by Aristides S. Bouras and a Python book for your personal interest. As a teacher, I suggest Automate the Boring Stuff with Python: Practical Programming for Total Beginners by Al Sweigart.

Knowing that the answers to your students' and your own questions lie somewhere within a book is very comforting for a teacher learning a new subject. When a student has a question and does not know the answer, you can help be a facilitator of knowledge and give the student a book. This tactic serves multiple purposes: you encourage the student to research and read about the subject, and it gives you a moment to regain some composure.

In reality, a teacher's role is not to provide answers and be the "sage on the stage," instead, we should be the guide that teaches students the important lifelong learning skills that engage and motivates them. Promoting research and information literacy skills to help learn will come naturally as you teach Python. It is a skill that you will want to instill early on in your course. Even advanced programmers often research answers on sites like Stack Overflow to seek out ways to solve coding problems. It is the nature of coding to research and learn new concepts. In addition to this skill, your students' questions and researching the answers together will push your understanding of the coding language further than if you were learning alone at home.

#2. If you're not on Twitter, get on Twitter!

The Python community is incredibly supportive and open. Even if you are not communicating with them directly, just being a passive voyeur on Twitter can help you learn a lot about the language and the lingo really quickly. There are a lot of teachers out there who teach Python to different age levels. Many people are also just learning Python to have fun and code. There are also many experts out there who know Python and are always willing to help you out. If you search "Python" on Twitter, you can find a few people to follow and start learning with the rest of us. I suggest following @mkennedy from Talk Python, @brianokken from the Test and Code and Python Bytes Podcast, and Julian and Bob from @pybites. These four people have been super supportive in our teaching python journey.

#3. Get a mentor

A coding mentor is a person that will be there to support you through this crazy time! This person does not need to know Python, but it does help a lot if they understand something about computer science or programming.

The most important thing is that you find somebody who believes in you and is willing to pep you up when you're feeling aggravated, listen to you when you're feeling lost or frustrated, and support and commend you on the progress that you have made along the way. Teaching is sometimes a lonely and stressful profession, and teaching a new subject is even harder, but it doesn't have to be! Good mentors know what it is like to be new at something, and they can provide guidance, motivation, and emotional support. Having a colleague, administrator, or someone at your school that is there to pick up your spirits on those difficult or challenging days will help give you the motivation to continue with your learning and teaching journey.

If you do not have someone at your school, I suggest looking outside of your division or find someone you can connect directly with online or in another school. Alternatively, go a step further and find someone on Twitter. My mentor, Sean Tibor (@smtibor), and I are always willing to meet new Pythonistas.

#4. Don't be afraid to learn from your students

More than likely, there will be one or two kids that are natural Python coders or students who have coded in another language. It is only natural, and we are teaching in_ their world_ now. This fact can be very intimidating, and it can be very tempting for you to try to prove that you are the smartest person in the room. Don't! It is okay to _NOT _have all the answers to every question. Empower yourself to let the learning be reciprocal between you and your students. Embrace it and let your students know that you are learning too!

Remember, you are not the sage on the stage anymore. You are modeling a life-long learning mindset. Remind your students about the importance of the learning path. A trait of a good teacher and a great Pythonista is knowing how to ask the right question to research. Also, their questions give you new topics that you may need to learn or investigate.

A good question is one where the student does not know the answer. A great question is where neither the student nor the teacher has the answer!

#5. Just Jump Right Into Learning

It does not really matter where or how you start learning; just do it. Use videos to explain topics that you don't feel comfortable explaining and short tutorials to practice code when you start to feel exhausted from learning. I suggest using a tutorial to help you start teaching your first days of class. It is a great safety crutch, and students often like watching videos. Nevertheless, remember, as your students are learning to code, so are you. Use your teaching to help reinforce your understanding.

I suggest YouTube videos from sentdex and short tutorials from Grok Learning. My students love both of these resources, and so do I. Learning alongside students has helped me to solidify the information and the foundational knowledge of Python. I often watched more and did more exercises than I assigned, but that is because I found them fun and engaging. Find activities that help you learn and that challenge you along your learning journey. Remember, it is okay not to have all the answers on your first day of class. However, it is never okay to stop learning new things!

Good Luck!

Learning how to code in Python has taught me a lot about who I am as a teacher and a lifelong learner. As teachers, we try to instill a passion for learning in our students but sometimes, after teaching for many years, we forget what it feels like to learn something new! Thus, I challenge you to learn something new. Learn how to teach Python!

Every day, I am still practicing and learning Python, and you can too. It's a good feeling to be reminded that you don't know all the answers, but you are confident that eventually, maybe with some struggle, you will find the answers and solve some great problems with Python. Don't be afraid to embrace the struggle, and Happy Coding!