<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" encoding="UTF-8" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:sy="http://purl.org/rss/1.0/modules/syndication/" xmlns:admin="http://webns.net/mvcb/" xmlns:atom="http://www.w3.org/2005/Atom/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:googleplay="http://www.google.com/schemas/play-podcasts/1.0" xmlns:itunes="http://www.itunes.com/dtds/podcast-1.0.dtd" xmlns:fireside="http://fireside.fm/modules/rss/fireside">
  <channel>
    <fireside:hostname>app03</fireside:hostname>
    <fireside:genDate>Mon, 26 Oct 2026 08:49:22 +0000</fireside:genDate>
    <generator>Fireside (https://fireside.fm)</generator>
    <title>Teaching Python - Episodes Tagged with “Makecode”</title>
    <link>https://www.teachingpython.fm/tags/makecode</link>
    <pubDate>Wed, 09 Jan 2019 21:00:00 -0500</pubDate>
    <description>Teaching Python is a podcast about Python programming, computer science education, AI literacy, software development, cloud computing, cybersecurity, data, and how people learn technical skills. Hosted by Kelly Schuster-Paredes, Sean Tibor, and Julian Sequeira, the show is for educators, developers, technology leaders, and lifelong learners who want to better understand how Python connects to the wider world of computing. Episodes explore not only how people learn to code, but also how they build technical judgment, understand systems, evaluate AI-generated code, work with data, think about security, and move from beginner programming into real-world software development. About the Hosts Kelly Schuster-Paredes is a teacher who codes whose work has expanded from classroom computer science into AI strategy, curriculum design, professional learning, educational technology, and responsible technology adoption. Her background in Python and computer science education shapes her focus on learning, AI literacy, computational thinking, and what people need to understand in an AI-shaped world. Sean Tibor is Vice President of Infrastructure and Cloud at Pfizer and a former computer science teacher. He brings expertise in cloud computing, infrastructure, engineering operations, and technical leadership, connecting what people learn about computing with how large-scale systems are actually built, operated, secured, and maintained. Julian Sequiera is a technologist, Fractional CTO, and Senior Program Manager with more than 20 years of experience in infrastructure, cloud, engineering operations, and large-scale technology programs. He is also the co-founder of PyBites, a Python learning platform and community that has helped thousands of developers improve their Python and software development skills. What We Cover Python Programming and Computer Science Education: Learning Python, teaching programming, computational thinking, debugging, code literacy, and helping beginners build strong mental models. AI and AI Literacy: AI-assisted programming, evaluating AI-generated code, responsible AI use, human judgment, and what learners still need to understand when AI can produce code. Cloud, Infrastructure, and Cybersecurity: Systems, networks, deployment, security, reliability, architecture, and the operational side of software. Data and Software Engineering: APIs, databases, testing, maintainability, version control, software design, and moving from simple scripts to real-world applications. Learning and Technical Growth: How people learn difficult technical concepts, get unstuck, build confidence, and develop the judgment needed to use technology well. Expert Interviews: Conversations with educators, developers, engineers, researchers, technology leaders, and others shaping the future of computing and technical education. Teaching Python remains grounded in Python, but the conversation extends beyond syntax. The podcast explores the knowledge, skills, systems, and judgment people need to learn, build, and make responsible decisions with technology.</description>
    <language>en-us</language>
    <itunes:type>episodic</itunes:type>
    <itunes:subtitle>We're two computer science educators learning and teaching Python</itunes:subtitle>
    <itunes:author>Sean Tibor and Kelly Paredes</itunes:author>
    <itunes:summary>Teaching Python is a podcast about Python programming, computer science education, AI literacy, software development, cloud computing, cybersecurity, data, and how people learn technical skills. Hosted by Kelly Schuster-Paredes, Sean Tibor, and Julian Sequeira, the show is for educators, developers, technology leaders, and lifelong learners who want to better understand how Python connects to the wider world of computing. Episodes explore not only how people learn to code, but also how they build technical judgment, understand systems, evaluate AI-generated code, work with data, think about security, and move from beginner programming into real-world software development. About the Hosts Kelly Schuster-Paredes is a teacher who codes whose work has expanded from classroom computer science into AI strategy, curriculum design, professional learning, educational technology, and responsible technology adoption. Her background in Python and computer science education shapes her focus on learning, AI literacy, computational thinking, and what people need to understand in an AI-shaped world. Sean Tibor is Vice President of Infrastructure and Cloud at Pfizer and a former computer science teacher. He brings expertise in cloud computing, infrastructure, engineering operations, and technical leadership, connecting what people learn about computing with how large-scale systems are actually built, operated, secured, and maintained. Julian Sequiera is a technologist, Fractional CTO, and Senior Program Manager with more than 20 years of experience in infrastructure, cloud, engineering operations, and large-scale technology programs. He is also the co-founder of PyBites, a Python learning platform and community that has helped thousands of developers improve their Python and software development skills. What We Cover Python Programming and Computer Science Education: Learning Python, teaching programming, computational thinking, debugging, code literacy, and helping beginners build strong mental models. AI and AI Literacy: AI-assisted programming, evaluating AI-generated code, responsible AI use, human judgment, and what learners still need to understand when AI can produce code. Cloud, Infrastructure, and Cybersecurity: Systems, networks, deployment, security, reliability, architecture, and the operational side of software. Data and Software Engineering: APIs, databases, testing, maintainability, version control, software design, and moving from simple scripts to real-world applications. Learning and Technical Growth: How people learn difficult technical concepts, get unstuck, build confidence, and develop the judgment needed to use technology well. Expert Interviews: Conversations with educators, developers, engineers, researchers, technology leaders, and others shaping the future of computing and technical education. Teaching Python remains grounded in Python, but the conversation extends beyond syntax. The podcast explores the knowledge, skills, systems, and judgment people need to learn, build, and make responsible decisions with technology.</itunes:summary>
    <itunes:image href="https://cdn.fireside.fm/file/fireside-images-2024/podcasts/images/c/c8ea6bdf-0c80-46e7-a00a-639d7dc2be91/cover.jpg?v=3"/>
    <itunes:explicit>no</itunes:explicit>
    <itunes:keywords>Python, Python programming, learn Python, teaching Python, computer science education, coding education, programming for beginners, Python for beginners, computational thinking, code literacy, debugging, software development, software engineering, data science, artificial intelligence, AI literacy, AI-assisted coding, generative AI, machine learning, cybersecurity, cloud computing, cloud infrastructure, APIs, databases, systems thinking, technical education, STEM education, educational technology, edtech, curriculum design, instructional design, professional learning, teacher professional development, coding for students, computer science curriculum, physical computing, robotics, responsible AI, digital literacy, data literacy, technology leadership, developer education, technical coaching, lifelong learning, learning to code, teaching programming, real-world programming, coding with AI, Python podcast, computer science podcast, technology education podcast, programming podcast</itunes:keywords>
    <itunes:owner>
      <itunes:name>Sean Tibor and Kelly Paredes</itunes:name>
      <itunes:email>sean.tibor@gmail.com</itunes:email>
    </itunes:owner>
<itunes:category text="Education"/>
<itunes:category text="Technology"/>
<item>
  <title>Episode 6: Gaining a Deeper Understanding of Python With Coding Challenges</title>
  <link>https://www.teachingpython.fm/6</link>
  <guid isPermaLink="false">0c1751e5-5fbf-44af-9bde-7bb1dfd15df6</guid>
  <pubDate>Wed, 09 Jan 2019 21:00:00 -0500</pubDate>
  <author>Sean Tibor and Kelly Paredes</author>
  <enclosure url="https://aphid.fireside.fm/d/1437767933/c8ea6bdf-0c80-46e7-a00a-639d7dc2be91/0c1751e5-5fbf-44af-9bde-7bb1dfd15df6.mp3" length="20847674" type="audio/mpeg"/>
  <itunes:episode>6</itunes:episode>
  <itunes:title>Gaining a Deeper Understanding of Python With Coding Challenges</itunes:title>
  <itunes:episodeType>full</itunes:episodeType>
  <itunes:author>Sean Tibor and Kelly Paredes</itunes:author>
  <itunes:subtitle>Kelly and Sean are back in this week's episode to talk about the role of coding challenges for student understanding. Coding challenges are teacher-defined coding problems that students tackle individually or in groups with more than one possible solution. The advantages of these challenges compared to passive learning include deeper retention of skills and knowledge, opportunities for social and emotional education, and increased student confidence through subject mastery.</itunes:subtitle>
  <itunes:duration>37:01</itunes:duration>
  <itunes:explicit>no</itunes:explicit>
  <itunes:image href="https://cdn.fireside.fm/file/fireside-images-2024/podcasts/images/c/c8ea6bdf-0c80-46e7-a00a-639d7dc2be91/cover.jpg?v=3"/>
  <description>&lt;p&gt;Kelly and Sean are back this in this week's episode to talk about the role of coding challenges for student understanding. Coding challenges are teacher-defined coding problems that students tackle individually or in groups with more than one possible solution. The advantages of these challenges compared to passive learning include deeper retention of skills and knowledge, opportunities for social and emotional education, and increased student confidence through subject mastery.&lt;/p&gt;

&lt;h2&gt;What are coding challenges?&lt;/h2&gt;

&lt;p&gt;Coding challenges are teacher-defined coding problems that students tackle individually or in groups with more than one possible solution. Challenges are time-bound, i.e. they must be solved within a set period of time and range in complexity from simple code snippets to complete programs.&lt;/p&gt;

&lt;p&gt;For example:&lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;A 5-minute challenge to add comments to existing code&lt;/li&gt;
&lt;li&gt;A 3-day challenge to create a game in Python&lt;/li&gt;
&lt;li&gt;A standing challenge to solve a complex math problem by the end of the course&lt;/li&gt;
&lt;/ul&gt;</description>
  <itunes:keywords>python, teaching, coding, education</itunes:keywords>
  <content:encoded>
    <![CDATA[<p>Kelly and Sean are back this in this week's episode to talk about the role of coding challenges for student understanding. Coding challenges are teacher-defined coding problems that students tackle individually or in groups with more than one possible solution. The advantages of these challenges compared to passive learning include deeper retention of skills and knowledge, opportunities for social and emotional education, and increased student confidence through subject mastery.</p>

<h2>What are coding challenges?</h2>

<p>Coding challenges are teacher-defined coding problems that students tackle individually or in groups with more than one possible solution. Challenges are time-bound, i.e. they must be solved within a set period of time and range in complexity from simple code snippets to complete programs.</p>

<p>For example:</p>

<ul>
<li>A 5-minute challenge to add comments to existing code</li>
<li>A 3-day challenge to create a game in Python</li>
<li>A standing challenge to solve a complex math problem by the end of the course</li>
</ul><p><a rel="payment" href="https://www.patreon.com/teachingpython">Support Teaching Python</a></p><p>Links:</p><ul><li><a title="Simple Programming Problems" rel="nofollow" href="https://adriann.github.io/programming_problems.html">Simple Programming Problems
</a> &mdash; This page is a collection of progressively more difficult exercises that are suitable for people who just started learning. It will be extended as I come up with new exercises. Except for the GUI questions, exercises are generally algorithmic and should be solvable without learning any libraries. The difficulty of the exercises of course somewhat depends on the programming language you use. The List exercises for example are more complicated in languages like C that don’t have build-in support for lists.
</li><li><a title="Coding Games and Programming Challenges to Code Better" rel="nofollow" href="https://www.codingame.com/start">Coding Games and Programming Challenges to Code Better
</a> &mdash; Coding games to improve your programming skills.
</li><li><a title="The 10 Best Coding Challenge Websites for 2018 – Coderbyte – Medium" rel="nofollow" href="https://medium.com/coderbyte/the-10-best-coding-challenge-websites-for-2018-12b57645b654">The 10 Best Coding Challenge Websites for 2018 – Coderbyte – Medium
</a></li><li><a title="4 Things Transformational Teachers Do | Edutopia" rel="nofollow" href="https://www.edutopia.org/blog/big-things-transformational-teachers-do-todd-finley">4 Things Transformational Teachers Do | Edutopia
</a></li><li><a title="seantibor/microbit-compass: A digital compass using the BBC micro:bit and a laser-cut compass rose" rel="nofollow" href="https://github.com/seantibor/microbit-compass">seantibor/microbit-compass: A digital compass using the BBC micro:bit and a laser-cut compass rose
</a> &mdash; Repository for the 6th grade Microbit Compass Challenge
</li><li><a title="Chapter 3: Guess the Number" rel="nofollow" href="http://inventwithpython.com/invent4thed/chapter3.html">Chapter 3: Guess the Number
</a> &mdash; The guess the number challenge inspiration.
</li></ul>]]>
  </content:encoded>
  <itunes:summary>
    <![CDATA[<p>Kelly and Sean are back this in this week's episode to talk about the role of coding challenges for student understanding. Coding challenges are teacher-defined coding problems that students tackle individually or in groups with more than one possible solution. The advantages of these challenges compared to passive learning include deeper retention of skills and knowledge, opportunities for social and emotional education, and increased student confidence through subject mastery.</p>

<h2>What are coding challenges?</h2>

<p>Coding challenges are teacher-defined coding problems that students tackle individually or in groups with more than one possible solution. Challenges are time-bound, i.e. they must be solved within a set period of time and range in complexity from simple code snippets to complete programs.</p>

<p>For example:</p>

<ul>
<li>A 5-minute challenge to add comments to existing code</li>
<li>A 3-day challenge to create a game in Python</li>
<li>A standing challenge to solve a complex math problem by the end of the course</li>
</ul><p><a rel="payment" href="https://www.patreon.com/teachingpython">Support Teaching Python</a></p><p>Links:</p><ul><li><a title="Simple Programming Problems" rel="nofollow" href="https://adriann.github.io/programming_problems.html">Simple Programming Problems
</a> &mdash; This page is a collection of progressively more difficult exercises that are suitable for people who just started learning. It will be extended as I come up with new exercises. Except for the GUI questions, exercises are generally algorithmic and should be solvable without learning any libraries. The difficulty of the exercises of course somewhat depends on the programming language you use. The List exercises for example are more complicated in languages like C that don’t have build-in support for lists.
</li><li><a title="Coding Games and Programming Challenges to Code Better" rel="nofollow" href="https://www.codingame.com/start">Coding Games and Programming Challenges to Code Better
</a> &mdash; Coding games to improve your programming skills.
</li><li><a title="The 10 Best Coding Challenge Websites for 2018 – Coderbyte – Medium" rel="nofollow" href="https://medium.com/coderbyte/the-10-best-coding-challenge-websites-for-2018-12b57645b654">The 10 Best Coding Challenge Websites for 2018 – Coderbyte – Medium
</a></li><li><a title="4 Things Transformational Teachers Do | Edutopia" rel="nofollow" href="https://www.edutopia.org/blog/big-things-transformational-teachers-do-todd-finley">4 Things Transformational Teachers Do | Edutopia
</a></li><li><a title="seantibor/microbit-compass: A digital compass using the BBC micro:bit and a laser-cut compass rose" rel="nofollow" href="https://github.com/seantibor/microbit-compass">seantibor/microbit-compass: A digital compass using the BBC micro:bit and a laser-cut compass rose
</a> &mdash; Repository for the 6th grade Microbit Compass Challenge
</li><li><a title="Chapter 3: Guess the Number" rel="nofollow" href="http://inventwithpython.com/invent4thed/chapter3.html">Chapter 3: Guess the Number
</a> &mdash; The guess the number challenge inspiration.
</li></ul>]]>
  </itunes:summary>
</item>
  </channel>
</rss>
