Podcast appearances and mentions of philip guo

Kelly talks with Philip Guo, creator of Python Tutor, about how the tool helps students trace code and understand programming basics. They also discuss the challenges AI-generated code creates in the classroom and possible ways to support student learning. *Wins of the Week * Philip: Hiring a second undergraduate student for Python Tutor, including one focused on user experience research with K-12 teachers Kelly: Finishing a year of in-person teacher trainings and reflecting on how far the teachers have come *AI, Coding, and Classroom Understanding * Much of the conversation focuses on how AI-generated code affects student learning. Kelly describes using AI code with eighth graders and how difficult it can be for them to understand functions, parameters, returns, and other fundamentals when the code is generated all at once. Philip suggests that tools like Python Tutor may be useful for helping students trace code and understand what is happening behind the scenes. Python Tutor and Possible AI Features Philip explains that Python Tutor currently visualizes execution and has an AI chat feature that can answer questions about code and errors. They discuss possible future features, including simplified AI-generated examples, alternative execution views that show only the lines actually run, and more guided inline help tied to specific code or variables. Oral Explanations and Assessment Kelly describes using a Socratic-style code review with students, where they discuss code aloud in groups. They also talk about using spoken explanations or short oral assessments to check whether students can really explain what code is doing, rather than just copying or prompting AI-generated answers. Broader Research and “Beyond the Desk” Philip briefly discusses a new research direction with a PhD student focused on AI support for work beyond the desk, including physical and embodied tasks in science labs and fieldwork. He says this differs from desk-based AI work and involves activities that are harder for current AI systems to support. **Chapters **0:25 Python Tutor and AI Learning 1:55 Hiring Help for Python Tutor 4:07 Classroom Wins and AI Reflections 6:11 Teaching Code Through Python Tutor 9:03 AI Code and Student Confusion 14:11 Simplifying Execution Traces 17:19 Functions Are the Hard Part 20:25 Keeping Fundamentals in AI Era 24:25 Socratic Seminars for Code 26:27 Voice-Based Code Thinking 29:27 Learning Beyond Lockdown 36:10 Prompting as a New Skill 36:25 Hardware Troubles and NeoPixels 40:15 Beyond the Code Editor 45:01 New Research on Embodied AI 49:12 PyCon and Community Plans 50:42 Teacher Call to ActionSpecial Guest: Philip Guo.

Philip Guo, an Associate Professor of Cognitive Science at the University of California, San Diego, built Python Tutor, which is neither just for Python nor really a tutor. It's actually a tool to visualize what code is doing! In today's episode, he talks about the other programming languages it supports (Java, C, and C++), gives examples of how he uses it, and explains the nuances of when to use it. See the transcript on the website (https://csedpodcast.org/blog/s4e4_tpb_coding_tutor/)

This week we are joined by Philip Guo and Sam Lau, researchers at the University of California, San Diego. Philip and Sam have recently published research on how computer science instructors use artificial intelligence tools like ChatGPT and GitHub Copilot in their classrooms. Join us to learn more about the data behind how generative AI is changing the way we teach computer science and coding. Special Guests: Philip Guo and Sam Lau.

Pandas is a great library that allows you to accomplish a ton of filtering and processing in condensed syntax. But how well do you understand what's happening? Sam Lau and Philip Guo built a great site to help use visually explore how Pandas is processing your dataset with your specific syntax. It's called PandasTutor, and Sam is here to tell us about it. Links from the show Sam Lau: samlau.me PandasTutor: pandastutor.com PythonTutor: pythontutor.com Principles and Techniques of Data Science book: textbook.ds100.org Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe on YouTube: youtube.com Follow Talk Python on Twitter: @talkpython Follow Michael on Twitter: @mkennedy Sponsors SignalWire Stack Overflow Talk Python Training

What's life after removing yourself from social media? Philip Guo joins Henry (the last in the "trilogy") to chat about LAT, life after Twitter. We discuss being irrelevant, forcing yourself to think about different things, treating a newsletter like email, restraining your growth, moving to the digital suburbs, engaging with the past, directing your attention and production, being particular and local, making it normal again to not have to create. (recorded in July) Transcript: https://hopeinsource.com/digital-death.

This week, Kelly and Sean interview Philip Guo, associate professor of cognitive science at UC San Diego. As a grad student in 2010, Philip created Python Tutor (https://pythontutor.com), the most widely-used program visualization tool for education. Using this tool, teachers and students can write Python programs directly in the web browser (without installing any plugins), step forwards and backwards through execution to view the run-time state of data structures, and share their program visualizations on the web. Over ten million people in more than 180 countries have used Python Tutor to visualize over 100 million pieces of code, often as a supplement to textbooks, lectures, and online tutorials. Special Guest: Philip Guo.

What's life after removing yourself from social media? Philip Guo joins Henry (the last in the "trilogy") to chat about LAT, life after Twitter. We discuss being irrelevant, forcing yourself to think about different things, treating a newsletter like email, restraining your growth, moving to the digital suburbs, engaging with the past, directing your attention and production, being particular and local, making it normal again to not have to create. (recorded in July) Transcript: https://hopeinsource.com/digital-death.

Why would you choose to leave the public internet on your own terms? Philip Guo joins Henry (for the 2nd time) to chat about his recent choice to make a minimal public web presence after being on the web for many years. We discuss the logistics of removing social media (Twitter, Facebook, YouTube), moving to longer forms of media (podcasts, essays, books), making introductory content, recognizing different stages of your career, being out of touch, freeing your mind for the next thing, not being ashamed of previous work, taking time to reflect, and friction. (recorded in May) Transcript: https://hopeinsource.com/unlisting.

Why would you choose to leave the public internet on your own terms? Philip Guo joins Henry (for the 2nd time) to chat about his recent choice to make a minimal public web presence after being on the web for many years. We discuss the logistics of removing social media (Twitter, Facebook, YouTube), moving to longer forms of media (podcasts, essays, books), making introductory content, recognizing different stages of your career, being out of touch, freeing your mind for the next thing, not being ashamed of previous work, taking time to reflect, and friction. (recorded in May) Transcript: https://maintainersanonymous.com/unlisting.

Philip Guo (http://pg.ucsd.edu) is an assistant professor of cognitive science at UC San Diego. His research spans human-computer interaction, programming tools, and online learning.

Are you using interactive notebooks for your data exploration or day-to-day programming? What environment do you use? Was it Jupyter and now you've made the move to JupyterLab? That's a great choice. But did you know there are more environments out there to choose from and compare? Have you heard of Callisto or Iodide? How about CoCalc or PolyNote? That's just the tip of the iceberg! That's why I'm happy to have Sam Lau and Philip Guo here to share their research comparing and categorizing over 60 notebook environments. Links from the show Sam on Twitter: @samlau95 Philip's site: pgbovine.net The paper: pgbovine.net/publications.htm PDF download: computational-notebooks-design-space_VLHCC-2020.pdf NBInteract: nbinteract.com NBStripout: pypi.org/project/nbstripout Audio live coding: foxdot.org NBDev: github.com/fastai/nbdev PyIodide episode: talkpython.fm Carnets: holzschu.github.io/Carnets_Jupyter Sponsors Linode Sentry Error Monitoring, Code TALKPYTHON Talk Python Training

A conversation with Philip Guo, Assistant Professor of Cognitive Science at UC San Diego

Do you run an open-source project? Does it seem like you never have enough time to support it? Have you considered starting one but are unsure you can commit to it? It's a real challenge. On this episode, we welcome back Philip Guo, who has been a solo maintainer of the very popular PythonTutor.com project for over 10 years. He has some non-traditional advice to keep your sanity and keep your project going while holding down a busy full-time job. Links from the show Philip on Twitter: @pgbovine Python Tutor: pythontutor.com Philip's website: pgbovine.net Python Tutor on github: github.com Dismissing Python Garbage Collection at Instagram: instagram-engineering.com Threshold Concepts in Computer Programming: blogs.kcl.ac.uk SageMath: sagemath.org Sponsors TideLift Clubhouse Talk Python Training

Support these videos: http://pgbovine.net/support.htmhttp://pgbovine.net/PG-Vlog-392-writing-on-my-own-platform.htm- [Blog@CACM - Philip Guo](https://cacm.acm.org/blogs/blog-cacm/?author=Philip+Guo)- [Silent Technical Privilege](http://www.slate.com/articles/technology/technology/2014/01/programmer_privilege_as_an_asian_male_computer_science_major_everyone_gave.html) ([original article on my website](http://pgbovine.net/tech-privilege.htm))- [Why Academics Feel Overworked](https://www.insidehighered.com/advice/2014/12/01/essay-why-academics-feel-overworked) ([original article on my website](http://pgbovine.net/why-academics-feel-overworked.htm))Recorded: 2019-11-09 (2)

Do we learn in a vacuum, or does it involve our whole selves? Philip Guo (UC San Diego) joins Henry to chat about maintaining a web presence since its beginnings. We discuss some of the points made in Nadia's post on ideas carrying us forward, even beyond what we are known for, the greater intimacy of podcasts and vlogs, attaching ideas to people, science as subjective vs. purely objective and in community, knowledge as opening up possibilities, embracing whimsy and being random (haircut podcasts), embracing spontaneity and cities, understanding our bodies and mortality and it's relation to our digital lives and rest. Transcript: https://maintainersanonymous.com/growing-old

Do we learn in a vacuum, or does it involve our whole selves? Philip Guo (UC San Diego) joins Henry to chat about maintaining a web presence since its beginnings. We discuss some of the points made in Nadia's post on ideas carrying us forward, even beyond what we are known for, the greater intimacy of podcasts and vlogs, attaching ideas to people, science as subjective vs. purely objective and in community, knowledge as opening up possibilities, embracing whimsy and being random (haircut podcasts), embracing spontaneity and cities, understanding our bodies and mortality and it's relation to our digital lives and rest.

Philip Guo researches ways to scale programming education beyond the classroom. He is the creator of Python Tutor (http://pythontutor.com/), a widely-used code visualization and collaborative learning platform, and an assistant professor at UC San Diego. In this episode, we discuss why diverse groups of people study CS, his various prototypes, and the differences between technological research and industry. http://futureofcoding.org/episodes/22

Roger makes a special appearance on Philip Guo's Podcast to talk about podcasting in academia and white boards. Show notes: Philip Guo's web site: http://pgbovine.net/index.html Effort Report Stickers: https://www.stickermule.com/marketplace/17852-the-effort-report-podcast Roger on Twitter: https://twitter.com/rdpeng Elizabeth on Twitter: https://twitter.com/elizabethmatsui Effort Report on Twitter: https://twitter.com/theeffortreport Get The Art of Data Science: https://leanpub.com/artofdatascience Subscribe to the podcast on Apple Podcasts: https://pcr.apple.com/id1133375717 Subscribe to the podcast on Google Play: https://play.google.com/music/listen?authuser#/ps/Iz7gvpa3d6qro3btjmfk7g3l2gu Find past episodes: http://effortreport.libsyn.com Contact us at theeffortreport@gmail.com