Note: This is the first post in an experiment at shared blogging by Punya Mishra, Nicole Oster and myself. Over the past months we have found ourselves engaged in some fascinating conversations around genAI, education, bias and more. This shared blogging experiment is an attempt to take some of these conversations and move them into this sharable […]
An important feature of a learning machine is that its teacher will often be very largely ignorant of quite what is going on inside. A. M. Turing, Computing Machinery and Intelligence, 1950 Last week at the SITE conference, I talked with Katrina Tour from Monash University about her work with refugees in Australia. She is […]
I thoroughly enjoyed attending the 2024 Society for Information Technology and Teacher Education conference in Las Vegas, Nevada last week. Great people, great ideas. New and old friends. A quick recap: Friends! The best part of this conference was meeting up with some great friends from Arizona State, New Mexico State, and Monash Universities. (including […]
GenAI is weird. It is not human, but it can sound like it. It is very confident in its errors but, when confronted, quick to apologize…and repeat the same errors again. It could be seen as a synthesis of the internet (good, bad, and ugly) but with human guardrails that attempt to fix the ugly […]
Lately I’ve felt like I’m living in parallel universes. On one hand, I am trying to get the word out of the bias in GenAI, the problems that can cause, and the caution we should be using when these technologies are applied in educational contexts. For example, ChatGPT 3.5 provides lower average writing scores when […]
I have the honor of sharing some ideas about teaching, learning, and AI with New Mexican Educators Rising members at the 2024 Conference. Here are some concepts and resources that might be useful. Ideas for using LLMs in Learning Ideas for using LLMS in Teaching Additional Resources Videos Santa Fe Institute: The Future of Artificial […]
Access resources here! Bad Audio of All Presentations: Bias in LLMs: It’s Not What You Think Full Paper: Warr, Melissa and Oster, Nicole Jakubczyk and Isaac, Roger, Implicit Bias in Large Language Models: Experimental Proof and Implications for Education (November 6, 2023). Available at SSRN: https://ssrn.com/abstract=4625078 or http://dx.doi.org/10.2139/ssrn.4625078 Beyond Cheating: Using LLMs in Teaching and Learning Higher Ed […]
*Cover image created with ChatGPT4, Dall-E3, and Adobe Firefly I recently had a discussion about “generative learning.” It was a phrase I hadn’t heard before. A bit of research and I found it that it is, indeed, a thing–and it was a thing before the generative AI shockwave of 2022. Although it was interesting to […]
While on a walk the other day, I was listening to a (rebroadcasted) episode of RadioLab: During the episode, they discuss Benford’s Law–that in many contexts, there are more numbers that start with lower digits (1, 2, etc.) than higher digits (8, 9, etc.): This law holds for river length, population growth, stock prices, and […]
Cover image courtesy of Punya Mishra We (Punya Mishra, Rezwana Islam, and I) just published a new article in the Journal of Digital Learning in Teacher Education. The article considers the meaning of TPACK in a world of generative AI. We particularly wanted to emphasize the need of teachers to develop contextual knowledge. It was […]