Are you concerned about assessment in the age of AI?
Faculty for Undergraduate Neuroscience
August 30, 2024
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Facilitator
Facilitator
Lew Ludwig
Lew Ludwig
Dr. Ludwig is a Professor of Mathematics and the director of the Center for Learning and Teaching. at Denison University. He is a nationally recognized speaker on generative AI, leading numerous webinars and workshops for the MAA, POD, and the GLCA. His work includes serving as a project leader on the MAA Instructional Practice Guide and presenting innovative teaching strategies at various national conferences.
Hot off the press piece on AI
Enjoy Joshua Rothman’s excellent article, "What Does It Really Mean to Learn?" in The New Yorker. Rothman explains into "educability"—the deep, ongoing human capacity to learn, contrasting sharply with the limitations of artificial intelligence. This piece explores the beautiful, often messy process of human learning, where knowledge isn't just acquired but woven into the rich tapestry of our experiences and insights. Read the article or listen to the nine-minute audio for a compelling perspective on the unique nature of human intellect. From a SLAC? Be sure to catch the "mic drop" sentence at the end.
Very recent pieces on AI
AI and the Case for Project-Based Teaching
In the age of ChatGPT, faculty members have no choice but to adjust course design from a focus on “what” to “why.” by Chad Raymond
Why We Should Normalize Open Disclosure of AI Use
It’s time we reclaim faculty-student trust through clear advocacy — not opaque surveillance. by Marc Watkins
Ryan Watkins discusses the impact of AI on professional agency, offering strategies to balance AI integration with maintaining human control and expertise.
In Teaching With Gen AI, Consider Sustainability
Faculty lack information about generative AI’s environmental impacts, and universities should prioritize sustainable computing, Susanne Hall writes.
An excellent resource for both students and faculty, this student guide by Elon University and the AAC&U is designed to navigate college life in the AI era. Freely available, it offers practical advice on using AI responsibly and enhancing academic and career journeys. Access it at studentguidetoai.org to start leveraging AI effectively in your educational and professional endeavors.
The mathematics behind LLMs
A MUST FOR ALL MATH STUDENTS!
This is a continuation of the Neural Networks series, which introduces the mathematics and deep learning involved in transformers and their prerequisites.
3Blue1Brown April, 2024
A five part series from 2017 explaining neural networks, how they are trained and the concept of backpropagation. Requires a basic understadning of linear algerbra and mulit-variable calculus.
3Blue1Brown October, 2017
How to get started with Generative AI
Subscribe to the 'On Tech A.I. Newsletter' from The New York Times to embark on your journey to becoming an AI expert. This weeklong series is just the beginning, with regular updates every few weeks to keep you informed throughout the year.
NYT April, 2023
A series that chronicles my exploration of generative AI as it relates to mathematics and my calculus. class. In particular using AI for coding and mathematical image generation.
Lew Ludwig, April, 2024
Watch this video for an easy-to-understand guide on common AI terms, an overview of how the GPT model functions, a comparison between ChatGPT 3.5 and 4, and an insight into some of its limitations, presented by Lew Ludwig, August 2023.
Some Technical Things to Consider with Generative AI
MIT Technology Review
MIT Technology Review
The article explores the remarkable and puzzling capabilities of large language models, which can perform impressive feats of generalization and reasoning that defy traditional statistical understanding, leaving AI researchers scratching their heads about the underlying mechanisms that drive these models' success.
March, 2024
Harvard Business School
Harvard Business School
The article explores how AI like GPT-4 can boost or trip up the work, depending on the task at hand. It's a deep dive into when AI is a help and when it's not!
September, 2023
The current issue of the Bulletin explores the impact of artificial intelligence on mathematical research, asking whether AI will revolutionize the field, change research methodologies, and address the concerns and potential of using machine learning in mathematical proofs and beyond.
April, 2024
A visual walk-through of how this type of artificial intelligence work by Seán Clarke, Dan Milmo, and Garry Blight, The Guardian, November 1, 2023
Many things Mollick
An essential guide for educators on using AI as a transformative co-worker, co-teacher, and coach.
April, 2024
This paper introduces innovative AI-based exercises that empower faculty to design personalized, transformative learning experiences, fostering their role as builders and innovators for their students.
(Assumes some experience.)
April, 2024
A collection of prompts for instructors and students to help improve results from generative AI.
Working document
This blog/newsletter provides a research-based view on the implications of AI, Prof. Ethan Mollick of the Wharton School of Business
Working document
Other books on AI and Teaching
Offers educators a comprehensive and practical roadmap to effectively integrate AI into their teaching practices, addressing both the opportunities and challenges posed by AI, and equipping them with the tools to enhance learning, maintain academic integrity, and adapt to the rapidly evolving educational landscape.
Authored by Kevin Yee, Erin Main, Laurie Uttich, and Liz Giltner from the University of Central Florida, 50+ AI Hacks for Educators (.PDF), explores the urgent need for educators to understand and integrate Generative AI into their teaching, offering practical insights and strategies to enhance engagement and ensure students are well-equipped to use AI effectively in their careers.
July, 2024
Authored by Kevin Yee, Kirby Whittington, Erin Doggette, and Laurie Uttich from the University of Central Florida, 60+ Ideas for ChatGPT Assignments (.PDF), aims to explore the educational implications of ChatGPT and similar Large Language Models (LLMs) in the classroom setting.
September, 2023
Generative AI and Your Research
GenAI tools have transformed the landscape of research, providing new
methods for data collection, analysis, and interpretation. Here is a list of
cutting-edge GenAI applications designed to enhance efficiency and
creativity in research endeavors.
AI with and for your students
Ryan Watkins provides an adaptive survey you can use with students to determine what AI use is permissible or not in your classes.
July 27, 2023.
Explore how AI reshapes our roles in "Is AI Hijacking Our Agency?" by Ryan Watkins, urging us to mentor and guide appropriate AI use to avoid diminishing our self-efficacy and sense of control.
May, 2024
Editable surveys for you and your students
Editable surveys for you and your students
Its important to talk to your students about appropriate AI usage. Below are two editable Google Form surveys you can use with your students to begin these conversations. You will need to be logged into a Google account. Don't like these examples, use AI to help generate new ones. Here is a prompt to help get you started.
Calculus: You can make an editable copy of this Google form to create a progressive scale of student AI usage on a related rates assignment. Here is a list of prompts for each scale level students can use.
Intro to proofs: You can make an editable copy of this Google form to create a progressive scale of student AI usage on an equivalence relation assignment. Here is a list of prompts for each scale level students can use.
Alternative Grading and AI
In the age of generative AI, our educational practices are undergoing significant transformations. This technology compels us to reassess not just what and why we teach but also how we evaluate student learning. I believe one approach will be alternative grading methods, such as standards-based grading or contract grading, to better align with the evolving educational landscape. These approaches encourage a deeper, more personalized engagement with the material, creating a learning environment where students are motivated by curiosity and understanding rather than pursuing traditional grades.
by Linda B. Nilson (2014) - This book introduces specifications grading, a system that focuses on meeting specific criteria rather than accumulating points. It aims to restore rigor and motivate students while saving faculty time
edited by Susan D. Blum (2020) - This collection of essays by various educators discusses the drawbacks of traditional grading and provides practical advice on implementing ungrading practice.
by David Clark and Robert Talbert (2023) - This book critiques traditional grading systems and explores alternative grading methods like specifications grading and ungrading. It includes case studies and a workbook for designing alternative grading systems
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