Resource Page for Generative AI Talks and Workshop
Joint Math Meetings, Seattle
January 8-11, 2025
Joint Math Meetings, Seattle
January 8-11, 2025
Program details: Wednesday, January 8, 2025
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.
Dr. Karaali is a professor of mathematics at Pomona College. She is a founding editor of Journal of Humanistic Mathematics and a senior editor of Numeracy. Karaali has organized or facilitated several paper sessions and professional development workshops for mathematics faculty and K-12 teachers on a wide range of themes such as humanistic mathematics, teaching math for social justice, and writing.
Explore the integration of generative AI in math education, focusing on practical applications that enhance curriculum design and problem-solving. This hands-on workshop will cover the use of AI tools, such as ChatGPT, for creating dynamic assignments and facilitating an inclusive, engaging learning environment. Participants will develop AI-augmented educational materials, discuss the ethical dimensions of AI in the classroom and gain insights into preparing students for the AI-influenced future.
In this presentation, we examine the promises and pitfalls of generative AI, its application in SoTL research, and its role as a subject within SoTL. We will explore practical strategies for integrating AI tools into SoTL to enhance pedagogical effectiveness and engagement. Additionally, the talk will focus on how AI itself can become a focal point of SoTL studies, examining its impact on learning outcomes and educational practices. This presentation is designed for a general audience with no prior experience in generative AI.
Program details: Friday, January 10, 2025
Jackie Dewar is Professor Emerita of Mathematics at Loyola Marymount University in Los Angeles. Throughout her career and a decade into retirement her interests include scholarship of teaching and learning, K–12 math/science teacher preparation, gender equity in mathematics education, and the history of women in mathematics.
Have you ever wanted to develop a SOTL project but don’t know where to start? The goal of this presentation is to demonstrate generative AI’s use in teaching and learning both as an object to investigate and as a tool for conducting SoTL investigations. Among the three presenters are two with significant experience with SoTL (but not very familiar with the use of AI) and one person much more expert with generative AI (but less so with SoTL). With input from attendees, they will select a topic related to the use of AI in mathematics teaching and learning. Then with the assistance of generative AI software, the presenters and those in attendance will frame a question to investigate and develop a plan to carry out a SoTL investigation. Attendees will see how interacting with generative AI can help make progress on a SoTL project.
Program details: Saturday, January 11, 2025
In this presentation, we explore innovative methods for integrating generative AI into the mathematics classroom and beyond, emphasizing unique strategies that enhance both instructional productivity and student learning. We will cover applications such as automated content generation, personalized assessments, and AI-driven student support systems. By sharing real-world experiences and experiments, we aim to highlight the transformative potential of generative AI in reshaping the teaching and learning landscape for math faculty. No prior experience with AI is needed to benefit from these insights and applications.
Upcoming opportunities
This webinar invites mathematics faculty to explore generative AI tools in a way that is approachable, practical, and grounded in our professional context. Rather than advocating for technological adoption for its own sake, we will introduce low-barrier methods for experimenting with generative AI that may enhance various aspects of faculty work. By engaging with these tools in small, manageable ways, participants can gain firsthand experience to better understand the potential, the limits, and the broader implications of AI in academia. Our goal is not to prescribe the use of technology but to offer a space for open exploration—fostering a critical understanding that empowers participants to decide for themselves how, or if, these technologies might fit into their teaching, research, or administrative roles.
Artificial intelligence, particularly generative AI like ChatGPT, is on everyone’s mind right now. There is a robust and ongoing discussion of its risks and benefits, its potential impacts on higher education, the philosophical and ethical questions it engenders, and the ways in which faculty and students might use it effectively. This workshop will support the participants as they dive into these conversations as informed contributors. After a brief but informative exploration of the mathematics that makes these new technologies work, we will engage with the pedagogical challenges and promises they bring to the foreground. Participants will have the opportunity to work hands-on with a selection of AI platforms, with particular emphasis on the most widely used large learning model, ChatGPT. They will develop assignments or lessons that encourage students to make use of these technologies in a competent and yet critical manner.
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.
April, 2024
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 Levy and Pérez Albertos, 'Teaching Effectively with ChatGPT' explores concrete examples of AI integration in education, offering practical strategies and insights to enhance teaching and prepare students for AI utilization.
July, 2024
Books on Understanding AI
Still the OG of AI books, An essential guide for educators on using AI as a transformative co-worker, co-teacher, and coach.
April, 2024
Authored by Arvind Narayanan and Sayash Kapoor, AI Snake Oil critically assesses AI's promises and pitfalls. It acknowledges the potential of generative AI, such as ChatGPT, while debunking myths and exposing misleading claims about the capabilities of other types of AI. This book provides essential insights into the use and misuse of AI across various sectors, helping readers navigate the benefits and challenges of AI. Includes accompanying website with tons of resources.
Septemember, 2024
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.
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.
Some useful blogs
These are some blogs I follow on Substack.
A professor at the Wharton School of the University of Pennsylvania, who studies entrepreneurship & innovation and AI. He is trying to understand what our new AI-haunted era means for work and education.
Assistant Director of Academic Innovation, Director of the Mississippi AI Institute, Lecturer of Writing and Rhetoric at the University of Mississippi. He trains faculty in AI literacy.
With a background as an affiliated scholar at Cambridge University and former Chief Learning Officer, this page offers a deep dive into integrating AI with educational practices.
Some resources on crafting prompts
Prompts are the questions or instructions we submit to generative AI, more complex than queries to a search engine. Effective prompting is a skill that takes time to craft and develop. These resources offer suggestions, many of which you can customize and adapt for your specific needs.
Mollick advocates for "good-enough prompting" as a user-friendly method for interacting with AI, treating it as a capable but peculiar coworker. Mollick emphasizes the importance of experimenting with AI to understand its capabilities and limitations, aiming to make it accessible and effective for diverse applications.
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
A collection of prompts by the Mollicks for instructors and students to help improve results from generative AI.
Working document
Are you new to generative AI?
Here are some useful resources to help you get started.
Focused on the essentials and written to be accessible to a newcomer, this interactive guide will give you the background you need to feel more confident with engaging in conversations about AI in your classroom.
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.
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
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
A useful guide when considering AI Literacy
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.
Some Technical Things to Consider with Generative AI
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
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 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
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.
The "Cheat-Proof" Calculus Test
The article presents a comprehensive calculus exam question covering various topics like limits, derivatives, integrals, and theorems through a graphical approach, highlighting its effectiveness in assessing students' problem-solving abilities and deepening their understanding of calculus concepts.[1]
September, 2019
An innovative "take-home quiz" assessment approach for calculus courses where students create their own questions, graphs, and solutions over a week-long period, promoting higher-order thinking skills, retention through interleaving of concepts, and a sense of ownership while mitigating cheating concerns compared to traditional timed tests.
May, 2022
With the advent of generarive AI, explore one student's journey of attempting a cyborg approach to the "cheat-proof" calculus test.
May, 2024
A Possible Way Forward: 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.
This sample course created by Rachel Weir demonstrates how to create an alternate grading system in Canvas, aligning with the grading checklist provided in the syllabus. It also allows students to easily track their progress using the Learning Mastery gradebook.
Rachel Weir of Allegheny College has curated a comprehensive repository of resources for alternative grading in various math courses, ranging from developmental math to advanced analysis, and covering most levels in between.
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
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