Navigating the AI Landscape
MAA MathFest
August 8-9, 2024
Embedded Files
The "cheat-proof" calculus test
The "cheat-proof" calculus test
Prompt: Create a graph of a function f and a calculus question where the limit as x approaches a exists, but the limit does not equal f(a)
Prompt: Create a graph of a function f and a calculus question using the product rule for f (x) · cos x, where the answer can be found without a calculator.
Prompt: Create a graph of a function f and a calculus question where lim f′′(x) as x approaches a exists, but lim f′(x) as approached a does not exist (written as one question.
A list of prompts that we can explore from Yee, Kevin, Laurie Uttich, Eric Main, and Elizabeth Giltner. AI Hacks for Educators. FCTL Press, 2024. Creative Commons BY-NC-SA 4.0.
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
An example of the "cheat-proof" test which asks students to create questions about limits, derivatives, and integrals.
An ungraded example of a student's submission of Quiz 3, including the quiz and explanations key.
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
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.
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.
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.
Explore a more effective and authentic approach to grading, developed by two mathematics professors with input from colleagues across disciplines, to address common issues with traditional grading systems.
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