AI: Introduction

Brief introduction to the underlying structure and function of generative AI systems, with definitions of key acronyms and terms, a stop-bystep look at the process used to generate text and images.

Detailed explanation of the structure and function of generative AI systems written for a non-technical audience.

Brief report drawing on focus group interviews with over 200 college and university students in the UK about their use and perceptions of generative AI. These students view generative AI as a tool to develop their ideas; want to use AI because it will be part of their future jobs; have concerns about the ethics, equity, and accessibility of AI tools; and expect their instructors to be competent in the use of AI and integrate it into teaching.

Detailed user study of ChatGPT 4.0, Bard, and Bing Chat. Users trusted the bots and found them useful, especially appreciating how they cut the time needed to collect and summarize information. Users did not verify bot suggestions and were also disappointed when the bots did not respond with follow-up questions, "forgot" the context of the conversation, or refused to answer prompts outside programming-imposed guardrails.

Thoughtful and relatively brief article addressing reasons to incorporate generative AI into the classroom and placing the current services into context of earlier tools.

Educator and author Mollick shares lessons from a semester of student use of generative AI in class. Notable points include "without training, everyone uses AI wrong," "students understand accuracy and bias issues," and "AI is everywhere already."

Thoughtful advice on how to use generative AI that concludes, "Never directly send, publish, or share a piece of writing generated by a genAI tool without reviewing it first." Includes a decision-making flowchart.

AI detectors don't work and may cause more harm than good. Supposed "AI detection" tools not only fail regularly at finding AI-generated text, they also often flag text written by non-native English speakers as suspect.

Thoughtful and lengthy blog post from renowned literacy scholar on the potential impacts of generative AI on education.

Thoughtful piece on the possible importance of AI prompting to the workforce of the future.

YouTube playlist of 5 videos by Ethan Mollick of the Wharton School on the basics of generative AI aimed at teachers and students.

Free video course on using a number of generative AI tools. 2 hours total.

Hour-long webinar that "covers the importance of digital literacy in the context of AI interaction. Teaching students how to evaluate information generated by AI tools can help them understand the importance of source evaluation and will help them not only in college but also in their daily lives. Although the focus has been on ChatGPT and students utilizing it to write essays, students can use AI tools to develop their semester schedule, edit an essay, understand a complex topic, and research esoteric fields."

Free, 2-hour course in prompt engineering, the underlying structure of ChatGPT and other Large Language Models (LLMs), and general principles for getting the best results from these tools.

First-hand report from a teacher on uses of ChatGPT in history, economics, and speech and debate classes, with techniques which could be applied in other disciplines, too.

A guide that "provides a structure for learning to use AI, including explanations of key AI concepts and questions to consider when using AI. ... The framework is intended to meet people where they are and scaffold upon their current AI literacy level, whether they have little to no knowledge of AI or are prepared to build their own large language model (LLM)."

Shortened overview of the article below focusing on strategies for AI integration and examples of those methods in action.

Abstract: "This paper examines the transformative role of Large Language Models (LLMs) in education and their potential as learning tools, despite their inherent risks and limitations. The authors propose seven approaches for utilizing AI in classrooms: AI-tutor, AI-coach, AI-mentor, AI-teammate, AI-tool, AI-simulator, and AI-student, each with distinct pedagogical benefits and risks. The aim is to help students learn with and about AI, with practical strategies designed to mitigate risks such as complacency about the AI’s output, errors, and biases. These strategies promote active oversight, critical assessment of AI outputs, and complementarity of AI's capabilities with the students' unique insights. By challenging students to remain the "human in the loop", the authors aim to enhance learning outcomes while ensuring that AI serves as a supportive tool rather than a replacement. The proposed framework offers a guide for educators navigating the integration of AI-assisted learning in classrooms."

Abstract: "This paper provides guidance for using AI to quickly and easily implement evidence-based teaching strategies that instructors can integrate into their teaching. We discuss five teaching strategies that have proven value but are hard to implement in practice due to time and effort constraints. We show how AI can help instructors create material that supports these strategies and improve student learning. The strategies include providing multiple examples and explanations; uncovering and addressing student misconceptions; frequent low-stakes testing; assessing student learning; and distributed practice. The paper provides guidelines for how AI can support each strategy, and discusses both the promises and perils of this approach, arguing that AI may act as a “force multiplier” for instructors if implemented cautiously and thoughtfully in service of evidence-based teaching practices."

Overview of uses of ChatGPT in teaching from its provider.

Tips and resources gathered by the campus Center for Teaching Excellence to help with teaching and learning.

Information on legal cases involving AI and its use in some form "covering everything from algorithms used in hiring and credit and criminal sentencing decisions to liability for accidents involving autonomous vehicles[, ...] some cases concerning statistical analysis and data protection that may not directly involve artificial intelligence, but that are of particular relevance to AI projects."

Comprehensive introduction to generative AI and information about specific tools compiled by the staff at Syracuse University's library.

Materials on many aspects of AI use and development aimed at using them as teaching and learning tools at the university level.

Very thorough listing of AI tools, uses, and considerations around its usage in academia compiled by Melissa S. Del Castillo, FIU Libraries.

Open to all students, SIU's Digital Humanities Lab (a.k.a. the Center for Virtual Expression) offers hands-on experience and assistance with AI, VR, and simulator tools and software. If you want to see what the cutting edge looks like, this is the place to go on campus.

Categorized lists of AI resources of interest to teachers.

A "potpourri" of links to generative AI resources of possible use or interest to educators.

Helpful discussion of how to craft the sort of prompts which will get the results you want from generative AI services.

Blog, newsletter, and upcoming book by Princeton researchers which serves as a "voice of reason" amid all the AI hype. A study sound too catchy or too good to be true? These folks likely have the real story. For example, "Is GPT-4 getting worse over time?."

List of resources about AI aimed at librarians, but useful well beyond that profession.

Extensive of list of generative AI tools, tips for using them, and contextual information.

Blog of teaching and learning resources for educators.

Blog focused on the intersection of technology and libraries.

Discord-based AI image generating service. Offers a very limited free trial before requiring a subscription.