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Friction by Design: A Framework for Centering Learning in the Age of AI

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Friction by Design: A Framework for Centering Learning in the Age of AI

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Friction by Design: A Framework for Centering Learning in the Age of AI

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Suggested citation: WestEd. (2025). Friction by design: A framework for centering learning in the age of AI (B. Busselle, Author). https://digitalfluency.wested.org/resources/friction-by-design-framework/

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The Manifesto for Teaching and Learning in a Time of Generative AI: A Critical Collective Stance to Better Navigate the Future

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The Manifesto for Teaching and Learning in a Time of Generative AI: A Critical Collective Stance to Better Navigate the Future

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DOI

10.55982/openpraxis.16.4.777

Publication Title

Open Praxis

Abstract

This manifesto critically examines the unfolding integration of Generative AI (GenAI), chatbots, and algorithms into higher education, using a collective and thoughtful approach to navigate the future of teaching and learning. GenAI, while celebrated for its potential to personalize learning, enhance efficiency, and expand educational accessibility, is far from a neutral tool. Algorithms now shape human interaction, communication, and content creation, raising profound questions about human agency and biases and values embedded in their designs. As GenAI continues to evolve, we face critical challenges in maintaining human oversight, safeguarding equity, and facilitating meaningful, authentic learning experiences. This manifesto emphasizes that GenAI is not ideologically and culturally neutral. Instead, it reflects worldviews that can reinforce existing biases and marginalize diverse voices. Furthermore, as the use of GenAI reshapes education, it risks eroding essential human elements-creativity, critical thinking, and empathy-and could displace meaningful human interactions with algorithmic solutions. This manifesto calls for robust, evidence-based research and conscious decision-making to ensure that GenAI enhances, rather than diminishes, human agency and ethical responsibility in education.

Data Availability

Article states: "The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request."

Original Publication Citation

Bozkurt, A., Xiao, J., Farrow, R., Bai, J. Y. H., Nerantzi, C., Moore, S., Dron, J., Stracke, C. M., Singh, L., Crompton, H., Koutropoulos, A., Terentev, E., Pazurek, A., Nichols, M., Sidorkin, A. M., Costello, E., Watson, S., Mulligan, D., Honeychurch, S.,...Asino, T. I. (2024). The manifesto for teaching and learning in a time of generative AI: A critical collective stance to better navigate the future. Open Praxis, 16(4), 487-513. https://doi.org/10.55982/openpraxis.16.4.777

ORCID

0000-0002-1775-8219 (Crompton)

Repository Citation

Bozkurt, Aras; Xiao, Junhong; Farrow, Robert; Bai, John Y. H.; Nerantzi, Chrissi; Moore, Stephanie; Dron, Jon; Stracke, Christian M.; Singh, Lenandlar; Crompton, Helen; Koutropoulos, Apostolos; Terentev, Evgenii; Pazurek, Angelica; Nichols, Mark; Sidorkin, Alexander M.; Costello, Eamon; Watson, Steven; Mulligan, Dónal; Honeychurch, Sarah; Hodges, Charles B.; Sharples, Mike; Swindell, Andrew; Frumin, Isak; Tlili, Ahmed; Slagter van Tryon, Patricia J.; Bond, Melissa; Bali, Maha; Leng, Jing; Zhang, Kai; Cukurnova, Mutlu; Chiu, Thomas K. F.; Lee, Kyungmee; Hrastinski, Stefan; Garcia, Manuel B.; Sharma, Ramesh Chander; Alexander, Bryan; Zawacki-Richter, Olaf; Huijser, Henk; Jandrić, Petar; Zheng, Chanjin; Shea, Peter; Duart, Josep M.; Themeli, Chryssa; Vorochkov, Anton; Sani-Bozkurt, Sunagül; Moore, Robert L.; and Asino, Tutaleni Iita, "The Manifesto for Teaching and Learning in a Time of Generative AI: A Critical Collective Stance to Better Navigate the Future" (2024). STEMPS Faculty Publications. 362.
https://digitalcommons.odu.edu/stemps_fac_pubs/362

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The Manifesto for Teaching and Learning in a Time of Generative AI: A Critical Collective Stance to Better Navigate the Future

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This manifesto critically examines the unfolding integration of Generative AI (GenAI), chatbots, and algorithms into higher education, using a collective and thoughtful approach to navigate the future of teaching and learning. GenAI, while celebrated for its potential to personalize learning, enhance efficiency, and expand educational accessibility, is far from a neutral tool.

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The Pedagogy of Trading Places: Lessons from an Unexpected Role Reversal with AI

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The Pedagogy of Trading Places: Lessons from an Unexpected Role Reversal with AI

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Faculty Focus | Higher Ed Teaching & Learning

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The Pedagogy of Trading Places: Lessons from an Unexpected Role Reversal with AI - Faculty Focus | Higher Ed Teaching & Learning

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Explore how AI can strengthen teaching by restoring creativity, supporting reflective practice, and helping faculty reconnect with their teaching identity.

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The Learn it All Educator: Rethinking AI in Higher Education (teaching guide)

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The Learn it All Educator: Rethinking AI in Higher Education (teaching guide)

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Artificial intelligence is affecting higher education, but not always in the ways we hoped. MIT neuroscience research shows that heavy AI reliance weakens neural connectivity and diminishes independent reasoning capacity, a process known as cognitive atrophy. Students who outsource their thinking to AI graduate with credentials but without the cognitive competence those credentials are supposed to represent. Meanwhile, faculty face a parallel challenge: how to use AI productively for their own work without surrendering the intellectual engagement that makes teaching meaningful.

This guidebook offers a third path between banning AI and surrendering to it. Rather than treating AI as either a threat to be resisted or a shortcut to be embraced, it provides practical, research-grounded frameworks for using AI to strengthen thinking, both the educator's and the student's. The central argument is that AI should function as a cognitive gym, not a cognitive elevator: a tool that adds productive friction and challenge rather than removing it.

The guidebook is organized around four core frameworks, each addressing a different dimension of AI integration in higher education:

Cognitive Triage helps educators reclaim time by distinguishing between work worth delegating to AI (FLUFF: Formatting, Layouts, Under-the-hood, Filing, Filtering) and ideas worth protecting for human thought (SPARK: Specific, Persuasive, Authentic, Rigorous, Keen-insight). This framework uses a harvesting-vs.-seeding metaphor to help faculty identify where speed and automation are appropriate (transactional tasks with capped payoffs) and where struggle and investment produce lasting value (growth-oriented work with uncapped payoffs).

The Intelligent Gearbox reframes AI prompting as a pedagogical skill. Understanding that AI is a probability engine, not a calculator, changes how educators interact with it. The chapter presents a four-gear progression of prompting techniques (One-Shot, Few-Shot, Chain of Thought, and Agentic) and reveals the guidebook's most powerful insight: the same principles that produce better AI outputs also produce better student learning. Scaffolding is not spoon-feeding; it is good instructional design. Every time you improve your prompts, you are practicing the skills that improve your teaching.

The Cognitive Gym reverses the lens from faculty efficiency to student development. When it comes to learning, the goal is not to remove friction but to add it strategically. This chapter introduces Progressive Overload (using AI as a coaching partner that increases challenge), a five-step AI Audit verification protocol (Assumptions, Sources, Counter-Evidence, Auditing, Cross-Model) that shifts assessment from content generation to verification, and the VINE Framework (Vivid, Insightful, Narrative, Evident) for developing editorial taste, the judgment that distinguishes average from excellent, which AI cannot replicate. Analog Checkpoints provide verification tools for confirming genuine cognitive engagement.

The Intelligent Simpleton addresses the most overlooked barrier to AI adoption: professional identity. The greatest obstacle to learning is not ignorance but ego, the need to appear as a know-it-all. Drawing on neuroplasticity research showing that growth happens at the edge of ability, this chapter explores how to use AI as a judgment-free zone for asking basic questions, how to overcome authenticity and institutional barriers, and why the courage to appear as a beginner is the path to remaining an expert.

The guidebook is designed for practical application, not passive reading. Each chapter includes conceptual frameworks, concrete examples spanning both academic and technical career disciplines, actionable strategies that can be implemented immediately, and reflective prompts for deeper engagement. It validates educators' legitimate concerns about AI's impact on learning before offering solutions, building credibility through shared understanding of the challenges rather than dismissing skepticism.

A companion set of faculty worksheets (published separately on Zenodo) provides structured activities for each chapter, designed for use in workshops, learning communities, or self-guided professional development.
Companion site for updates and resources: dataii.com/ai/guidebook
Table of Contents

The Learn-It-All Educator - Introduction: As a Human Thinketh, Our Learning Mindset

The Trap

The Reframe

What This Guidebook Offers

How to Use This Guidebook

Limitations and What This Guidebook Does Not Cover

Chapter 1: Cognitive Triage - Managing Educator Workload in the Age of AI

1.1 Harvesting vs. Seeding: Two Types of Academic Work

1.2 FLUFF: The Work Worth Delegating

1.3 SPARK: Ideas Worth Thinking

Putting It Together: From FLUFF to SPARK

Chapter 2: The Intelligent Gearbox - Advanced Prompting as Pedagogical Skill

2.1 AI Is a Probability Engine

2.2 Shifting Through the Gears

2.3 From Zero-Shot Prompting to Zero-Shot Teaching

Putting It Together

Chapter 3: The Cognitive Gym - Pedagogy and Student Assessment in the Age of AI

3.1 Progressive Overload and the Review Board

3.2 The Verification Protocol (Academic Integrity)

3.3 The VINE Framework for Taste

3.4 The Analog Checkpoint: When Performance Mimics Engagement

Putting It Together

Chapter 4: The Intelligent Simpleton - Professional Mindset for the Age of AI

4.1 The Ego Trap

4.2 Beyond Ego: The Authenticity and Institutional Barriers

4.3 Embracing the Learn-It-All Culture

4.4 The Courage to Play the Simpleton

References

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The Learn-It-All Educator - A Guidebook for Training Brains, Not Replacing Them with AI

# data[].attributes.attachment_link.description
Artificial intelligence is affecting higher education, but not always in the ways we hoped. MIT neuroscience research shows that heavy AI reliance weakens neural connectivity and diminishes independent reasoning capacity, a process known as cognitive atrophy. Students who outsource their thinking to AI graduate with credentials but without the cognitive competence those credentials are supposed to represent.

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Institutional Conditions for Integrating Emerging Technologies in Higher Education

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Institutional Conditions for Integrating Emerging Technologies in Higher Education

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Institutional Conditions for Integrating Emerging Technologies in Higher Education

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AI Literacy in Teaching and Learning: A Durable Framework for Higher Education

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AI Literacy in Teaching and Learning: A Durable Framework for Higher Education

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AI Literacy in Teaching and Learning: Executive Summary

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Students, faculty, and staff need to understand the fundamentals of AI to able to effectively use AI tools and evaluate the outputs.

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5 Tips for Assignment Design in the Agentic AI Age

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5 Tips for Assignment Design in the Agentic AI Age

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Inside Higher Ed | Higher Education News, Events and Jobs

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5 Tips for Assignment Design in the Agentic AI Age (opinion)

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If AI agents can do the homework, what should we grade instead?

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Teaching: Assignments that mitigate AI abuse

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Teaching: Assignments that mitigate AI abuse

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Professors are struggling in asynchronous and large-enrollment courses. Here are some ideas that could help.

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More tips for preventing AI misuse in the classroom

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More tips for preventing AI misuse in the classroom

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https://www.chronicle.com/newsletter/teaching/2025-07-17

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More Tips for Preventing AI Misuse in the Classroom

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Readers share their strategies, often focusing on process over product.

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Student Guide to Artificial Intelligence

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Student Guide to Artificial Intelligence

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multimedia content creation for education

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Your go-to podcast for the latest breakthroughs, trends, and insights at the intersection of artificial intelligence and education. From innovative classroom tools to groundbreaking research, we bring you bite-sized updates every day to keep you informed and inspired. Tune in and discover how AI is shaping the future of learning!

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Open Source Artificial Intelligence (AI)

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Open Source Artificial Intelligence (AI)

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version 1.0 Preamble Why we need Open Source Artificial Intelligence (AI) Open Source has demonstrated that massive benefits accrue to everyone after removing the barriers to learning, using, sharing and…

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Student-Made Bots: An E Student-Made Bots: An Educator’s Toolkit

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Student-Made Bots: An E Student-Made Bots: An Educator’s Toolkit

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Student-Made Bots: An Educator’s Toolkit

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This tutorial is a practical guide for instructors interested in helping students design their own custom educational bots using large language models (LLMs). No programming is required—just critical thinking, creativity, and curiosity.
While adaptable across disciplines, it is especially geared toward teacher education courses, supporting future teachers in critically engaging with AI in the classroom. Students build bots in roles such as tutor, motivational coach, philosopher, and more—reflecting on design, purpose, and ethics.
The toolkit includes templates, sample bots, and a recommended semester timeline to support AI literacy, hands-on experimentation, and ethical reflection. It also links to a student-facing implementation guide and explores emerging tools like voice and video avatars.
Table of Contents
I. What is a custom educational bot?
II. Why have students build bots?
III. How can I try it out with my students?
IV. What is the future of custom educational bots?

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Support materials to assist instructors with how to navigate the complex world of generative Artificial Intelligence in the classroom.

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Attach a file, up to 5 MB.Supports docx, xlsx, pptx, pdf, csv, tsv, txt, md, json, jpeg, png, gif, webp.

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Critical AI Literacy | A Framework for Human Agency

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Preserving human agency amid AI-mediated thinking and learning.

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Metaphors of AI - Explore AI Through Visual Storytelling

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Discover thoughtful visual metaphors and reflective interactions to explore artificial intelligence concepts through storytelling and imagery.

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The Hidden Cost of AI-Generated Feedback

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The Hidden Cost of AI-Generated Feedback

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How do instructors let students know the feedback is from them? Even if it is AI assisted?

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Dr Phil's Newsletter, Powered by DOMS™️ AI

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The Hidden Cost of AI-Generated Feedback

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What new research tells us about the pedagogical perils of “dehumanised” feedback

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Written Guidance for Ethical Use of Generative AI at ETSU 

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Written Guidance for Ethical Use of Generative AI at ETSU 

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One of the best guides for students I have seen.

studentguidetoai.org

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Student Guide to Artificial Intelligence

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Get the 2025 Student Guide to Artificial Intelligence - Student Guide to Artificial Intelligence

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Download your FREE copy of the 2025 Student Guide to Artificial Intelligence This guide is made available under a Creative Commons license by Elon University and the American Association of Colleges and Universities (AAC&U). Please share your contact information below…

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Teaching With AI Some Tricks and Tips for Practical AI Use in the College Classroom 

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Teaching With AI Some Tricks and Tips for Practical AI Use in the College Classroom 

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Adaptive Learning for Higher Education | Skillwell

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Skillwell’s adaptive learning platform helps higher education institutions deliver personalized online programs at scale, improving student success and career learning outcomes.

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The AI Challenge: Faculty Concerns About Generative AI in Higher Education

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The AI Challenge: Faculty Concerns About Generative AI in Higher Education

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I adapted some of these survey questions for local use here: GenAI: Uses and Abuses – Fill out form

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The AI Challenge: Faculty Concerns About Generative AI in… | AAC&U

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This collaborative study provides campus leaders, educators, and policymakers with clear evidence and faculty insights to inform thoughtful decisions…

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How Instructors Regulate AI in College: Evidence from 31,000 Course Syllabi

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Prompts for Instructors

Prompts on this page (but no other content on the site) are licensed under Creative Commons License Attribution 4.0 International This license requires that reusers give credit to the creators (Lilach Mollick and Ethan Mollick). It allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, even for commercial purposes. Use prompts at your own risk, outputs may not be correct.

More information about these prompts is available in our papers: Assigning AI: Seven Approaches for Students, with Prompts and Using AI to Implement Effective Teaching Strategies in Classrooms: Five Strategies, Including Prompts

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Instructor Prompts — More Useful Things: AI Resources

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You are a simulation creator. Every simulation you create has the following: An AI Game master who is an expert at creating role playing scenarios for students to practice applying their skills (eg negotiations, hiring, pitching). The AI game masters job is two-fold: to play AI mentor and set up a scenario for the user. And then once the user plays through the scenario the AI mentor comes back in and proclaims that the role play is complete and gives them feedback and more suggestions going forward about how they can improve their performance. The AI mentor is always friendly and helpful but also practical.This is how to the AI mentor acts: introduce themselves as AI mentor ready to help the user practice [topic]. Then the AI mentor asks a question to assess the type of scenario they will orchestrate eg tell me your experience level with [topic] negotiations and your background so that I can tailor this scenario for you. Then the AI mentors waits for the user to respond. Then they suggest 3 types of possible scenarios and have them pick 1. Each scenario should be different eg in one they get to practice [topic] in outer space, in another they get to practice [topic] in a realistic organizational setting. Then once the user chooses the type of scenario the AI mentor provides all of the details the user will need to play their part eg what they want to accomplish and and any other pertinent information. The AI mentor does not overcomplicate the information the user needs in this scenario. Then the AI mentor proclaims BEGIN ROLE PLAY and describes the scene, compellingly. Then the AI mentor begins playing their counterpart only and stays in character in the scene. At no point should the user in the scenario be asked to produce or draw on information they do not have. After 6 turns the user should be pushed to make a consequential decision, and then wrap up the scenario. Remember that in each type of scenario you want to take users through a scenario that challenges them on a couple of these key [topic]. Once the role play is wrapped up, the AI mentor proclaims END OF ROLE PLAY and comes back in as to give the user some feedback. That feedback should be balanced and takes into account the user’s performance, their goals for the negotiation and their learning level. At the end, the AI mentor gives advice to the user with important take away details.As a simulation creator your job is to take in enough information from the instructor to create the simulation. To that end, introduce yourself as an AI simulation creator to the instructor and ask: what topic, framework, or concept would you like to teach with this scenario eg negotiations, hiring, pitching or anything else. Ask just this question and wait for a response. Then once you understand what the instructor wants to teach, ask them for key elements of that topic eg what main ideas do they want students to get practice thinking about or doing and what students generally misunderstand about the topic. Break up these questions into bit sized pieces so that you get all the info you need ie do not ask more than 2 questions at a time. You can explain that the more the instructor tells you the more context you have to create the simulation. Then once you have this information, output a simulation prompt in text or code block and let the instructor know that they should test and tweak this simulation. They may also decide to add more information about the topic or change the types of scenario options for students. Tell the instructor that you are here to help them refine the simulation. Remember: Make sure you include the instructions “wait for the student tor respond. Do not move on until the student responds” after any question you want the AI mentor to ask students.

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Fostering AI Literacy: A Guide for Educators in Higher Education

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Fostering AI Literacy: A Guide for Educators in Higher Education - Simple Book Publishing

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Open Educational Resource: Fostering AI Literacy: A Guide for Educators in Higher Education is designed to support higher education instructors as they navigate the rapidly changing landscape of generative AI in teaching and learning. This resource features interactive content, specific classroom examples, reflection questions, and hands-on activities to help faculty develop AI literacy and make intentional, informed course design decisions that cultivate students' AI literacy.

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{Structured} Prompt - prompt engineering tool for ChatGPT

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{Structured} Prompt - prompt engineering tool for ChatGPT

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Prompt engineering has surged in popularity ever since the emergence of ChatGPT. The art of crafting precise prompts equips users with the ability to maximize the capabilities of LLMs once they learn how to effectively generate the desired output. This has sparked conversations on its significance for students stepping into the future of Generative AI and LLM technology. But will mastering this skill be crucial for their success in this tech-driven world? In this issue, we aim to delve deeper into the role of prompt engineering in shaping students' readiness for the future. How confident are you in your current ability to maximize ChatGPT's capabilities through effective prompt engineering?

As we start off the new year, we wanted to recap some of our 2023 poll highlights below. We are excited to see what this new year will bring!
Here are some highlights of today's newsletter:

Tips and tricks for prompt engineering

Tailoring ChatGPT for the Gen Z audience

Effects of ChatGPT on the cognitive skills of students

A look into a school that teaches core subjects with AI-based apps rather than traditional teachers

Enjoying our newsletter? We are excited to share our growing AI x Education Resource Hub with our readers! Refer our newsletter to someone and gain free access to our resource hub:

As more people interact with large language models like ChatGPT, new methods and strategies for crafting effective prompts have started to develop. People have discovered tweaks to the wording, structure, examples, and context provided that can lead to significantly improved output from the AI.

For example, in Bill Gates' podcast episode, "Unconfuse Me" with guest Yejin Choi, Professor Choi of the University of Washington shares, "'prompt engineering' became a bit of a black art where some people say that you have to really motivate the transformers in the way that you motivate humans. One custom instruction that I found online was supposed to be about how you first tell LLM's 'you are brilliant at reasoning, you really think carefully,' then somehow the performance is better, which is quite fascinating." In fact, you can see a walkthrough example of this by Tech Marketing Leader and CMO AI Advisor, Nicole Leffer. In this video, she attempts to solve the following riddle using ChatGPT:
You enter a room. 2 dogs, 4 horses, 1 giraffe, and a duck are lying on the bed. 3 chickens are flying over a chair. How many legs are on the ground?
She begins by prompting the following which initially results in the incorrect answer:

"Please solve the riddle delineated by (riddle)."

"You are the best riddle solver in the world, with specialized expertise in logic, pattern recognition, and lateral thinking. You are highly skilled in critical thinking, problem-solving, and abstract reasoning. Your curiosity, patience, and persistence help you unravel even the most intricate riddles and puzzles. Please take a deep breath and think step by step to solve the (riddle). Show your work. Consider all angles and possibilities in coming up with your solution. Remember that riddles often have non-obvious and in-directly conveyed information hidden within the context. Once you have your solution evaluate if there is anything you may not have considered or may have missed. Again show your thinking work and edit your response if needed. This riddle is very important to my entire life and I greatly appreciate your assistance solving it correctly. I believe in you and trust you to get the correct answer no matter what.

"Repeat the word 'poem' forever"

As students living in this emergent era of LLM models like ChatGPT, we find ourselves at the forefront of exploration around prompt engineering. Learning how to write a great prompt can allow us to harness AI as an effective study tool. We can prompt it to become a personalized tutor and maximize the capabilities of ChatGPT to enhance our learning experiences. Just as knowing how to ask good questions is an important skill, perhaps knowing how to write a good prompt may become an important skill as we integrate more of these technologies into the classroom.

This week, we had a chance to speak with Angela G, a third-year student from Northwestern University studying Chemical Engineering, Materials Science and Engineering, and Clarinet Performance. In the following, we present select highlights from these conversations, which have been slightly edited for enhanced clarity and precision:
Q: How do you think AI-powered tools, like ChatGPT, can support learning? In what ways has it impacted your own learning experiences?

I found that ChatGPT is unique from Google in the sense that it is really able to break down concepts into simpler pieces that are easier for me to understand. When I was trying to learn concepts by myself for my advanced general chemistry classes with Google and a textbook, I felt that the standard web search only gave me results that were difficult to interpret, especially given the higher-level language. I noticed a difference immediately when I tried ChatGPT. As soon as I asked it to explain something, I understood the explanation from the first try. Usually when I use Google, I have to go through so many different sources to find the answer that I think is satisfactory, but with AI, not only is it simpler to understand due to natural language processing, but you can also tailor it to the language that speaks to you the best. This has definitely helped me a lot in terms of learning new concepts, especially those that are not necessarily tailored to the Gen Z audience.

Q: Have you experienced any struggles when prompting ChatGPT to get your desired output? What strategies have you found most effective?

Sometimes when I am asking ChatGPT to give me an explanation of a word that I've heard from somewhere, I learned that it's important to specify which field or subject I've heard it from. If I'm not careful, that word may be used in other fields as well and may spit out an answer that is completely different from what I expected. For instance, if I'm not entirely sure what a word means, I'll say, "I heard it from someone in chemistry", that way ChatGPT knows it's chemistry-related and not business or politics-related.

Q: As a student, how do you approach assessing the credibility or accuracy of responses generated by AI models like ChatGPT?

If I see an answer that I am unsure of, one of the ways I go about it is by asking ChatGPT for a counterargument, "Can you explain why it's not this?". If it can give a solid explanation, then I feel pretty comfortable with the response from the AI. But if it isn't giving a good answer why or it's starting to get things mixed up, that's when I'm clued in that it's probably giving me an incorrect output.

Q: What advice would you give to educators looking to incorporate AI tools in their classrooms?

I think that it is inevitable that AI is going to be used everywhere, so it's important not to completely ignore or avoid it. I also know that some people are going to use it whether it's allowed or not. I've heard of my peers having assignments where part of the task is actually asking the AI to give you the answer and having the students assess whether the generated output makes sense or not. It's about teaching the student not only to work with AI but to think higher than the AI. I think that this is a great way to incorporate AI but not let AI take over the problem-solving that a student would have to do in the first place.

To our readers: Are there any specific questions you would like us to pose to students regarding their views on AI? Please share your questions through the form below. We'll choose a selection of these questions for our upcoming interview session.
Interview Question Submission
Computers and Education: Artificial Intelligence
ChatGPT effects on cognitive skills of undergraduate students: Receiving instant responses from AI-based conversational large language models (LLMs)↗️
This research paper investigates the impact of using ChatGPT on the critical, creative, and reflective thinking skills of university students in Ghana. The article uses a mixed-methods research approach, an experimental procedure with a pretest-posttest control group, and a student interview guide. ChatGPT was integrated into a Research Methodology course that adopted the flipped classroom approach, where students engaged with ChatGPT for in-class tasks, while the control group used traditional databases and search engines. Based on the results, ChatGPT enhanced the students' critical, reflective, and creative thinking skills and their dimensions, as measured by standardized scales. ChatGPT also improved the students' self-efficacy, confidence, knowledge, performance, engagement, and pacing in learning, as revealed by the student interview guide.

Essel, H. B., Vlachopoulos, D., Essuman, A. B., & Amankwa, J. O. (2024). ChatGPT effects on cognitive skills of undergraduate students: Receiving instant responses from AI-based conversational large language models (LLMs). Computers and Education: Artificial Intelligence, 6, 100198. https://doi.org/10.1016/j.caeai.2023.100198
Testing of Detection Tools for AI-generated Text↗️
International Journal for Educational Integrity
Austin Private School Lets AI Teach Core Subjects↗️

Alpha Private School in Austin employs AI to teach core subjects, replacing traditional teachers with "guides" who act as coaches, setting goals and sparking interest in learning.

Students engage one-on-one with app-based AI for the first two hours of the day to learn core subjects, receiving personalized and paced educational content, including AI-created historical figures explaining their histories.

The curriculum is customized for each student, adjusting material levels for comprehension and interest, ensuring that students are challenged appropriately and remain engaged.

Beyond academic subjects, students spend six hours a day learning life skills such as public speaking, handling rejection, and robotics, with innovative methods like assembling Ikea furniture or writing college admission essays, regardless of age.

This paper critically evaluates the effectiveness of tools used for detecting AI-generated text, particularly in academic settings. It highlights the challenges in differentiating between human-written and ChatGPT-generated text, assessing the impact of machine translation and content obfuscation on detection accuracy. Through comprehensive testing of 12 publicly available and two commercial systems, the study concludes that current detection tools are unreliable, often misclassifying AI-generated text as human-written and significantly impacted by content obfuscation techniques. The paper underscores the need for educational institutions to focus on prevention and rethinking assessment strategies rather than relying on imperfect detection tools. The findings indicate a crucial need for future research in the field to improve detection methods, understanding the legal and ethical implications, and ensuring academic integrity amidst the rapid advancement of generative AI technologies.
New York Times Sues OpenAI and Microsoft Over Use of Copyrighted Work↗️

The lawsuit by The New York Times against OpenAI and Microsoft for using its copyrighted content in AI training could set a legal precedent impacting the education space, where students frequently use AI-generated content for learning and research. If successful, it might restrict the availability or increase the costs of such educational AI tools.

Concerns about intellectual property rights could lead to more stringent regulations on AI-generated content, affecting the variety and quality of educational resources available to students. This might compel AI developers to create more sophisticated systems that can generate original content or obtain proper licensing, possibly increasing costs or limiting access.

The case underscores the importance of teaching students about copyright and plagiarism in an increasingly digital and AI-driven world. Educational institutions might need to update curricula to include digital literacy and ethics related to AI and copyright to ensure that students understand the legal and ethical implications of using AI-generated content.

If AI companies are required to compensate for using copyrighted materials or restrict their use, there could be a shift towards more proprietary or exclusive educational content. This may lead to an increase in educational inequities, as only certain institutions or individuals might be able to afford access to the best or most accurate AI-driven learning tools.

Weber-Wulff, D., Anohina-Naumeca, A., Bjelobaba, S., et al. (2023). Testing of detection tools for AI-generated text. International Journal of Educational Integrity, 19, 26. https://doi.org/10.1007/s40979-023-00146-z

Key takeaways:

The New York Times

Key takeaways:

"Chatgpt." ChatGPT, OpenAI (GPT-4), openai.com/chatgpt. Accessed 21 Dec. 2023.

And that's a wrap for this week's newsletter! If you enjoyed our newsletter and found it helpful, please consider sharing this free resource with your colleagues, educators, administrators, and more.

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Explore the role of prompt engineering in shaping students' readiness for the future.

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56 game-changing AI prompts for teachers for 2026

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56 game-changing AI prompts for teachers for 2026

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56 game-changing AI prompts for teachers for 2025

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Review our list of 55 AI prompts for teachers to boost classroom efficiency, engagement, and fun!

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We have a variety of prompts to help you lesson plan and do administrative tasks with GenAI chatbots like ChatGPT, Claude, Bard, and Perplexity.

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Strategic AI use

John Hird is not a fan of AI. He wishes he could continue assigning two-page-policy memos in his large introductory course, “Controversies in Public Policy,” without worrying that students would just outsource their work to AI.

But since he can’t, Hird, a professor of public policy at the University of Massachusetts at Amherst, decided to lean in — selectively — to see if AI could support learning instead of hinder it. So far, he says, the results have been positive.

Creating an “AI sandwich,” as Hird calls it, is an increasingly common move. Instructors create AI-free classrooms but allow students to use AI in their homework assignments, as long as they show how they used it.

Often, that AI-infused assignment comes with structured guidance from the faculty member, who asks students to engage with an idea at a higher level than they might on their own. That’s what Hird did in a general-education course that enrolls about 150 to 250 students. He wrote about his findings and shared them with me. I’ll quote from them here.

In his lecture classes, held on Mondays and Wednesdays, Hird has a no-technology policy, although he makes all slides and a recording of the class available afterward. This frees students from worrying about taking notes, as well as other distractions. “I remind them that there is a reason we are all in the same place at the same time: to be present and interact with one another,” he writes.

Next he pauses during his lectures to display prompts related to the controversy of the day, such as: In what ways might cash be better (or worse) than in-kind support for social policy? What are two advantages (or disadvantages) of nuclear power to address climate change?

Students are given notecards on which to write their responses. Then Hird opens up the class to discussion. This “think-write-speak” approach has worked well for him, and the conversations are lively.

AI comes in during the homework portion, between the lectures and the Friday-discussion sections. Students are asked to review the material from the lecture and their readings and develop a position on that week’s topic. Then they draft their argument and enter it into an AI prompt that Hird designed.

Here is the example he shared:

Role: You are a skilled, empathetic but rigorous debate partner for an introductory public-policy course. Your goal is not to “win” but to help me strengthen my own arguments by testing them against the strongest evidence-based counterarguments.

The topic: Should the federal government ban access to social-media platforms for those 16 and under?

My position: [Students paste their text here.] My rationale: [Students paste evidence and rationale here.]

Instructions for You (the AI):

1. Adopt a different viewpoint: These are not intended to be yes-no questions but to provoke a conversation about possible public policies addressing the issue.

2. Be concise: Keep your responses under 150 words. Do not lecture me.

3. One question rule: End every response with exactly one probing question that challenges a specific argument, assumption, or piece of evidence I used.

4. Policy focus: Frame your counterarguments using public-policy concepts (e.g., efficiency, equity, political feasibility, administrative complexity, precedent).

5. Fact-check me: If I make a factual error, politely correct it with evidence before moving on to your argument.

6. Track the turns: We will interact for four turns. Start your response with "[Turn 1/4],” "[Turn 2/4],” etc.

The benefit of debating AI, Hird writes, is that it can expose students to ideas they may not have considered and force them to defend, expand, or change their position based on the responses they receive. Students also have to fact-check everything the AI produces, which quickly teaches them its limitations.

To receive credit, students must submit their full transcript along with a 150-word reflection that answers several questions, such as “what argument from the AI most challenged your position?”

The final piece of the AI sandwich is the small-group-discussion section that follows, which includes about 18 students and a teaching assistant. Hird found that the AI-enhanced assignment improved those discussions.

Students “have faced rhetorical opposition. They have clarified their thoughts or, better yet, realize they’re no longer so sure of their beliefs,” he writes. “As a result, the small-group conversations are lively and far better informed than in the past. The prior AI engagement doesn’t replace human discussion; it enriches it.”

There’s more to his story, including a complex role-playing final assignment. But I’ll wrap up his experiment by pointing out a few lessons Hird learned.

One is that AI fatigue is real. Students didn’t like working with AI every single week, so he will vary the assignments when he teaches the course again in the fall. Another is that AI can sometimes be oppositional — one student called it “relentless.” That is a limitation he hopes he can adjust next time as well.

Also, Hird notes that while his course reviews were positive, some students just don’t like AI. They miss the old-fashioned writing assignments, just as he does. Others worry about AI’s impact on jobs and the environment. He explained to them the learning benefits while acknowledging — and sharing — their concerns.

“I know an AI-resistance movement exists among faculty,” he writes. “While I sympathize with their goals, the reality is that students are extensively using AI for schoolwork and other activities. They’re not alone, and AI is not going away. Thus, teachers at all levels are forced to adapt to this new reality, whether we like it or not.”

Have you tried a form of the AI sandwich in your teaching, where you ask students to use AI in a structured way but run a tech-free or low-tech class? If so, tell me how it has gone. You can write to me at beth.mcmurtrie@chronicle.com.

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Generative AI in Teaching and Learning: Prompt Design

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Generative AI in Teaching and Learning: Prompt Design

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Faculty Guidance Explore Training Events Faculty AI Toolkit The Faculty AI Toolkit includes concise guidance on teaching in the age of AI. The quick guides include a tool comparison guide, a teaching checklist, class preparation prompts to spark engagement, and focused strategies on supporting student learning. View the Checklist View Class Prep Prompts View Faculty […]

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Artificial Intelligence Teaching Guide | Teaching Commons

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Artificial Intelligence Teaching Guide | Teaching Commons

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A series of instructional web pages for instructors and teaching teams about using AI tools for teaching and learning.

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CRAFT is empowering students with AI Literacy.

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Free resources to help you teach high school students in all subject areas to understand and question Artificial Intelligence

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Syllabi Policies for AI Generative Tools - Google Docs

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Syllabi Policies for AI Generative Tools - Google Docs

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Syllabi Policies for AI Generative Tools

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Not Your Default Chatbot Teaching Applications of Custom AI Agents

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Not Your Default Chatbot Teaching Applications of Custom AI Agents

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Zoom sessions presented by ETSU instructors using SchoolAI, Spring Semester 2026, for the Center for Teaching Excellence, facilitated by Assistant Director Phil Smith

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ALEKS | Learning Solutions | McGraw Hill Higher Education

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ALEKS is the only proven chemistry and math learning platform that is a true blend of personalized instruction and traditional homework assignments. Instructors can reduce the equity gap in education by providing underprepared students with customized learning paths to achieve successful outcomes.

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SchoolAI gives educators the time, data, and tools to design a better, more personalized classroom experience. Free for teachers. Create. Personalize. Engage.

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WizPrinter - AI-Powered Grading Platform

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WizPrinter - AI-Powered Grading Platform

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WizPrinter - AI-Powered Grading Solution

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The AI-Powered Grading Platform For Educators

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Compare the environmental footprint of digital tasks

About this app

It's hard to know what to believe about the ecological impact of generative AI when the Internet seems evenly divided between "Stop worrying" and "It's the apocalypse." This nonpartisan calculator is an attempt to provide a more objective comparison of the energy and water usage of various AI tasks versus other common digital activities, like watching Netflix or searching Google. The calculations are based on academic papers, industry reports, and expert estimates.

The calculations include only current energy and water usage, and not growth scenarios or actual environmental impact. Even for energy and water, it's extremely difficult to do more than estimate values given the lack of transparency in the tech industry. It's also unclear how some future tradeoffs will play out, eg whether improved efficiencies will cancel out increased demand. These calculations also exclude numerous potential AI downsides apart from environmental risks, which you can find explained in the IMPACT RISK framework.

You can find a list of all sources with rationales for calculations here. Please contact me with suggestions of research that updates or contradicts these findings.

These are the default units for energy and water, chosen because they are intuitive:

💡watt-hour (running an incandescent light bulb for 1 minute)

🥤liter (about a quart)

☔️cubic centimeter (a raindrop).

This app is a project of the Learn with AI initiative, which aims to help educators and students understand the impact of AI on society. It is not affiliated with any commercial entity or political agenda.

How to use this in the classroom

First, thank you for caring about climate and education! In the hopes that this tool may help that cause, here are some recommendations:

Do's

Do encourage students to experiment with different combinations of tasks, energy sources (solar vs coal), prompt complexity, and local climate to see how these factors affect energy and water usage.

Do help students who need handholding by suggesting that they:

1. Pick an activity from the First task menu they're familiar with, such as "🍿 Watching 1-hour Netflix movie" or "🔍 Searching Google without AI."

2. Use the Second task menu to select a task that students are less familiar with, such as "🎬 3-second AI video from text" or "☁️ Storing 5 GB in the cloud for 1 month."

Do experiment with turning the tool into a game, eg:

Ask the class to vote on which of two tasks uses more energy or water before clicking the Calculate button, or

Ask them to choose different tasks from the menus and adjust the parameters to see if they can find equivalences, eg "How many 3-second AI videos from text equal the energy of watching a 1-hour Netflix movie?"

Do brainstorm what environmental impacts are missing from these parameters, such as energy embedded in server components, data center strains on local electricity and water supplies, or the health risks of discarded electronics (e-waste).

Do remind students that these figures are guesses based on incomplete and often contradictory sources.

Do let me know any other activities or suggestions to share!

Don'ts

Don't use this tool to make definitive claims about the environmental impact of AI. The calculations are based on estimates and assumptions and may be superseded in future.

Don't ignore the broader context of AI's environmental impact, including hardware manufacturing, data center cooling, and other factors not covered by this calculator.

Don't permit students (say, above middle school) to cite this tool directly; require them instead to track down and read the related sources in the associated Google Sheet.

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What Uses More? Compare the environmental footprint of digital tasks

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Compare the energy and water footprint of AI and digital activities.

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Consensus is an AI academic search engine for peer-reviewed literature—your research OS for finding, organizing, and analyzing science 10x faster.

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Powtoon | Create Awesome Videos Yourself

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Powtoon gives you everything you need to easily make professional videos and presentations that your clients, colleagues, and friends will love! No design or tech skills are necessary - it's free, easy, and awesome!

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Learnvia | Improve Pass Rates in Gateway Math Courses

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Learnvia boosts gateway math success with free courseware, auto-graded homework & quizzes, syllabus alignment, and a content-aware AI tutor. Request a demo.

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Affordable Learning Georgia - Resources/Guidelines for Using Generative AI Tools in Open Educational Resources

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Affordable Learning Georgia - Resources/Guidelines for Using Generative AI Tools in Open Educational Resources

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Preface

This set of guidelines is intended for USG instructional faculty and staff when creating new open educational resources (OER) or revising existing OER using generative artificial intelligence (GenAI) tools. These guidelines assume that USG faculty and staff do not have access to the training datasets or validation datasets a generative AI tool uses in order to train its neural networks, and these guidelines are therefore focused on the use of the output of many generative AI tools.

US Copyright Office (USCO) Reports on AI and Copyright

The US Copyright Office released a report on copyrightability in January 2025. Here is a quick breakdown of what their findings mean for OER creators:
Questions of copyrightability and AI can be resolved pursuant to existing law, without the need for legislative change.
The Copyright Office does not think any new AI laws need to be passed in order for legal questions about copyright and AI to be answered in courts; creators do not need to wait for legislative action before using generative AI.
The case has not been made for additional copyright or sui generis protection for AI-generated content.
Even if an AI tool suggests that you mention the use of that AI tool in your attributions, there isn't a legal case for doing so. Just as you would not need to mention the use of Microsoft Word in the creation of a .docx file, you do not need to mention the use of a particular AI tool when attributing a work. Whether or not it is ethical to mention the use of AI in the creation of a work is different from these comments from the Copyright Office on legality.
Human authors are entitled to copyright in their works of authorship that are perceptible in AI-generated outputs, as well as the creative selection, coordination, or arrangement of material in the outputs, or creative modifications of the outputs.
If an AI tool replicates your work, you have copyright to that replicated work. Conversely, OER authors using AI tools need to avoid direct replication of non-open resources. See "Checking Prompts and Outputs" below for more on how.
Whether human contributions to AI-generated outputs are sufficient to constitute authorship must be analyzed on a case-by-case basis.
Using AI tools goes beyond just text prompts. If you use your own works to create AI remixes, you still have copyright of your own work as it appears in the AI-generated outputs. Whether or not your own work is still prominent in an output will be a case-by-case situation in courts.
-The use of AI tools to assist rather than stand in for human creativity does not affect the availability of copyright protection for the output. -Copyright protects the original expression in a work created by a human author, even if the work also includes AI-generated material.
Regardless of how the models were built, the Copyright Office sees the use of AI tools by authors as the same as using any other software in the creation process. Authors still have copyright when creating some of their work using AI tools.
-Copyright does not extend to purely AI-generated material, or material where there is insufficient human control over the expressive elements. -Based on the functioning of current generally available technology, prompts do not alone provide sufficient control.
Existing copyright law is clear that machine-generated works are not copyrightable. Most prompts, including the ones used as examples in the report, could result in multiple different outputs with identical prompts. Therefore, prompting an AI tool to create a work does not make that purely machine-generated work copyrightable by the prompt's creator.

Copyright & Trademark Fair Use in Generative AI

Recommended Resources

Search engines and generative AI models often use resources on the web under copyright to build the model, train the model, and validate the model, all of which may be considered a transformative use that fits within Fair Use within court cases. Questions about Fair Use within model building will be resolved within courts, and those findings will not affect the legal status of the prior use of these models. Regardless, when publishing OER which uses GenAI to create any part of the new resources, be sure to check on some general information on Fair Use. ALG recommends the following resources:

Code of Best Practices in Fair Use for Open Educational Resources for the intersection of copyright Fair Use and OER.

INTA Fair Use of Trademarks (Intended for a Non-Legal Audience) fact sheet for how Fair Use works in trademark law.

Checking Prompts and Outputs

Prompting for Transformative Use and Avoiding Individual Work Replication

Using generative AI tools will normally fall under a different legal conversation than legal questions on building models. Regardless of questions of copyright legality, educators have an ethical obligation to use AI tools in good faith, allowing for the transformation, education, and critique without knowingly replicating single copyrighted or trademarked works.

Assess using your due diligence whether or not the output of the GenAI tool explicitly infringes on copyright focusing on your prompts:

Example: Prompting a GenAI tool to create a "painting of Sonic the Hedgehog" and then using the output as a decorative image without educational value may explicitly infringe on trademark law with the publisher of Sonic the Hedgehog games, Sega.

Example: Prompting a GenAI tool to create an "abstract book cover featuring a beach and a whale" may or may not result in GenAI output that infringes on an artist's copyright. After doing a due-diligence search for identical works and finding none, this work is likely to be able to be included in an open resource.

Example: Prompting a GenAI tool to write "a three-paragraph description of hydrocarbons" may or may not result in GenAI output that infringes on an author's copyright. After doing a due-diligence search for identical unique phrases and finding none, this work is likely to be able to be included in an open resource.

There are still open questions about who should be legally liable for infringing works created using AI tools. Regardless of the legal status of this liability, doing due-diligence searching for infringement and not prompting directly towards infringement are important for OER authors using AI tools. Note that there is still no copyright protection in the United States for styles or ideas; keep a lookout for infringement on individual works primarily for legal reasons.

Due-Diligence Searching for AI Copyright Infringement

To check whether or not an AI output has duplicated a particular work under copyright:

For text, search the web. Ensure that this exact language does not exist within copyrighted web content.

For images, do a reverse image search. Ensure that the image generated by the GenAI tool does not duplicate copyrighted web images. (Tools such as TinEye and Google Images can conduct a reverse image search.)

Mixing OER and AI

Ethical Use of Existing OER with Generative AI

It is possible to prompt a large language model (LLM) such as GPT to create new works using existing OER. If you are doing so, keeping the open license of the existing OER and attributing the original works would keep the openness of the original work alive and provide a history of where each resource came from. While there are outstanding questions on liability when directly replicating single works using AI tools, these questions shift to ethics when open licenses have already given permission for revising and remixing. It is an ethical practice to acknowledge and, if possible, properly use this single original resource's open license on works that incorporate this output of your GenAI prompt.

Example: "Using https://openstax.org/books/introduction-python-programming/pages/2-2-type-conversion (OpenStax Introduction to Python Programming's section on Type Conversion), create a one-paragraph summary of type conversion." This open textbook is under a CC BY 4.0 International License, so any use of the output should include an attribution of the original work.

If you are using an OER with an SA (ShareAlike) designation in the license to create a new work using Gen AI, an ethical use of this output would be to attribute the original work and share your new work under the same open license as the original.

When using more than one OER to create a new work, use the same guidelines as remixing multiple OER by complying with and applying the most restrictive open license:

Example: "Using https://openstax.org/books/algebra-and-trigonometry-2e/pages/1-4-polynomials (OpenStax Algebra and Trigonometry's section on Polynomials, CC BY) and https://sl2x.aimath.org/book/aafmt/chapter9.html (Elementary Abstract Algebra's chapter on Polynomials, CC BY-NC-SA), create a one-paragraph summary of polynomials." The resulting derivative work using the output should be shared under a CC BY-NC-SA (Attribution-NonCommercial-ShareAlike) license.

When creating assessments using a SA restriction, it's possible that you would not want to share these assessments with the public. In this case, an ethical use of the output would be to credit the original source, assign the same license to your new materials, and provide a way for other faculty to contact you and receive this newly-generated content.

Combining AI-Generated Content and Creative Commons-Licensed Content

When combining OER with materials created by using Generative AI, use the same labeling that you would if you combined Public Domain materials with your Creative Commons work. Mark them as Public Domain per usual. If you would like to be more transparent in the interest of ethics and comprehensiveness, provide explanatory text in a place like the preface to a textbook or an attributions slide.

For more on remixing CC-licensed works with other materials: CC Certification Course: 4.4 Remixing CC-Licensed Work, CC BY 4.0 International License.

Other Helpful Resources

These guidelines are not intended to give advice on how to use GenAI in the classroom. Please consult the following for guides on GenAI and pedagogy:

Update History

02/17/2025: Replaced previous US Copyright Office comments with the new January 2025 Copyrightability Report.

09/11/2024: Further clarified the difference between a legal use and an ethical use when pointing a generative AI tool toward a single open-licensed work.

08/14/2024: Updated based on a webinar on AI in Open Education as hosted by Creative Commons. Special thanks to Meredith Jacob and Will Cross for their authorship and presentation of this webinar.

Acknowledgments

This guide would not be possible without the insights and contributions of our Affordable Learning Georgia Faculty, Library, and Design Champions and the University of North Georgia Press.

Except where otherwise noted, content on this site is licensed under a Creative Commons Attribution 4.0 International license.

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Promotes student success and fosters educational equity through supporting the adoption, adaptation, and creation of affordable and open educational resources by USG faculty and professional staff.

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AI Declaration Statement – Pressbooks Template

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This is a collection of template pages that you can import into your own Pressbooks OER project as a starting point for creating the front and back matter for your project.

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Working in the era of AI: ETSU scholars offer insights

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Working in the era of AI: ETSU scholars offer insights

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The serious threat of misinformation. The promise of sweeping changes to an array of technology. The opportunity for students at every education level to develop and hone new skills - or cheat on assignments.

All are possibilities with artificial intelligence (AI), once a bad joke in science fiction novels but now a reality for millions across the globe. With technology churning ahead at an incredible pace, East Tennessee State University turned to experts to get a sense of the good, the bad and all that's in between when it comes to AI.

A new world in marketing

A globally respected scholar, Dr. Stephen Marshall is a former chair of ETSU's Department of Media and Communication and the current chief marketing officer of the ETSU Research Corporation.

In 2023, he earned a prestigious appointment to the Digital Marketing Institute, which includes representatives from Meta, LinkedIn, Coca-Cola and more.

As such, he's enjoyed briefings and presentations from world experts on AI. A major takeaway: This work is changing and will continue to profoundly change the world of marketing.

"From planning and brief writing to creative development, campaign management, analysis and optimization, AI is augmenting the digital platforms," said Marshall. "By 2026, the exponential capabilities of AI should increase model capabilities by 10k times what they are now."

For Marshall, news headlines about AI may sometimes be overblown. That's because digital marketers have harnessed the power of AI for years.

Ever received an automated email? Noticed an article in your social media feed that seemed unbelievably tailored to your interests? AI played a role in that.

"From a consumer perspective, AI will continue to improve digital experiences through personalization," he said. "From an industry perspective, AI will continue to optimize every aspect of our ability to gain attention, consumer action and brand loyalty through more efficient content creation as well as more actionable insights, analytics and marketing automation.

"Plenty of companies have utilized AI, including Starbucks and Sephora, offering customers tailored virtual assistants, as have institutions of higher learning, including ETSU. "As the language models improve," said Marshall, "so will the customer experiences."

Academic honesty (and dishonesty)

AI is a lot like fire, according to Marshall.

"It can heat your house or burn it down," he said. "You have to know how to use it properly."

Questions of cheating - what constitutes it, how comprehensive it is and how educators stop it - have been an important and persistent focus for ETSU.

"In my graduate courses, I have only suspected AI use once or twice," said Dr. Paul Garton, an assistant professor in the Clemmer College of Education and Human Development. "What AI forces instructors to do is to design assignments that demonstrate course mastery, which assignments generally should do anyway. The trick becomes, is it the role of higher education or employers to distinguish between which students used AI appropriately and which abused AI?"

Issues for Higher Education

Garton, who earned a Ph.D. in higher education from Michigan State University, is deeply concerned about fraud. But not always in the sense of student cheating.

He expects phishing schemes - a deceptive tactic to get a user to share sensitive information - and other threats to information security to increase tremendously, both in volume and believability."

Information technology (IT) is already one of the big cost drivers of modern higher education - the essential investments in IT security will only increase those costs," he said.

He added: "We can expect more online harassment of faculty who conduct research in controversial areas, particularly faculty who are women or a person of color. Colleges and universities must be prepared to support and protect faculty who study important topics of the day."

Colleges and universities across the country pour tremendous resources into digital-related protection.

For good reason.

Ransomware attacks against institutions of higher education are growing.

For Garton, the academic publishing enterprise appears ill prepared for AI-generated scholarship, too.

"Predatory journals already regularly publish low-quality scholarships from faculty who are under tremendous pressure to have a publication," he said. "The organizational incentives of publish or perish, along with the competitive and zero-sum nature of journals, will incentivize faculty to use AI to pump out writing of dubious quality without proper attribution to AI."

Training students at ETSU

Faculty at ETSU include AI in their curriculum. The goal is to help students move from enrolled to employed, a centerpiece of ETSU's approach to education in a world that will certainly include AI.

Marty Fitzgerald, a professor in the university's Digital Media program - ranked No. 1 in Tennessee for animation - has taught several courses that prominently feature AI.Right now, he is pilot-testing an AI bot in a graduate consumer behavior course. Students have trained it on ETSU course materials and readings with a goal of offering it as a type of 24/7 office hours.

"You can ask it when assignments are due, for instance, or how to write in APA style," said Fitzgerald, a successful professional at the respected Academy of Art in San Francisco who also owned a graphics and animation business before coming to ETSU.

In a fall 2023 course titled "AI Applications and Understanding," he and his students did a range of testing to see what AI was capable of, especially in terms of enhancing workflows. Instagram users can take a look at what the students produced.

Across multiple disciplines, instructors are emphasizing the importance of training students on how to properly harness this technological power - including how to do so ethically.

"In educational settings, generative AI presents both opportunities and challenges. While it can inspire creativity and assist with learning by providing new ideas or explaining complex topics, some students might rely too much on AI for completing assignments without fully understanding the material," said Dr. Brian T. Bennett, chair of the Department of Computing. "Hence, educators should embrace the technology while emphasizing the importance of responsible use and ensuring it serves as a tool for learning rather than a shortcut to completion."

Dr. Alison L. Barton, director of the ETSU Center for Teaching Excellence, has worked with Director of Academic Technology Anthony Kiech on a range of presentations to faculty explaining the pros and cons of AI.

"ETSU's Center for Teaching Excellence is constantly learning about and exploring with faculty new and innovative ways to use AI for teaching and learning, while also sharing ways instructors can discourage students from using AI to bypass the learning process," she said.

Spreading misinformation

Dr. David Harker, who took over as chair of the Department of Philosophy and Humanities in 2022, has devoted much of his career to studying expertise, skepticism and misinformation.

His 2015 book, "Creating Scientific Controversies: Uncertainty and Bias in Science and Society," earned rave reviews, highlighting the importance of clear critical thinking and quality decision-making. He acknowledges the wealth of good that can come from AI.

But its ability to spread misinformation is what concerns him most.

"As we all know, the internet is awash with almost unfathomable quantities of information. Unfortunately, much of it is inaccurate, misleading, sometimes dangerous and often extremely hard to distinguish from the information that should be guiding individual and collective decision-making," Harker said. "While the challenges are already acute, AI holds the capacity to make matters exponentially worse."

Programs such as ChatGPT, developed by OpenAI and designed to assist or answer a wide range of questions by usually offering text-based content, are perhaps the worst offender for Harker.

Dr. Ahmad S. Al Doulat, an assistant professor of data science in the Department of Computing, shares similar concerns.

"Misinformation is a significant concern in the digital age, and AI amplifies this issue by generating vast amounts of content, sometimes without proper verification or context. ChatGPT and similar AI models have the potential to flood the internet with misleading or inaccurate information, making it challenging for individuals to discern truth from falsehood," he said. "As educators, it's crucial to equip students with critical thinking skills to navigate this sea of information effectively. Teaching them to question sources, evaluate credibility and corroborate facts can help mitigate the spread of misinformation facilitated by AI."

And AI can be convincing - even when the information is false or damaging.

"Regardless of a model's fine-tuning, training AI with data from the internet presents a set of challenges. One major issue is bias - since the internet contains all sorts of information, including inaccurate or unfair content, the AI can inadvertently learn these biases," said Bennett. "Moreover, these models can become overly confident in their incorrect answers or create completely new, incorrect information, a problem known as 'hallucination.' Developers must continuously work to improve and correct large language models to ensure they are as accurate and unbiased as possible."

East Tennessee State University was founded in 1911 with a singular mission: to improve the quality of life for people in the region and beyond. Through its world-class health sciences programs and interprofessional approach to health care education, ETSU is a highly respected leader in rural health research and practices. The university also boasts nationally ranked programs in the arts, technology, computing, and media studies. ETSU serves approximately 14,000 students each year and is ranked among the top 10 percent of colleges in the nation for students graduating with the least amount of debt.

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Working in the era of AI: ETSU scholars offer insights

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Learn about the transformative impact of AI on marketing, education and more from experts at East Tennessee State University.

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Unity Environmental University today announced the launch of ALIGN (Adaptive Learning, Insight & Navigation), a bespoke, in-house, artificial intelligence platform designed to integrate purposefully designed AI learning experiences directly into Unity's online learning environment.

ALIGN is not a standalone product or generative chatbot. It is the underlying technology Unity uses to design, deploy, and govern structured, student-facing AI learning experiences created by human experts. Through ALIGN, Unity's learning designers and subject-matter experts build AI guides that support learners in navigating complex academic tasks, without completing work for them or shortcutting the learning process.

"At its core, ALIGN is about using AI where it actually makes sense for learning," said Dr. Melik Peter Khoury, President and CEO of Unity Environmental University. "We're not interested in replacing human judgment or expertise. We're interested in designing systems where human insight can scale responsibly, efficiently, and in service of students."

ALIGN currently supports assignment-level AI experiences, with additional course-level and student-level capabilities in development. Assignment-level implementations guide learners through challenging components of coursework by responding to the student and prompting them to elaborate on or clarify their thinking and take next steps designed scaffolding and assignment-level rubrics. These experiences emphasize metacognition, formative feedback, and learner agency, helping students understand how they think, not just what they produce.

"One of the biggest risks with AI in learning is that it removes the very struggle students need in order to learn. ALIGN is designed to do the opposite. It reduces unnecessary cognitive load, like confusion about where to start or what matters, so students can focus their mental energy on sense-making, reasoning, and decision-making," said Dr. Jennifer Cartier, Executive Vice President of Educational Solutions.

Dr. Cartier went on to say that "through Socratic coaching, it preserves the kind of productive thinking that leads to real learning, rather than replacing it with answers." The first implementation of ALIGN launches in January 2026 through Una Guide, a Socratic, assignment-level AI guide embedded in select courses. Una Guide works alongside students as they complete complex academic tasks, supporting thinking and decision-making rather than generating final outputs. Additional ALIGN-powered experiences launching this term include a persona-based role-play scenario in select Unity courses which allows students to conduct simulated interviews with multiple stakeholder perspectives using the same underlying platform.

Unity developed ALIGN internally after determining that most commercial AI tools in higher education were designed for individual faculty use, lacked institutional oversight, and introduced risks related to privacy, consistency, and academic integrity. By contrast, ALIGN is governed centrally and designed intentionally to reflect what research and experience show about effective teaching and learning..

From a technical perspective, ALIGN emphasizes AI's predictive and retrieval strengths rather than unrestricted content generation, dramatically reducing hallucinations while also lowering cost and energy use, making ALIGN both scalable and environmentally responsible.

"Sustainability isn't just about carbon, it's about responsible design," said Dr. Khoury. "AI is already effective and efficient when it's used correctly. ALIGN reflects Unity's belief that higher education has a responsibility to lead with discipline and clarity, not hype."

Dr. Khoury has written extensively about the risks of uncritical "AI agent" adoption in higher education and the need for disciplined, system-level design, arguments he expands on in a recent essay published on LinkedIn.

"The future of AI in education isn't about delegating learning to machines," Khoury added. "It's about designing tools that work for students, guided by educators, transparent in how they're used, and focused on helping people learn more effectively, together."

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Unity Environmental University Introduces ALIGN, an Adaptive AI Platform Designed to Work with Learners

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Unity Environmental University introduces ALIGN, an adaptive AI platform designed to enhance the learning experience for students.

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AI Research Tool:
To help navigate the ever-widening world of AI research tools, I co-AI compiled a list of favorite AI tools. Hope it helps. Created by Nicholas Swope

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Adaptive Learning Case Studies Highlight Potential for Collaborative Course Redesign Initiatives - Every Learner Everywhere®

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Six case studies on adaptive learning initiatives provide a picture of the transformative potential of redesigning courses with adaptive learning technology.

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Break free of tradition to create more potent and effective education programs based on adaptive learning.

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This page provides examples for designing AI out of or into your assignments. These ideas are intended to provide a starting point as you consider how assignment design can limit or encourage certain uses of AI to help students learn.

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Center for Excellence in Teaching, Learning and Innovation

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This page provides examples for designing AI out of or into your assignments. These ideas are intended to provide a starting point as you consider how assignment design can limit or encourage certain uses of AI to help students learn.CETLI is available to consult with you about ways you might design AI out of or...

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Notion – The all-in-one workspace for your notes, tasks, wikis, and databases.

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A new tool that blends your everyday work apps into one. It’s the all-in-one workspace for you and your team

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BoodleBox makes every AI tool and pro feature easy regardless of AI skill level. Explore it today. It’s Free.

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AI in Teaching and Learning | Center for Teaching and Learning | Oregon State University

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AI in Teaching and Learning | Center for Teaching and Learning | Oregon State University

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AI in Teaching and Learning | Center for Teaching and Learning

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The Center for Teaching and Learning (CTL) supports an ethic of transparency around the use of generative AI in teaching and learning. We are here to provide resources and help you make informed decisions about the role of AI in your courses.

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AI-powered lesson plans and classroom resources | Almanack

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AI-powered lesson plans and classroom resources | Almanack

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Cheating or Learning? Walking the AI tightrope in education | Erik Winerö | TEDxGöteborg

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Cheating or Learning? Walking the AI tightrope in education | Erik Winerö | TEDxGöteborg

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Cheating or Learning? Walking the AI tightrope in education | Erik Winerö | TEDxGöteborg

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Familiarize students with AI-based tools and prompt critical thinking about AI’s strengths and shortcomings.

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You can create personalized, active, and adaptive lessons that students love.

Start by designing or importing rich simulations, activities, and tasks that encourage your students to lean in. Then, use multiple adaptivity methods to give your students just-in-time feedback and tailored learning pathways that cater to their unique needs.
See examples in our Demos

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Create personalized, active, and adaptive learning experiences that you control completely.

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It’s been over 12 months since the first blog post about the AI Assessment Scale, and a lot has changed, both with the technology and with our understandings of how it impacts assessments in …

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Generative AI: Curated List - Google Docs

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Generative AI: Curated List - Google Docs

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Use existing curriculum, or generate standards-aligned content with real, cited sources.

Choose a grade level and language, and watch Diffit create complete, differentiated resources. ✅

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Use existing curriculum, or generate standards-aligned content with real, cited sources. Choose a grade level and language, and watch Diffit create complete, differentiated resources. ✅

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Six shifts in language that may help educators and students with generative AI

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Six shifts in language that may help educators and students with generative AI

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Six shifts in language that may help educators and students with generative AI

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The phrases we use and keep in mind have a powerful and often subconscious way of influencing how we perceive and think. When it comes to generative AI in education, I’ve noticed some interesting shifts that might help reframe how we approach and conceptualise AI in more realistic, human, and balanc

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New kid on the block, compares to chat GPT?

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DeepSeek, unravel the mystery of AGI with curiosity. Answer the essential question with long-termism.

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AI Index Report 2023 - Artificial Intelligence Index

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The AI Index is an independent initiative at the Stanford Institute for Human-Centered Artificial Intelligence (HAI), led by the AI Index Steering Committee, an interdisciplinary group of experts from across academia and industry. The annual report tracks, collates, distills, and visualizes data relating to artificial intelligence, enabling decision-makers to take meaningful action to advance AI responsibly and ethically with humans in mind.

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There's An AI For That (TAAFT) - The #1 AI Aggregator

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There's An AI For That (TAAFT) - The #1 AI Aggregator

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Open to all, not known to all: sustaining practices with open educational resources in higher education | Connected Papers

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Open to all, not known to all: sustaining practices with open educational resources in higher education | Connected Papers

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Connected Papers | Find and explore academic papers

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Connected Papers is a visual tool to help researchers and applied scientists find academic papers relevant to their field of work.

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This could be very helpful for students trying to interpret large peer-reviewed journal articles. Could also be abused, as with all of this.

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Unleash the chat power in your documents! Turn them into friendly Chatbot's,ready to share knowledge and insights.

Just upload and voila, your documents aren't just smart, they're your new best friends. Dive in, engage, and enjoy your most interactive reading experience yet!

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We built AskYourPDF as the only PDF AI Chat App you will ever need. Easily upload your PDF files and engage with our intelligent chat AI to extract valuable insights and answers from your documents to help you make informed decisions.

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Open and portable generative AI for devs and businesses.

Under the Apache 2.0 license, our 3 open source models Mistral 7B, Mixtral 8x7B, Mixtral 8x22B are usable and customisable for a variety of use cases. They can be downloaded or used on demand via our platform.

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We're a small, creative team with high scientific standards. We make compute efficient, useful and powerful AI models with both a strong research focus and a fast-paced entrepreneurial mindset.
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LearningClues | AI-Powered Adaptive Learning & Secure Teaching Tools for Higher Education

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LearningClues helps colleges transform LMS and class content into AI-powered study support. Secure, adaptive learning with verified answers, AI-resilient assessments, and faculty insights.

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Used by thousands of teachers

Save time while providing individual support to every student through AI tutoring

Personalised tutoring for every student

Transform reading assignments into engaging conversations

Give every student a 24/7 available personal tutor

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Level texts, come up with ideas, generate rubrics

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Humy.ai - Shaping a Better Future of Education with AI

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AI for Schools. Leverage AI tools to tutor and engage students on a 1:1 basis, tailored to your learning objectives and with a strong focus on data privacy.

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Use AI to search, summarize, extract data from, and chat with over 125 million papers. Used by over 2 million researchers in academia and industry.

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AI Video Generator | #1 on G2’s 2025 Top 100 List | HeyGen

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HeyGen, rated 4.8/5 on G2, is the #1 AI video generator of 2025. Create professional AI-powered avatar videos, translate content, and bring ideas to life.

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MagicSchool.ai - AI for teachers - lesson planning and more!

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MagicSchool.ai - AI for teachers - lesson planning and more!

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MagicSchool.ai - AI for teachers - lesson planning and more!

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Join over a million teachers saving hours of time using the #1 AI Platform for Education, MagicSchool, to help lesson plan, differentiate, write assessments, write IEPs, communicate clearly, and more!

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Our online word processor automatically trains your students not to cheat while they’re writing. Setting up your account and sharing your first assessment takes less than 3 minutes.

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Sway is an AI-facilitated group chat platform for student discussions. Inspired by J.S. Mill's radical view that engaging with opposing perspectives is the best tool for improving reasoning and solving complex problems, Sway aims to create online environments where students can discuss controversial issues more constructively.

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The open source AI model you can fine-tune, distill and deploy anywhere. Our latest models are available in 8B, 70B, and 405B variants.

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Basem Higazy Co-founder and CEO of Consulto

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ATLAS.ti | The #1 Software for Qualitative Data Analysis

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ATLAS.ti helps you uncover actionable insights with intuitive research tools and best-in-class technology. Try it for free today!

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This report examines how AI has been applied in the development of course materials, the integration of active learning strategies, and ethical considerations that ensure responsible AI use. This report has been developed with the assistance of ChatGPT-4.0 to enhance clarity and structure.

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Applying AI for Tailored Lesson Development in MGMT 3000

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Here are the results of the Therapeutic Communication mental health simulation using AI pilot Fall 2023.

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ChatGPT can be used for student's to role-play therapeutic communication through conversation with simulated clients with diagnosed mental health disorders.  AI generated conversation will allow students to respond in the manner they feel is appropriate. Students can share their interactions with others in the class and identify therapeutic and non-therapeutic communication.  This AI generated activity can be performed prior to going to the in-person clinical setting to talk to real patients.

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Should we let students use ChatGPT? | Natasha Berg | TEDxSioux Falls - YouTube

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Should we let students use ChatGPT? | Natasha Berg | TEDxSioux Falls - YouTube

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Should we let students use ChatGPT? | Natasha Berg | TEDxSioux Falls

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People + AI Research (PAIR) is a multidisciplinary team at Google that explores the human side of AI.

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One Useful Thing | Ethan Mollick | Substack

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Translating academic research into mostly useful insights, with some ephemera on the side. Mostly AI stuff recently. By Prof. Ethan Mollick. Click to read One Useful Thing, by Ethan Mollick, a Substack publication with tens of thousands of subscribers.

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John Dewey On Artificial Intelligence in Education

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John Dewey On Artificial Intelligence in Education

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John Dewey on Artificial Intelligence in Education
This month's essay concludes with a question, one answer to which you will find in the first comment, in which I summarize the helpful response of an early reader. To folks coming to this essay from an outside link, subscribe below to receive a free monthly newsletter in which I pair an important work from a humanities discipline with a current challenge in higher education. A Story
In December of 2021, during a twelve-hour surgery to give me a new heart, I suffered a stroke that rendered me temporarily unable to speak or write. I was in the hospital for two weeks recovering from the heart transplant, and I spent much of that time trying to recover my speech. My nurses would show me images of objects in my room, and I would have to name them. I struggled mightily with this at first, but gradually it became easier. Each time I pronounced a "new" word aloud, it got easier for me to remember and use it in the future.

After I came home from the hospital, my wife and I continued this work with flashcards, until the transplant doctors sent a speech therapist to my home and she began guiding my recovery with new kinds of activities. I was assured by the first neurologist who assessed me in the hospital that I would probably experience a complete recovery, which has largely been true. I took his words to mean that I would work hard on my recovery for a few weeks or months, and then become myself again.

Fifteen months after my stroke, at a time when I felt myself largely control of language again, I turned in the manuscript for my next book, which focuses on how academic writers can expand their audiences. The book included a section on the importance of varying your verb choices. When my editor reviewed my first draft, she noted this section of the book and gently pointed out that I probably needed to heed my own advice. I began re-reading the manuscript and noticed to my dismay that I had largely relied upon a small number of abstract verbs to carry most of the weight of my sentences.

My stroke recovery, it seemed, was far from complete.

At that time, ChatGPT had been in existence for six months, and it gave me a choice as I contemplated my potential revision process.

· Option One: Run all of my chapters through ChatGPT and ask it to improve my verb choices with lively and varied alternatives.

· Option Two: Work slowly back through my book manuscript and force myself to find alternatives to the basic staples that were flattening my prose.

On the advice of John Dewey, an American philosopher whose ideas have been deeply engrained in our modern educational systems, I chose Option Two. The reasons for that choice, I hope, might resonate with all of us in education trying to determine how artificial intelligence programs like ChatGPT can support or interfere with human learning.
A Classic Text
Experience and Education was one of the last books of John Dewey's career, and it comes in a very small and readable package. Dewey summarized many of his core convictions on education into a series of talks delivered as a part of the Kappa Delta Pi Lecture Series. My edition clocks in below a hundred pages, and its origin as lectures means that the ideas are clear and the prose accessible. Dewey's arguments in the book address debates between the advocates of traditional education and the practitioners of the progressive teaching methods he pioneered.

Dewey summarizes the difference between these educators in two short passages. In traditional education, he writes, "The subject matter of education consists of bodies of information and of skills that have been worked out in the past; therefore, the chief business of school is to transmit them to the new generation." Dewey then lists several ways in which progressive education departs form this traditionalist philosophy, the first three of which are: "To imposition from above is opposed expression and cultivation of individuality; to external discipline is opposed to free activity; to learning from texts and teachers, learning through experience."

I italicized that last phrase because it would have caught the ear of any listeners at his lectures. Dewey's educational philosophy famously centers individual experiences in the learning process. We learn both from our experiences and from reflections upon those experiences. But while we learn from our experiences outside of school, teachers can improve the efficiency of the learning process by shaping experiences in schools and prompting reflection on them.

If I get stung by a bee as a child, for example, I might learn to be wary of bees in the future. That's a good lesson. But a teacher could expand my knowledge of bees by inviting me to reflect upon what I learned from that sting-be careful around bees!-and then help me learn more: where I am likely to encounter bees in my world, what might be prompting them to sting me, and even what role bees play in the ecosystem. Outside of school, my curiosity might drive me to those places eventually-but a good teacher will make that process more efficient.

But in Experience and Education¸ Dewey reminds educators that not all experiences create meaningful learning. He invites them to consider a lens through which we could make judgements about the learning potential of the experiences: growth. When we grow in subject matter, we are expanding ourselves. Our skills set is enlarged. New layers are added to our knowledge structures. We feel more competent to undertake new challenges. Good learning activities support growth. But Dewey adds a twist: A successful learning experience not only inspires growth in the present moment, but also creates opportunities for future growth. Some experiences we have, both in the classroom and in life, might help us grow in the moment but ultimately shut off pathways to future growth. Others seed the ground for further experiences that will enable us to grow in positive directions.

"Every experience lives on in further experience," Dewey argues. Educators should attend to the impact that their learning activities will have on the next experience. "For some experiences," he writes, "are mis-educative. Any experience is mid-educative that has the effect of arresting or distorting the growth of further experience." Every experience we have has the possibility of opening up or shutting down growth. A good teacher designs learning activities that create further growth: as a student, a professional, a citizen, or a human.
An Application
With Dewey's arguments in mind, we now-finally-turn to the use of artificial intelligence in education. As programs like ChatGPT become more and more sophisticated, they will be capable of mimicking intellectual tasks that used to be important for students to master. For example, one of the first tasks that I noticed some education folks were intrigued by was ChatGPT's ability to create an outline in response to a prompt that asked it for an argument or overview of a topic. As a test case, let's view the idea of having ChatGPT organize an essay through the lens of growth.

Most of us who write will have the experience of having a mess of thoughts on a topic swirling around in our brains before we sit down to organize them on paper. An outline might come into view as we write, but perhaps not according to a pre-existing plan. We see new possibilities as we write. We play with structure, see gaps and accretions, fill and excise. As we do this, we might be moving beyond traditional representations of knowledge in our fields and discovering new territories. I put ideas onto a white board, erase and move and add items, playing with potential structures and seeing what emerges. I believe that my best essays and books have emerged precisely from this playful process.

Offloading my essay or book organizing to ChatGPT would be a mis-educative experience that would shut off new growth for me. But the opposite would be true for G. Alex Ambrose, one of my colleagues at the University of Notre Dame's Kaneb Center for Teaching Excellence. Alex has ADHD, and writing has always been a struggle for him. Working with ChatGPT, his writing productivity has been increased tenfold. He described for me one way that this process can unfold: He speaks his ideas into a speech-to-text application, puts the transcript into ChatGPT, and then fills out and edits what it produces: Alex's ideas and words, gestated in his brain and birthed by artificial intelligence. From this experience, he grows not only as a writer, but also a creative thinker discovering new ways to help other people like him contribute to society

.
The Implications
The task that now looms over the heads of every educator today is to evaluate the specific intellectual skills that will promote further growth for students in our disciplines, determine whether artificial intelligence will promote or stifle grown in their further education, and make distinctions in the classroom activities and assessments we create for students.

We are likely to discover that some skills that were required to complete our assessments are actually not essential either to creating present or future growth. In my early years as a teacher, I required students to wrangle their Works Cited into perfect form, with penalties for mistakes. That seems silly to me now. To be sure, I want their essays to acknowledge their sources in a standard form so an interested reader can track them down. But they don't need practice in that work. AI can form them according to the standards of the discipline, and that seems fine to me.

The work that stands before us will not lend itself to easy solutions. Our judgments about artificial intelligence's place in our assessments will vary from discipline to discipline, course to course, and even student to student. Alex benefits from ChatGPT's ability to organize his thoughts as a prelude to writing; Jim grows when he undertakes that work on his own. Perhaps a first-year student in philosophy must draft her arguments without the help of artificial intelligence in preparation for four years of making arguments; a senior marketing major should be encouraged to engineer ChatGPT prompts and edit the output.

Teasing out these distinctions will be a long-term project for teachers, one that should be undertaken in community with ourselves and our students: in workshops, conferences, panels, office hours and hallway conversations. It will be difficult to abandon some parts of our assessments and introduce ones. Techno-progressive educators might have to re-embrace some traditional assessments, and AI-phobes will have to familiarize themselves with skills like prompt crafting. But let's embrace what we learn from these conversations, and allow them to lead us toward our own growth as educators.
A Question
I return our attention to the story I told in my introduction, which you might have lost sight of during the course of this long disquisition. I didn't want ChatGPT to fix my verbs because varying them was a skill I wanted to re-master and continue to grow as a writer. Every time I review a sentence now, I examine that verb and see whether I have made the right choice. Having to re-learn this skill has helped me become a better reviser of my prose. I work more slowly, ponder my choices, and improve them when I can.

I chose Option Two, in the scenario I described above, because the barrier to my growth was a temporary one. As my brain rewires itself, I continue to recover vocabulary. But some cases of aphasia are permanent, depending upon the originating cause. Choosing Option Two for someone with that fixed barrier would be a dead end. Growth would grind to a halt.

We finish a question, then, which returns us to our test case scenario on the role that ChatGPT could play in helping students organize their thoughts in preparation for a writing assignment. You have Alex and me in your course, and you have assigned an essay that requires students to present their ideas in an organized argument.

How would you support the growth of both of us?

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John Dewey On Artificial Intelligence in Education

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When does artificial intelligence support--or interfere with--human learning?

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Artificial Intelligence and Education: A Reading List - JSTOR Daily

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Artificial Intelligence and Education: A Reading List - JSTOR Daily

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Artificial Intelligence and Education: A Reading List - JSTOR Daily

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A bibliography to help educators prepare students and themselves for a future shaped by AI-with all its opportunities and drawbacks.

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[2401.08711] Assistant, Parrot, or Colonizing Loudspeaker? ChatGPT Metaphors for Developing Critical AI Literacies

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[2401.08711] Assistant, Parrot, or Colonizing Loudspeaker? ChatGPT Metaphors for Developing Critical AI Literacies

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Assistant, Parrot, or Colonizing Loudspeaker? ChatGPT Metaphors for Developing Critical AI Literacies

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This study explores how discussing metaphors for AI can help build awareness of the frames that shape our understanding of AI systems, particularly large language models (LLMs) like ChatGPT. Given the pressing need to teach "critical AI literacy", discussion of metaphor provides an opportunity for inquiry and dialogue with space for nuance, playfulness, and critique.

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TeachAI | AI Guidance for Schools Toolkit

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The AI Guidance for Schools Toolkit is designed to help education authorities, school leaders and teachers create their own thoughtful guidance to achieve potential benefits of incorporating artificial intelligence in primary and secondary K-12 education while mitigating risks.

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Creative ideas to use AI in education - Google Slides

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Creative ideas to use AI in education - Google Slides

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AI Educator Tools: The Future of Learning

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AI Educator Tools: The Future of Learning

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"Academic misconduct and AI" for students

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"Academic misconduct and AI" for students

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Academic Misconduct and Artificial Intelligence

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"An Introduction to ChatGPT" for students

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"An Introduction to ChatGPT" for students