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Articles
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Students’ Voices on Generative AI: Perceptions, Benefits, and Challenges in Higher EducationAn important empirical study capturing student perspectives. It validates the usefulness of AI for brainstorming and overcoming writer’s block, while confirming students still value human feedback for in-depth learning. Supports integrating AI as a process aid.
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Integrating Large Language Models into Higher Education: Guidelines for Effective ImplementationProvides a roadmap for institutional policy. It argues that successful AI integration requires a transparent, inclusive process involving both faculty and students to set clear, ethical guidelines, ensuring institutional buy-in and legitimacy.
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Ethical Considerations in the Use of Artificial Intelligence in Higher EducationA foundational text for understanding the broader ethical landscape. It helps faculty move beyond plagiarism to address crucial issues like bias in LLM data sets, data privacy, and the moral responsibility of preparing students for an AI-integrated professional world.
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Enhancing Critical Writing Through AI Feedback: A Randomized Control StudyDirect evidence countering the "critical thinking" anxiety. This study demonstrates that AI-generated feedback can significantly improve students' ability to refine their argument coherence, evidence quality, and rhetorical strategies, reframing AI as a tool for critical revision.
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Large Language Models and Academic Writing: Five Tiers of EngagementOffers a practical framework to manage AI use. It categorizes LLM engagement into five defined levels (from proofreading to full drafting) with suggested permissions and prohibitions, helping faculty establish clear, enforceable boundaries for specific assignments.
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The Usage of AI in Teaching and Students' Creativity: The Mediating Role of Learning Engagement and the Moderating Role of AI LiteracyA study arguing that AI can be a positive force for creativity. It suggests that AI use significantly enhances student creativity when instructors focus on student engagement and explicitly teach AI literacy (the competence to use and evaluate AI tools).
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Human-AI Collaboration Patterns in AI-Assisted Academic WritingExplores the emerging "human-AI collaboration" model, advocating for pedagogy that teaches students how to be effective managers and collaborators with AI tools, viewing the final work as a joint product that still requires human intellect to steer.
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Artificial Intelligence and the Future of Teaching and Learning: Insights and RecommendationsA high-level governmental report that encourages educators to leverage AI for equity and personalized learning by focusing on AI's ability to provide instant, individualized feedback. It acts as an institutional call for proactive, thoughtful integration.
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The Impact of Artificial Intelligence Tools on Academic Writing Instruction in Higher Education: A Systematic ReviewA broad review of recent literature concludes that when used correctly, AI tools demonstrate promise in enhancing writing abilities, boosting student confidence, and increasing productivity. It provides a strong evidence-based endorsement for responsible integration.
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Assigning AI: Seven Approaches for Students, with PromptsThis working paper is for faculty development. It categorizes effective ways to incorporate AI into assignments. The Mollicks organize methods into seven categories, ranging from "AI as a Tutor" to "AI as a Simulation," and provide specific prompts for each. The paper emphasizes a guided, transparent use of AI by illustrating how instructors can design activities where AI does the low-stakes, repetitive work (like summarizing or brainstorming), thereby freeing up student time for higher-order tasks (critical analysis, refinement, and ethical judgment).
Rhetorical Prompting Method by Jeanne Law
This visual resource is important because it moves beyond the theory and gives students a concrete structure for how to talk to the AI, ensuring they maintain control over the output rather than passively accepting it.
Is AI Destroying Education?
(8:54- 25:31) This section of the video emphasizes a new shift in pedagogy required by generative AI: moving evaluation from the final written product to the documented writing process. This is presented as the most effective strategy for maintaining academic integrity and promoting deep learning. The video details practical methods centered on transparency and accountability, primarily through the use of an AI Interaction Log. This log makes the process visible by requiring students to record their prompts, the AI's output, and a personal reflection on how they used or revised the material. The video suggests reframing AI detection software as a diagnostic tool to initiate conversations about writing complexity, rather than solely a policing mechanism. This approach ensures the student remains the central agent of original thought and revision.
Furthermore, the video advocates for leveraging AI as a tool for critical thinking. This includes designing assignments like the "Fix This Essay" Challenge and "Spot the Lie" Verification, which require students to analyze, critique, and correct AI-generated content.
Feaured Books and E-books
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Teaching with AI
How AI is revolutionizing the future of learning and how educators can adapt to this new era of human thinking. Artificial Intelligence (AI) is revolutionizing the way we learn, work, and think. Its integration into classrooms and workplaces is already underway, impacting and challenging ideas about creativity, authorship, and education. In this groundbreaking and practical guide, teachers will discover how to harness and manage AI as a powerful teaching tool. José Antonio Bowen and C. Edward Watson present emerging and powerful research on the seismic changes AI is already creating in schools and the workplace, providing invaluable insights into what AI can accomplish in the classroom and beyond. By learning how to use new AI tools and resources, educators will gain the confidence to navigate the challenges and seize the opportunities presented by AI. From interactive learning techniques to advanced assignment and assessment strategies, this comprehensive guide offers practical suggestions for integrating AI effectively into teaching and learning environments. Bowen and Watson tackle crucial questions related to academic integrity, cheating, and other emerging issues. In the age of AI, critical thinking skills, information literacy, and a liberal arts education are more important than ever. As AI continues to reshape the nature of work and human thinking, educators can equip students with the skills they need to thrive in a rapidly evolving world. This book serves as a compass, guiding educators through the uncharted territory of AI-powered education and the future of teaching and learning.
Publication Date: 2024 -
Generative AI in Higher Education
Chan and Colloton's book is one of the first to provide a comprehensive examination of the use and impact of ChatGPT and Generative AI (GenAI) in higher education.
Publication Date: 2024 -
AI in Learning: Designing the Future
AI (Artificial Intelligence) is predicted to radically change teaching and learning in both schools and industry causing radical disruption of work. AI can support well-being initiatives and lifelong learning but educational institutions and companies need to take the changing technology into account. Moving towards AI supported by digital tools requires a dramatic shift in the concept of learning, expertise and the businesses built off of it. Based on the latest research on AI and how it is changing learning and education, this book will focus on the enormous opportunities to expand educational settings with AI for learning in and beyond the traditional classroom. This open access book also introduces ethical challenges related to learning and education, while connecting human learning and machine learning. This book will be of use to a variety of readers, including researchers, AI users, companies and policy makers.
Publication Date: 2022 -
The Impact of ChatGPT on Higher Education
In an ever-evolving educational landscape, traditional methods face unprecedented challenges. The Impact of ChatGPT on Higher Education takes you on a trailblazing journey into ChatGPT's transformative potential and the ethical considerations in higher education. Authored by experts at the forefront of educational transformation and technology's impact on learning, this book offers invaluable insights for educators, leaders, policymakers, and AI enthusiasts. Dive deep with the authors as they navigate from theory to practice, unravelling power dynamics, social structures, and ChatGPT's profound influence. Real-world examples and a captivating case study from MEF University provide tangible evidence of ChatGPT's impact on education. Explore how ChatGPT raises critical questions about course planning, assessments, teaching, and AI's role in education. The authors illuminate issues related to academic honesty, ethics, bias, misinformation, cost, equity, and data privacy. As AI technologies continue to evolve and impact education, The Impact of ChatGPT on Higher Education provides valuable guidance and insights for educators and researchers seeking to harness the power of ChatGPT in their work.
Publication Date: 2024 -
Optimizing AI in Higher Education: SUNY FACT² Guide, Second Edition
This document presents information and solutions to educators across the spectrum of enthusiasm and adoption interests, empowering everyone to make educated decisions for themselves and their students regarding generative AI.
Publication Date: 2024
The Best AI Tools for Academia in 2025
Additional Recommended Resources
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10 Charts Explaining the Impact of Generative AI on Work as We Know ItA collection of ten data visualizations demonstrating how generative AI is shifting job roles, workflows, and required skills across professional industries. McLees argues that the primary impact of AI will not be replacement, but the delegation of low-value, repetitive tasks, freeing up human workers to focus on high-value, cognitively demanding tasks such as critical judgment, emotional intelligence, and complex problem-solving.
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AI as Normal Technology"AI as Normal Technology" explores AI as a transformative but fundamentally normal technology, comparable to electricity or the internet, rather than a potentially superintelligent entity. The authors challenge both utopian and dystopian narratives that treat AI as a separate species, arguing instead that the tempo of technological change is set not by the pace of innovation but by the pace of adoption, which is gated by economic, social, and infrastructure factors, and by the need of humans to adapt. They emphasize that tasks requiring creativity and judgment, like preparing legal filings, are both the hardest to evaluate and would have the most profound impact if automated.
Yejin Choi on AI and Common Sense
In this Mindscape Podcast episode, Sean Carroll interviews Yejin Choi about the capabilities and limitations of large language models like ChatGPT. Choi explores whether these AI systems truly understand what they discuss or simply string words together convincingly without underlying comprehension. She explains that LLMs are trained merely to predict the next word in a sequence based on vast text data, representing words as vectors whose meaning depends on context. Her main concerns include AI's tendency to confidently state false information, its vulnerability to "jailbreaking" (manipulating banned prompts such as how to make a bomb), a lack of self-awareness about its limitations, and an absence of intrinsic motivation or curiosity—highlighting fundamental differences between artificial and human intelligence.