All resources in Artificial Intelligence (AI) & Adapting to Innovation

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Ethics of AI

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The Ethics of AI is a free online course created by the University of Helsinki. The course is for anyone who is interested in the ethical aspects of AI – we want to encourage people to learn what AI ethics means, what can and can’t be done to develop AI in an ethically sustainable way, and how to start thinking about AI from an ethical point of view.

Material Type: Full Course

Hands-On AI Projects for the Classroom: A Guide on Ethics and AI

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In this guide, students’ exploration of AI is framed within the context of ethical considerations and aligned with standards and concepts, and depths of understanding that would be appropriate across various subject areas and grade levels in K–12. Depending on the level of your students and the amount of time you have available, you might complete an entire project, pick and choose from the listed activities, or you might take students’ learning further by taking advantage of the additional extensions and resources provided for you. For students with no previous experience with AI education, exposure to the guided learning activities alone will create an understanding of their world that they likely did not previously have. And for those with some background in computer science or AI, the complete projects and resources will still challenge their thinking and expose them to new AI technologies and applications across various fields of study.

Material Type: Lesson, Lesson Plan, Module, Unit of Study

Authors: General Motors, International Society for Technology in Education (ISTE)

Ethical Use of Technology in Digital Learning Environments: Graduate Student Perspectives

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This book is the result of a co-design project in a class in the Masters of Education program at the University of Calgary. The course, and the resulting book, focus primarily on the safe and ethical use of technology in digital learning environments. The course was organized according to four topics based on Farrow’s (2016) Framework for the Ethics of Open Education and discusses Artificial Intelligence (AI) , social networking services (SNS), 3D printing, resource sharing, adaptive learning systems, STEM, assistive technologies, admissions, and communications. In each of the nine chapters, the authors discuss the connection to the value of technology in education, and practical possibilities of learning technologies for inclusive, participatory, democratic, and pluralistic educational paradigms.

Material Type: Teaching/Learning Strategy, Textbook

Authors: Barbara Brown, Christie Hurrell, Eds, Michele Jacobsen, Verena Roberts

Artificial Intelligence (AI) and Librarianship

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Courses on Artificial Intelligence (AI) and Librarianship in ALA-accredited Masters of Library and Information (MLIS) degrees are rare. We have all been surprised by ChatGPT and similar Large Language Models. Generative AI is an important new area for librarianship. It is also developing so rapidly that no one can really keep up. Those trying to produce AI courses for the MLIS degree need all the help they can get. This book is a gesture of support. It consists of about 95,000 words on the topic, with a 3-400 item bibliography.

Material Type: Reading

Author: Martin Fricke

Bloom's Taxonomy Revisited for AI

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Bloom’s Taxonomy is often used as a resource to help higher education faculty assess what kinds or “levels” of learning are planned based on course-level outcomes and, relatedly, to align appropriate activities and assessments to support student learning and success. Oregon State University's E-Campus used Bloom’s Taxonomy as a touchstone for reconsidering course outcomes and student learning in the age of generative AI. The visual outline and accompanying narrative are intended for faculty use as a guide to reflect on their activities, assessments, and (possibly) course outcomes and begin to identify what changes may be needed to ensure meaningful learning going forward.

Material Type: Teaching/Learning Strategy

Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations

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The U.S. Department of Education Office of Educational Technology’s new policy report, Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations, addresses the clear need for sharing knowledge, engaging educators, and refining technology plans and policies for artificial intelligence (AI) use in education. The report describes AI as a rapidly-advancing set of technologies for recognizing patterns in data and automating actions, and guides educators in understanding what these emerging technologies can do to advance educational goals—while evaluating and limiting key risks.

Material Type: Reading

Authors: Kristina Ishmael, MIguel A Cardona, Roberto J. Rodriguez

101 Creative ideas to use AI in education. A collection curated by #creativeHE.

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This open crowdsourced collection presents a rich tapestry of our collective thinking in the first months of 2023 stitching together potential alternative uses and applications of Artificial Intelligence (AI) that could make a difference and create new learning, development, teaching and assessment opportunities. Experimentation is at the heart of learning, teaching and scholarship. Being open to diverse ideas will help us make novel connections that can lead to new discoveries and insights to make a positive contribution to our world. Ideas shared may be in its embryonic stage, but worth exploring further through active and creative inquiry.

Material Type: Lesson Plan, Teaching/Learning Strategy

Authors: Antonio M. Arboleda, Chrissi Nerantzi, Marianna Karatsiori, Sandra Abegglen

Hands-On AI Projects for the Classroom: A Guide for Secondary Teachers

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This guide provides student-driven projects that can directly teach subject area standards in tandem with foundational understandings of what AI is, how it works, and how it impacts society. Several key approaches were taken into consideration in the design of these projects. Understanding these approaches will support both your understanding and implementation of the projects in this guide, as well as your own work to design further activities that integrate AI education into your curriculum.

Material Type: Lesson, Lesson Plan, Module, Unit of Study

Authors: General Motors, International Society for Technology in Education (ISTE)

Hands-On AI Projects for the Classroom: A Guide for Computer Science Teachers

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The projects in this guide use a student-driven approach to learning. Instead of simply learning about AI through videos or lectures, the students completing these projects are active participants in their AI exploration. In the process, students work directly with innovative AI technologies, participate in “unplugged” activities that further their understanding of how AI technologies work, and create various authentic products—from machine learning models to video games—to demonstrate their learning.

Material Type: Lesson, Lesson Plan, Module, Unit of Study

Authors: General Motors, International Society for Technology in Education (ISTE)

Generative AI in the Rhetoric & Composition Classroom – 2023 D2S2 Project

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This two-part resource is designed to support instructors and students as they navigate the presence of generative AI tools, specifically Large Language Models (LLMs) such as ChatGPT, in the rhetoric and composition classroom. Part I of this resource offers an instructor-focused introduction to what LLMs are and how they operate, as well as an in-depth exploration of the privacy concerns and ethical considerations related to using a tool like ChatGPT. Additionally, Part I provides insights on the practical application of LLMs within the realm of reading and writing in the rhetoric and composition classroom, while promoting a modified stasis theory as a strategy for evaluating any generated output. Part II of this resource offers student-focused tutorials that demonstrate how ChatGPT can augment the writing process for assignments commonly given in a rhetoric and composition course. These tutorials cover the evaluation essay, rhetorical analysis, Rogerian argument, annotated bibliography, and research essay—all while promoting the responsible and ethical use of AI in writing and research. With this comprehensive resource, instructors and students can not only build confidence in their understanding of generative AI within academia, but also build digital literacy that will serve them in the world beyond.

Material Type: Module

Authors: Anneke Snyder, Gwendolyn Inocencio, Irene Ai, Jonahs Kneitly, Mary (Perkins) Landry, Shweta Kailani, Terri Pantuso

WCET Report: Supporting Instruction & Learning Through Artificial Intelligence: A Survey of Institutional Practices & Policies

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Artificial Intelligence in general poses numerous challenges for educators and students alike, such as academic integrity, lack of knowledge and training, misinformation, and implementation costs. However, AI also presents opportunities to support equity and access, increased efficiency, new understandings of (and urgency around) digital literacy and crucial workforce skills, and improved instruction and learning, among others. In April 2023, WCET – the WICHE Cooperative for Educational Technologies, undertook a national survey to ascertain how and why postsecondary institutions are using Artificial Intelligence to support instruction and learning, what policies are in place, and what are the perceived barriers to, and benefits for, its use. This report highlights the survey results plus six in-depth interviews conducted post survey.

Material Type: Reading

Authors: Judith Sebesta, Van Davis

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