Since its launch in late 2022, the uncannily convincing AI text generator ChatGPT has prompted questions, opinions, and uncertainty about the potential impacts of AI-generated content on learning and academic work. Referred to as Language-Learning Models (LLM), Generative Artificial Intelligence (GenAI), or simply AI, this new technology is predicted to change the way we live and work.
Here, we focus on pedagogical approaches to AI.
Below you will find our AI Whitepaper, information about our AI Conversation Series, and a frequently-updated list of pedagogical readings and resources.
Click through for:
We’ve been hearing a lot in the news about how access to ChatGPT will revolutionize our teaching practices. The following is our attempt, in February 2023, to synthesize what we learned, and make some targeted suggestions to faculty for the Spring 2023 semester. Some of our suggestions should be pretty fast to implement, and others more time-consuming.
Events: AI Conversation Series
Beginning in Spring 2023, the CTL has facilitated a series of conversations about the impact of AI on education with and amongst Baruch College faculty and staff. These conversations, occurring once each month via Zoom, are guided by a central topic and create a space for discussion among faculty about how we can adapt our teaching to a quickly changing landscape in the nature of work and learning. We invite Baruch faculty and staff to grapple with these changes and what it means for our work through these informal dialogues and exchange of ideas.
Please see below for all AI-related conversations and events sponsored by the CTL, and keep checking this space for updates.
Below is the slide deck from the conversation, followed by a summary of the session and an analysis of the polls taken by attendees. Continue reading to learn about your colleagues’ thoughts on Generative AI and please join us on October 24 for the next conversation.(more…)
Below is the slide deck from the conversation, followed by an analysis of the polls taken by attendees, prepared by the CTL’s Christopher Campbell. Continue reading to learn about your colleagues’ thoughts on Generative AI and please join us on September 20 for the next conversation.(more…)
Resources: Staff Picks
This is a constantly updated compendium of academically-oriented information about AI, curated by Baruch’s Center for Teaching and Learning. We identify the author(s), offer brief guidance, a review and a link. Scroll down for links to Baruch, CUNY and external resources.
Should You Add an AI Policy to Your Syllabus?
Kevin Gannon (Queens University, Charlotte)
Read the article to get an idea for how to introduce an AI policy into your syllabus. Includes suggestions for background reading on which to make informed decisions about AI, its relation to your pedagogy, academic integrity and the changing pace of the field.
In this Chronicle of Higher Education piece, Kevin Gannon, Director of the Center for the Advancement of Faculty Excellence and a professor of history at Queens University of Charlotte (N.C.), encourages faculty to incorporate language about the use of AI in their syllabus policies and have thoughtful discussions about AI with students.
AI/LLM Policy Statements
Katy Pearce (University of Washington)
Adapt this statement or use it as inspiration for your own.
After writing an AI policy earlier in the year and implementing it in her courses, Katy has since made revisions and offers her feedback in this thoughtful post.
Association for Writing Across the Curriculum Statement on AI Writing Tools in WAC Settings
AWAC Executive Committee
Read especially if you are interested in the “practical and ethical implications” of AI. In this case, AI is affecting writing thought of as a cognitive process.
This statement from the flagship organization on Writing Across the Curriculum in the U.S. addresses the growing presence of AI text generators and their impact on writing education, highlighting concerns about their potential to replace authentic writing-based learning experiences, and encouraging a nuanced exploration of how AI tools might be integrated into writing pedagogy while upholding established best practices in Writing Across the Curriculum.
How to Cite ChatGPT, American Psychological Association
Use this resource as a reference for APA citations for AI-generated content.
Detailed guidance for citing material from different AI platforms using APA formatting. Contains useful case examples.
Modern Language Association Guidance on Citations for the Use of Generative-AI
MLA Style Center
Use this resource as a reference for MLA citations for AI-generated content.
Detailed guidance for citing material from different AI platforms using MLA formatting. Contains useful case examples. Begins with the important recommendation to not treat an AI tool as an author.
A People’s Guide to AI
Mimi Onuoha and Mother Cyborg (Diana Nucera)
This is about a couple hours of reading front-to-back. You can also just skip to the section you’re most interested in. It also includes some exercises and note-taking spaces for making sense of the information and connecting it more concretely to our lives.
This is a super accessible guide to learning more about AI, algorithms, machine learning and questions of equity in the face of these new technologies. The authors offer simple, non-jargon definitions and explanations of what AI currently looks like in our lives, and its potential impacts on our lives and social relations. The authors take the stance that we live under unequal and unfair social structures, and AI has the potential to further exacerbate those inequalities. However, the authors also call for more democratic and imaginative approaches to building AI and setting policies and rules around it that will help us solve social problems rather than intensifying them.(more…)
Resources on AI and Student Writing
Brooke Schreiber and Jen Whiting (Baruch)
Peruse this resource especially if your pedagogy is writing or writing-adjacent.
Curated by two writing professors at Baruch, includes syllabus statements, assignment design, academic integrity, and peer-reviewed articles on the implications of AI on writing as a way of learning and assessment in higher ed.
Developing Your Default GenAI Policy
Lance Cummings (UNC, Wilmington)
Read this article to learn about approaches to creating an AI policy for your course.
A thoughtful deductive approach to developing your classroom AI policy. The article describes how to create your syllabus policy for generative AI based on your approach to knowledge and views on technology.
Classroom Policies for AI Generative Tools
Lance Eaton (UMass, Boston)
The creator says: “Folks are welcomed to download or share this resource or parts of it with their colleagues, institutions, and communities of practice.”
This document compiles dozens of syllabus policy statements for AI-powered tools from institutions around the U.S. and across academic disciplines. A Spanish-language link is also provided in the document.
Overview of the Issues, Statement of Principles, and Recommendations
MLA-CCCC Joint Task Force on Writing and AI
Read this paper to learn about the effect of AI on literacy and writing education. It is short, 15 pages; see especially the recommendations on pages 10-11).
This working paper from the two flagship organizations in English and Writing Studies discusses the risks and benefits of generative AI for teachers and students in writing, literature, and language programs and makes principle-driven recommendations for how educators, administrators, and policy makers can work together to develop ethical, mission-driven policies and support broad development of critical AI literacy.
Developing AI Literacy
Peter Cardon, Carolin Fleischmann, Jolanta Aritz,
Minna Logemann (Baruch), and Jeanette Heidewald
Read this article to learn about AI writing in business courses and other business contexts (it is long, but see especially pages 24-25).
Journal article co-written by a colleague at Baruch in Comm Studies and focuses on AI writing in business contexts and approaches to AI literacy in business communication courses, though with possible wider applicability.
Practical AI for Instructors and Students
Ethan and Lilach Mollick (The Wharton School)
Watch this roughly one hour long video series to learn the basics about Generative AI, how you can use it to help you prepare your course, integrate it into assignments and guide your students in its use.
An introductory series of five videos (10-15 minutes each) on using Generative-AI featuring Professors Ethan and Lilach Mollick at The Wharton School of the University of Pennsylvania. Good background and introduction to Generative AI models, followed by its use in educational contexts: how it may be used by teachers and how teachers can help their students use it in mutually beneficial ways.