New papers explore the challenges and opportunities of AI for open education
By Sara Feijo
MIT Open Learning announces the publication of nine rapid response papers — written by researchers and practitioners across the world — that examine the challenges and opportunities artificial intelligence (AI) presents for open education. Published under an open license, the papers are the result of Open Learning’s AI + Open Education Initiative.
“The emergence of generative AI is rapidly transforming education around the world,” says Christopher Capozzola, senior associate dean for open learning at MIT and the project’s principal investigator. “Powerful new tools can help realize the promise of open education, and at the same time, we need to preserve and expand the values that motivate open learning. To solve that puzzle, we knew we had to gather a global cohort of voices at the intersection of AI and open education.”
In July 2024, Open Learning issued an international call for proposals exploring the future of open education in an AI-shaped ecosystem and received 147 submissions. An international jury of experts in AI and open education reviewed the submissions and selected nine papers authored by 32 researchers, highlighting the importance of looking beyond the U.S. and the need for shared expertise across fields.
“Together, the projects in this collection depict a future for AI and open education that is deeply personal: rather than supplanting current OER [open educational resources] with general-purpose AI systems, our authors explore ways that AI can be used to customize and refine OER for individual needs,” Sarah Schwettmann, jury chair and a research scientist at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), wrote in the preface to the collection. “Authors describe applications of AI ranging from dynamically generating custom learning paths, to enhancing visibility of OER for colorblind learners, editing Spanish Wikipedia articles, and localizing UDL [Universal Design for Learning] curriculum translations for Kazakhstan.”
Through the AI + Open Education Initiative, Open Learning aims to bring contributors and funders into conversations that catalyze research, infrastructure, industry, and teaching innovations to advance open education for learners worldwide. The initiative has committed seed funding to advance each of the nine selected projects. The initiative will also hold a public webinar series this year, hosted by the MIT OpenCourseWare Collaborations Program. Details will be announced soon. (Sign up for the initiative’s mailing list to receive more information.)
The nine published papers are:
Addressing Challenges in Faculty Professional Development: UDL Training through AI-Enhanced OER in a Non-English Context
Author: Aigerim Shilibekova
This rapid response paper illustrates how AI-powered open educational resources can foster equity and inclusivity in education, thus offering a replicable model for transforming professional development.
AI Literacies and the Advancement of Opened Culture: Global Perspectives and Practices
Authors: Angela Gunder, Joshua Herron, Nicole Weber, Colette Chelf, and Sherry Birdwell
This paper examines how AI influences open collaboration, the creation of open educational resources, and the alignment of resources and initiatives to the needs and values of the open community.
Auto-Evaluation: A Critical Measure in Driving Improvements in Quality and Safety of AI-Generated Lesson Resources
Authors: Hannah-Beth Clark, Margaux Dowland, Laura Benton, Reka Budai, Ibrahim Kaan Keskin, Emma Searle, Matthew Gregory, Mark Hodierne, William Gayne, and John Roberts
Through an illustrative case study, this paper analyzes AI-produced content quickly and efficiently with a focus on quality and safety.
Creating Open Learning Virtuous Circles: Wikipedia, Generative AI, and Postdigital Literacies in a Social Service Program for Online Students
Author: Jackeline Bucio-García
This project promotes postdigital literacies and sustainable practices for meaningful engagement with technology in collaborative learning.
CVD Mode: Hybrid AI-Adaptive Framework for Enhancing Digital Accessibility for Color Vision Deficiency
Author: Chintala Pranava Sai
This paper introduces a hybrid AI-adaptive scalable modular framework that improves accessibility by examining user experience of color.
Enhancing MOOCs with AI
Author: João Alberto Arantes do Amaral
This paper explores the successes and challenges of incorporating free and AI-based tools for Massive Open Online Courses (MOOCs) at the Federal University of São Paulo’s Outreach Program, including course development, delivery, and assessment.
Frankenstein Curricula: Stitching Together Open Educational Resources to Generate Dynamic Learning Paths With AI
Authors: Pegor Papazian and Zachary Pardos
This paper introduces a framework for creating a more flexible and learner-centered education experience by combining interoperable open educational resource modules.
Judicious AI Use to Improve Existing OER
Authors: Royce Kimmons, George Veletsianos, and Torrey Trust
This paper explores how open education can serve as a space for more sustainable and equitable uses of AI to achieve socially valuable goals.
Sopala: An Innovative Model for K-12 Education
Authors: Dan McGuire, Robert Murphy, Sadik Shahadu, Peter K. Amoabil, Maxwell Beganim, Musah Fuseini, Stephane Coillet-Matillon, and Steve Miley
This paper presents an innovative approach to K-12 education that functions effectively in classrooms with or without internet access, demonstrating how open practices can impact student learning in any setting.
MIT Open Learning’s AI + Open Education Initiative is supported by the William and Flora Hewlett Foundation. For more information, visit the AI + Open Education Initiative website.
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