Authors

Aras Bozkurt, Anadolu University
Junhong Xiao, Open University of Shantou
Robert Farrow, Open University
John Y. H. Bai, Carl von Ossietzky Universität
Chrissi Nerantzi, University of Leeds
Stephanie Moore, University of New Mexico
Jon Dron, Athabasca University
Christian M. Stracke, University of Bonn
Lenandlar Singh, University of Guyana
Helen Crompton, Old Dominion UniversityFollow
Apostolos Koutropoulos, University of Massachusetts Boston
Evgenii Terentev, HSE University
Angelica Pazurek, University of Minnesota
Mark Nichols, Open Polytechnic
Alexander M. Sidorkin, California State University
Eamon Costello, Dublin City University
Steven Watson, University of Cambridge
Dónal Mulligan, Dublin City University
Sarah Honeychurch, University of Glasglow
Charles B. Hodges, Georgia Southern University
Mike Sharples, The Open University
Andrew Swindell, Asian University for Women
Isak Frumin, Constructor University
Ahmed Tlili, Beijing Normal University
Patricia J. Slagter van Tryon, East Carolina University
Melissa Bond, University College London
Maha Bali, American University in Cairo
Jing Leng, East China Normal University
Kai Zhang, East China Normal University
Mutlu Cukurnova, University College London
Thomas K. F. Chiu, Chinese University of Hong Kong
Kyungmee Lee, Seoul National University
Stefan Hrastinski, KTH Royal Institution of Technology
Manuel B. Garcia, FEU Institute of Technology
Ramesh Chander Sharma, Graphic Era Hill University
Bryan Alexander, Georgetown University
Olaf Zawacki-Richter, University of Oldenburg
Henk Huijser, Queensland University of Technology
Petar Jandrić, Zagreb University of Applied Sciences
Chanjin Zheng, East China Normal University
Peter Shea, University of Albany
Josep M. Duart, Universitat Oberta de Catalunya
Chryssa Themeli, NTNU
Anton Vorochkov, Autonomous University of Madrid
Sunagül Sani-Bozkurt, Anadolu University
Robert L. Moore, University of Florida
Tutaleni Iita Asino, Carnegie Mellon University

Document Type

Editorial

Publication Date

2024

DOI

10.55982/openpraxis.16.4.777

Publication Title

Open Praxis

Volume

16

Issue

4

Pages

487-513

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.

Rights

© 2024 The Author(s).

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

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)

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