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Venturing into the Unknown: Critical Insights into Grey Areas and Pioneering Future Directions in Educational Generative AI Research

  • 19-02-2025
  • Original Paper
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Abstract

The article 'Venturing into the Unknown: Critical Insights into Grey Areas and Pioneering Future Directions in Educational Generative AI Research' delves into the integration of Generative AI (GenAI) in education. It highlights the widespread yet often invisible use of GenAI tools and the urgent need for rigorous evaluation and research to harness its benefits while mitigating potential risks. The study identifies nine themes of grey areas, including decision-making on GenAI use, AI ethics, appropriate levels of GenAI in learning, and the impact on learning and teaching. It also recommends eight themes for future research, such as pedagogical dimensions, cognitive dimensions, and social, cultural, and emotional/psychological dimensions. The findings are based on a modified Delphi technique involving 47 educators, providing a unique perspective on the challenges and opportunities of GenAI in education.
Title
Venturing into the Unknown: Critical Insights into Grey Areas and Pioneering Future Directions in Educational Generative AI Research
Authors
Junhong Xiao
Aras Bozkurt
Mark Nichols
Angelica Pazurek
Christian M. Stracke
John Y. H. Bai
Robert Farrow
Dónal Mulligan
Chrissi Nerantzi
Ramesh Chander Sharma
Lenandlar Singh
Isak Frumin
Andrew Swindell
Sarah Honeychurch
Melissa Bond
Jon Dron
Stephanie Moore
Jing Leng
Patricia J. Slagter van Tryon
Manuel Garcia
Evgeniy Terentev
Ahmed Tlili
Thomas K. F. Chiu
Charles B. Hodges
Petar Jandrić
Alexander Sidorkin
Helen Crompton
Stefan Hrastinski
Apostolos Koutropoulos
Mutlu Cukurova
Peter Shea
Steven Watson
Kai Zhang
Kyungmee Lee
Eamon Costello
Mike Sharples
Anton Vorochkov
Bryan Alexander
Maha Bali
Robert L. Moore
Olaf Zawacki-Richter
Tutaleni Iita Asino
Henk Huijser
Chanjin Zheng
Sunagül Sani-Bozkurt
Josep M. Duart
Chryssa Themeli
Publication date
19-02-2025
Publisher
Springer US
Published in
TechTrends / Issue 3/2025
Print ISSN: 8756-3894
Electronic ISSN: 1559-7075
DOI
https://doi.org/10.1007/s11528-025-01060-6
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