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

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 GarciaEvgeniy 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

Research output: Contribution to journalArticlepeer-review

Abstract

Advocates of AI in Education (AIEd) assert that the current generation of technologies, collectively dubbed artificial intelligence, including generative artificial intelligence (GenAI), promise results that can transform our conceptions of what education looks like. Therefore, it is imperative to investigate how educators perceive GenAI and its potential use and future impact on education. Adopting the methodology of collective writing as an inquiry, this study reports on the participating educators’ perceived grey areas (i.e. issues that are unclear and/or controversial) and recommendations on future research. The grey areas reported cover decision-making on the use of GenAI, AI ethics, appropriate levels of use of GenAI in education, impact on learning and teaching, policy, data, GenAI outputs, humans in the loop and public–private partnerships. Recommended directions for future research include learning and teaching, ethical and legal implications, ownership/authorship, funding, technology, research support, AI metaphor and types of research. Each theme or subtheme is presented in the form of a statement, followed by a justification. These findings serve as a call to action to encourage a continuing debate around GenAI and to engage more educators in research. The paper concludes that unless we can ask the right questions now, we may find that, in the pursuit of greater efficiency, we have lost the very essence of what it means to educate and learn.

Original languageEnglish
JournalTechTrends
DOIs
StateAccepted/In press - 2025

Scopus Subject Areas

  • Education
  • Computer Science Applications

Keywords

  • Artificial intelligence in education
  • Future research directions
  • Generative artificial intelligence (GenAI)
  • Grey areas
  • Higher education

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