TY - JOUR
T1 - Venturing into the Unknown
T2 - Critical Insights into Grey Areas and Pioneering Future Directions in Educational Generative AI Research
AU - Xiao, Junhong
AU - Bozkurt, Aras
AU - Nichols, Mark
AU - Pazurek, Angelica
AU - Stracke, Christian M.
AU - Bai, John Y.H.
AU - Farrow, Robert
AU - Mulligan, Dónal
AU - Nerantzi, Chrissi
AU - Sharma, Ramesh Chander
AU - Singh, Lenandlar
AU - Frumin, Isak
AU - Swindell, Andrew
AU - Honeychurch, Sarah
AU - Bond, Melissa
AU - Dron, Jon
AU - Moore, Stephanie
AU - Leng, Jing
AU - van Tryon, Patricia J.Slagter
AU - Garcia, Manuel
AU - Terentev, Evgeniy
AU - Tlili, Ahmed
AU - Chiu, Thomas K.F.
AU - Hodges, Charles B.
AU - Jandrić, Petar
AU - Sidorkin, Alexander
AU - Crompton, Helen
AU - Hrastinski, Stefan
AU - Koutropoulos, Apostolos
AU - Cukurova, Mutlu
AU - Shea, Peter
AU - Watson, Steven
AU - Zhang, Kai
AU - Lee, Kyungmee
AU - Costello, Eamon
AU - Sharples, Mike
AU - Vorochkov, Anton
AU - Alexander, Bryan
AU - Bali, Maha
AU - Moore, Robert L.
AU - Zawacki-Richter, Olaf
AU - Asino, Tutaleni Iita
AU - Huijser, Henk
AU - Zheng, Chanjin
AU - Sani-Bozkurt, Sunagül
AU - Duart, Josep M.
AU - Themeli, Chryssa
N1 - Publisher Copyright:
© Association for Educational Communications & Technology 2025.
PY - 2025
Y1 - 2025
N2 - 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.
AB - 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.
KW - Artificial intelligence in education
KW - Future research directions
KW - Generative artificial intelligence (GenAI)
KW - Grey areas
KW - Higher education
UR - http://www.scopus.com/inward/record.url?scp=85218173332&partnerID=8YFLogxK
U2 - 10.1007/s11528-025-01060-6
DO - 10.1007/s11528-025-01060-6
M3 - Article
AN - SCOPUS:85218173332
SN - 8756-3894
JO - TechTrends
JF - TechTrends
ER -