%0 Journal Article %1 xiao2025venturing %A Xiao, Junhong %A Bozkurt, Aras %A Nichols, Mark %A Pazurek, Angelica %A Stracke, Christian M. %A Bai, John Y. H. %A Farrow, Robert %A Mulligan, Dónal %A Nerantzi, Chrissi %A Sharma, Ramesh Chander %A Singh, Lenandlar %A Frumin, Isak %A Swindell, Andrew %A Honeychurch, Sarah %A Bond, Melissa %A Dron, Jon %A Moore, Stephanie %A Leng, Jing %A van Tryon, Patricia J. Slagter %A Garcia, Manuel %A Terentev, Evgeniy %A Tlili, Ahmed %A Chiu, Thomas K. F. %A Hodges, Charles B. %A Jandrić, Petar %A Sidorkin, Alexander %A Crompton, Helen %A Hrastinski, Stefan %A Koutropoulos, Apostolos %A Cukurova, Mutlu %A Shea, Peter %A Watson, Steven %A Zhang, Kai %A Lee, Kyungmee %A Costello, Eamon %A Sharples, Mike %A Vorochkov, Anton %A Alexander, Bryan %A Bali, Maha %A Moore, Robert L. %A Zawacki-Richter, Olaf %A Asino, Tutaleni Iita %A Huijser, Henk %A Zheng, Chanjin %A Sani-Bozkurt, Sunagül %A Duart, Josep M. %A Themeli, Chryssa %D 2025 %J TechTrends %K GenAI ai artificial education generative intelligence review %R 10.1007/s11528-025-01060-6 %T Venturing into the Unknown: Critical Insights into Grey Areas and Pioneering Future Directions in Educational Generative AI Research %U https://doi.org/10.1007/s11528-025-01060-6 %X 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.

@article{xiao2025venturing, 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.}, added-at = {2025-02-23T14:28:04.000+0100}, author = {Xiao, Junhong and Bozkurt, Aras and Nichols, Mark and Pazurek, Angelica and Stracke, Christian M. and Bai, John Y. H. and Farrow, Robert and Mulligan, Dónal and Nerantzi, Chrissi and Sharma, Ramesh Chander and Singh, Lenandlar and Frumin, Isak and Swindell, Andrew and Honeychurch, Sarah and Bond, Melissa and Dron, Jon and Moore, Stephanie and Leng, Jing and van Tryon, Patricia J. Slagter and Garcia, Manuel and Terentev, Evgeniy and Tlili, Ahmed and Chiu, Thomas K. F. and Hodges, Charles B. and Jandrić, Petar and Sidorkin, Alexander and Crompton, Helen and Hrastinski, Stefan and Koutropoulos, Apostolos and Cukurova, Mutlu and Shea, Peter and Watson, Steven and Zhang, Kai and Lee, Kyungmee and Costello, Eamon and Sharples, Mike and Vorochkov, Anton and Alexander, Bryan and Bali, Maha and Moore, Robert L. and Zawacki-Richter, Olaf and Asino, Tutaleni Iita and Huijser, Henk and Zheng, Chanjin and Sani-Bozkurt, Sunagül and Duart, Josep M. and Themeli, Chryssa}, biburl = {https://www.bibsonomy.org/bibtex/24a6d338c77cbe18ef6e49623716253c3/yish}, doi = {10.1007/s11528-025-01060-6}, interhash = {bb6fbce229367e1481d5d2275a1fcbc0}, intrahash = {4a6d338c77cbe18ef6e49623716253c3}, issn = {15597075}, journal = {TechTrends}, keywords = {GenAI ai artificial education generative intelligence review}, refid = {Xiao2025}, timestamp = {2025-02-23T14:28:04.000+0100}, title = {Venturing into the Unknown: Critical Insights into Grey Areas and Pioneering Future Directions in Educational Generative AI Research}, url = {https://doi.org/10.1007/s11528-025-01060-6}, year = 2025 }