@article{discovery10206577,
       publisher = {Springer Nature},
           title = {Venturing into the Unknown: Critical Insights into Grey Areas and Pioneering Future Directions in Educational Generative AI Research},
            year = {2025},
         journal = {TechTrends},
           month = {February},
            note = {This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.},
        keywords = {Artificial intelligence in education; Future research directions; 
Generative artificial intelligence (GenAI); 
Grey areas; 
Higher education},
            issn = {8756-3894},
          author = {Xiao, J and Bozkurt, A and Nichols, M and Pazurek, A and Stracke, CM and Bai, JYH and Farrow, R and Mulligan, D and Nerantzi, C and Sharma, RC and Singh, L and Frumin, I and Swindell, A and Honeychurch, S and Bond, M and Dron, J and Moore, S and Leng, J and van Tryon, PJS and Garcia, M and Terentev, E and Tlili, A and Chiu, TKF and Hodges, CB and Jandri{\'c}, P and Sidorkin, A and Crompton, H and Hrastinski, S and Koutropoulos, A and Cukurova, M and Shea, P and Watson, S and Zhang, K and Lee, K and Costello, E and Sharples, M and Vorochkov, A and Alexander, B and Bali, M and Moore, RL and Zawacki-Richter, O and Asino, TI and Huijser, H and Zheng, C and Sani-Bozkurt, S and Duart, JM and Themeli, C},
        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.},
             url = {https://doi.org/10.1007/s11528-025-01060-6}
}