Bridging the Divide: An Empirical Investigation of Artificial Intelligence and Generative Artificial Intelligence Integration Across Genders, Disciplines and Academic Roles
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Andrew, S., & Halcomb, E. J. (2009). Mixed methods research for nursing and the health sciences. Blackwell Pub.AndrewS.HalcombE. J., (2009). Mixed methods research for nursing and the health sciences. Blackwell Pub.Search in Google Scholar
Banh, L., & Strobel, G. (2023). Generative artificial intelligence. Electronic Markets, 33(1), 63. https://doi.org/10.1007/s12525-023-00680-1BanhL.StrobelG., (2023). Generative artificial intelligence. Electronic Markets, 33(1), 63. https://doi.org/10.1007/s12525-023-00680-1Search in Google Scholar
Bonsu, E. M., & Baffour-Koduah, D. (2023). From the consumers’ side: Determining students’ perception and intention to use ChatGPT in Ghanaian higher education. Journal of Education, Society & Multiculturalism, 4(1), 1–29. https://doi.org/10.2478/jesm-2023-0001BonsuE. M.Baffour-KoduahD., (2023). From the consumers’ side: Determining students’ perception and intention to use ChatGPT in Ghanaian higher education. Journal of Education, Society & Multiculturalism, 4(1), 1–29. https://doi.org/10.2478/jesm-2023-0001Search in Google Scholar
Chiu, T. K. F. (2023). The impact of generative AI (GenAI) on practices, policies and research direction in education: A case of ChatGPT and Midjourney. Interactive Learning Environments, 1–17. https://doi.org/10.1080/10494820.2023.2253861ChiuT. K. F., (2023). The impact of generative AI (GenAI) on practices, policies and research direction in education: A case of ChatGPT and Midjourney. Interactive Learning Environments, 1–17. https://doi.org/10.1080/10494820.2023.2253861Search in Google Scholar
Correll, S. J. (2001). Gender and the career choice process: The role of biased self assessments. American Journal of Sociology, 106(6), 1691–1730. https://doi.org/10.1086/321299CorrellS. J., (2001). Gender and the career choice process: The role of biased selfūassessments. American Journal of Sociology, 106(6), 1691–1730. https://doi.org/10.1086/321299Search in Google Scholar
Dahlkemper, M. N., Lahme, S. Z., & Klein, P. (2023). How do physics students evaluate artificial intelligence responses on comprehension questions? A study on the perceived scientific accuracy and linguistic quality of ChatGPT. Physical Review Physics Education Research, 19(1), 010142. https://doi.org/10.1103/PhysRevPhysEducRes.19.010142DahlkemperM. N.LahmeS. Z.KleinP., (2023). How do physics students evaluate artificial intelligence responses on comprehension questions? A study on the perceived scientific accuracy and linguistic quality of ChatGPT. Physical Review Physics Education Research, 19(1), 010142. https://doi.org/10.1103/PhysRevPhysEducRes.19.010142Search in Google Scholar
Dimla, C. Y., Sumaway, M. D., Torres, J. M. T., & Dela Cruz, C. A. B. (2024). The role of artificial intelligence in personalized learning: Enhancing student engagement and academic performance. International Journal of Research Publication and Reviews, 4(4), 8495-8505.DimlaC. Y.SumawayM. D.TorresJ. M. T.Dela CruzC. A. B., (2024). The role of artificial intelligence in personalized learning: Enhancing student engagement and academic performance. International Journal of Research Publication and Reviews, 4(4), 8495–8505.Search in Google Scholar
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., …& Wright, R. (2023). Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642DwivediY. K.KshetriN.HughesL.SladeE. L.JeyarajA.KarA. K.WrightR., (2023). Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642Search in Google Scholar
Ehrlinger, J., & Dunning, D. (2003). How chronic self-views influence (and potentially mislead) estimates of performance. Journal of Personality and Social Psychology, 84(1), 5–17. https://doi.org/10.1037/0022-3514.84.1.5EhrlingerJ.DunningD., (2003). How chronic self-views influence (and potentially mislead) estimates of performance. Journal of Personality and Social Psychology, 84(1), 5–17. https://doi.org/10.1037/0022-3514.84.1.5Search in Google Scholar
Feuerriegel, S., Hartmann, J., Janiesch, C., & Zschech, P. (2024). Generative AI. Business & Information Systems Engineering, 66(1), 111–126. https://doi.org/10.1007/s12599-023-00834-7FeuerriegelS.HartmannJ.JanieschC.ZschechP., (2024). Generative AI. Business & Information Systems Engineering, 66(1), 111–126. https://doi.org/10.1007/s12599-023-00834-7Search in Google Scholar
Haensch, A.-C., Ball, S., Herklotz, M., & Kreuter, F. (2023). Seeing ChatGPT through students’ eyes: An analysis of TikTok data.HaenschA.-C.BallS.HerklotzM.KreuterF., (2023). Seeing ChatGPT through students’ eyes: An analysis of TikTok data.Search in Google Scholar
Huang, C. (2013). Gender differences in academic selfefficacy: A meta-analysis. European Journal of Psychology of Education, 28(1), 1–35. https://doi.org/10.1007/s10212-011-0097-yHuangC., (2013). Gender differences in academic selfefficacy: A meta-analysis. European Journal of Psychology of Education, 28(1), 1–35. https://doi.org/10.1007/s10212-011-0097-ySearch in Google Scholar
Idowu, J. A. (2024). Debiasing education algorithms. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-023-00389-4IdowuJ. A., (2024). Debiasing education algorithms. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-023-00389-4Search in Google Scholar
Jordan, M. I, & Mitchell, T. M. (2015). Machine learning: Trends, perspectives, and prospects. Science, 349(6245), 255–260. https://doi.org/10.1126/science.aaa8415JordanM. I.MitchellT. M., (2015). Machine learning: Trends, perspectives, and prospects. Science, 349(6245), 255–260. https://doi.org/10.1126/science.aaa8415Search in Google Scholar
Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). Exploring generative artificial intelligence preparedness among university language instructors: A case study. Computers and Education: Artificial Intelligence, 5(2), 100156. https://doi.org/10.1016/j.caeai.2023.100156KohnkeL.MoorhouseB. L.ZouD., (2023). Exploring generative artificial intelligence preparedness among university language instructors: A case study. Computers and Education: Artificial Intelligence, 5(2), 100156. https://doi.org/10.1016/j.caeai.2023.100156Search in Google Scholar
Kurtz, G., Amzalag, M., Shaked, N., Zaguri, Y., Kohen-Vacs, D., Gal, E., …& Barak-Medina, E. (2024). Strategies for integrating generative AI into higher education: Navigating challenges and leveraging opportunities. Education Sciences, 14(5), 503. https://doi.org/10.3390/educsci14050503KurtzG.AmzalagM.ShakedN.ZaguriY.Kohen-VacsD.GalE.Barak-MedinaE., (2024). Strategies for integrating generative AI into higher education: Navigating challenges and leveraging opportunities. Education Sciences, 14(5), 503. https://doi.org/10.3390/educsci14050503Search in Google Scholar
Malik, T., Dettmer, S., Hughes, L., & Dwivedi, Y. K. (2024). Academia and generative artificial intelligence (GenAI) SWOT analysis – Higher education policy implications. In S. K. Sharma, Y. K. Dwivedi, B. Metri, B. Lal, & A. Elbanna (Eds.), Transfer, diffusion and adoption of next-generation digital technologies (pp. 3–16). Springer Nature Switzerland.MalikT.DettmerS.HughesL.DwivediY. K., (2024). Academia and generative artificial intelligence (GenAI) SWOT analysis – Higher education policy implications. In SharmaS. K.DwivediY. K.MetriB.LalB.ElbannaA. (Eds.), Transfer, diffusion and adoption of next-generation digital technologies (pp. 3–16). Springer Nature Switzerland.Search in Google Scholar
Mao, J., Chen, B., & Liu, J. C. (2024). Generative artificial intelligence in education and its implications for assessment. TechTrends, 68(1), 58–66. https://doi. org/10.1007/s11528-023-00911-4MaoJ.ChenB.LiuJ. C., (2024). Generative artificial intelligence in education and its implications for assessment. TechTrends, 68(1), 58–66. https://doi.org/10.1007/s11528-023-00911-4Search in Google Scholar
Marengo, A., Pagano, A., Pange, J., & Soomro, K. A. (2024). The educational value of artificial intelligence in higher education: A 10-year systematic literature review. Interactive Technology and Smart Education. https://doi.org/10.1108/ITSE-11-2023-0218MarengoA.PaganoA.PangeJ.SoomroK. A., (2024). The educational value of artificial intelligence in higher education: A 10-year systematic literature review. Interactive Technology and Smart Education. https://doi.org/10.1108/ITSE-11-2023-0218Search in Google Scholar
Mathew, R., & Stefaniak, J. E. (2024). A needs assessment to support faculty members’ awareness of generative AI technologies to support instruction. TechTrends, 68, 773–789. https://doi.org/10.1007/s11528-024-00964-zMathewR.StefaniakJ. E., (2024). A needs assessment to support faculty members’ awareness of generative AI technologies to support instruction. TechTrends, 68, 773–789. https://doi.org/10.1007/s11528-024-00964-zSearch in Google Scholar
Ooi, K.-B., Tan, G. W.-H., Al-Emran, M., Al-Sharafi, M. A., Capatina, A., Chakraborty, A., …& Wong, L.-W. (2023). The potential of generative artificial intelligence across disciplines: Perspectives and future directions. Journal of Computer Information Systems, 1-32. https://doi.org/10.1080/08874417.2023.2261010OoiK.-B.TanG. W.-H.Al-EmranM.Al-SharafiM. A.CapatinaA.ChakrabortyA.WongL.-W., (2023). The potential of generative artificial intelligence across disciplines: Perspectives and future directions. Journal of Computer Information Systems, 1–32. https://doi.org/10.1080/08874417.2023.2261010Search in Google Scholar
Padgett DK. (2012). Qualitative and mixed methods in public health. SAGE Publications. https://doi.org/doi:10.4135/9781483384511PadgettDK., (2012). Qualitative and mixed methods in public health. SAGE Publications. https://doi.org/doi:10.4135/9781483384511Open DOISearch in Google Scholar
Pallier, G. (2003). Gender differences in the selfassessment of accuracy on cognitive tasks. Sex Roles, 48(5), 265–276. https://doi.org/10.1023/A:1022877405718PallierG., (2003). Gender differences in the selfassessment of accuracy on cognitive tasks. Sex Roles, 48(5), 265–276. https://doi.org/10.1023/A:1022877405718Search in Google Scholar
Pedró, F., Subosa, M., Rivas, A., & Valverde, P. (2019). Artificial intelligence in education: Challenges and opportunities for sustainable development.PedróF.SubosaM.RivasA.ValverdeP., (2019). Artificial intelligence in education: Challenges and opportunities for sustainable development.Search in Google Scholar
Ravi Kumar, V. V., & Raman, R. (2022). Student perceptions on artificial intelligence (AI) in higher education. 2022 IEEE integrated STEM education conference (ISEC) (pp. 450-454).Ravi KumarV. V.RamanR., (2022). Student perceptions on artificial intelligence (AI) in higher education. 2022 IEEE integrated STEM education conference (ISEC) (pp. 450–454).Search in Google Scholar
Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.RogersE. M., (2003). Diffusion of innovations (5th ed.). Free Press.Search in Google Scholar
Sáinz, M., Fàbregues, S., & Solé, J. (2020). Parent and teacher depictions of gender gaps in secondary student appraisals of their academic competences. Frontiers in Psychology, 11, 573752. https://doi.org/10.3389/fpsyg.2020.573752SáinzM.FàbreguesS.SoléJ., (2020). Parent and teacher depictions of gender gaps in secondary student appraisals of their academic competences. Frontiers in Psychology, 11, 573752. https://doi.org/10.3389/fpsyg.2020.573752Search in Google Scholar
Saks, M., & Allsop, J. (2013). Researching health: Qualitative, quantitative and mixed methods (2nd ed.). SAGE London.SaksM.AllsopJ., (2013). Researching health: Qualitative, quantitative and mixed methods (2nd ed.). SAGE London.Search in Google Scholar
Saldana, J. (2009). The coding manual for qualitative researchers. Sage Publications.SaldanaJ., (2009). The coding manual for qualitative researchers. Sage Publications.Search in Google Scholar
Turing, A. M. (2009). Computing machinery and intelligence. In R. Epstein, G. Roberts, & G. Beber (Eds.), Parsing the Turing test: Philosophical and methodological issues in the quest for the thinking computer (pp. 23–65). Springer Netherlands.TuringA. M., (2009). Computing machinery and intelligence. InEpsteinR.RobertsG.BeberG. (Eds.), Parsing the Turing test: Philosophical and methodological issues in the quest for the thinking computer (pp. 23–65). Springer Netherlands.Search in Google Scholar
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., …& Polosukhin, I. (2017). Attention is all you need. Advances in neural information processing systems.VaswaniA.ShazeerN.ParmarN.UszkoreitJ.JonesL.GomezA. N.PolosukhinI., (2017). Attention is all you need. Advances in neural information processing systems.Search in Google Scholar
Wang, L., & Yu, Z. (2023). Gender-moderated effects of academic self-concept on achievement, motivation, performance, and self-efficacy: A systematic review. Frontiers in Psychology, 14, 1136141. https://doi.org/10.3389/fpsyg.2023.1136141WangL.YuZ., (2023). Gender-moderated effects of academic self-concept on achievement, motivation, performance, and self-efficacy: A systematic review. Frontiers in Psychology, 14, 1136141. https://doi.org/10.3389/fpsyg.2023.1136141Search in Google Scholar
Zou, B., Liviero, S., Hao, M., & Wei, C. (2020). Artificial intelligence technology for EAP speaking skills: Student perceptions of opportunities and challenges. In M. R. Freiermuth & N. Zarrinabadi (Eds.), Technology and the psychology of second language learners and users (pp. 433–463). Springer International Publishing.ZouB.LivieroS.HaoM.WeiC., (2020). Artificial intelligence technology for EAP speaking skills: Student perceptions of opportunities and challenges. In FreiermuthM. R.ZarrinabadiN. (Eds.), Technology and the psychology of second language learners and users (pp. 433–463). Springer International Publishing.Search in Google Scholar