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Generative AI in Academic Research: A Descriptive Study on Awareness, Gender Usage, and Views among Pre-Service Teachers

Yıl 2024, Cilt: 8 Sayı: 1, 45 - 60

Matthew Nyaaba Patrick Kyeremeh Eric Kojo Majialuwe Collins Owusu-fordjour Esther Asebiga Barnabas A-ingkonge

https://doi.org/10.61969/jai.1400867

Öz

This study investigated the engagement of Pre-Service Teachers (PSTs) with Generative AI (GAI) tools in their research projects, focusing on their awareness, source of awareness, usage pattern based on gender, and views of GAI tools in academic research. We adopted a descriptive survey method to collect data from one hundred and four PSTs across five institutions in Ghana using a five-point Likert-type survey instrument, which included an open-ended question. The quantitative data were analyzed using means, frequencies, percentages, standard deviations, and an independent samples t-test. The findings revealed that PSTs are familiar with GAI tools, especially ChatGPT and Google Bard. They learned about these tools through personal searches, recommendations from friends, and social media platforms. The PSTs used these tools in writing all chapters of their research projects, with the Introduction Chapter being the most common area of application, followed by the Discussion and Findings Chapter, the Literature Review Chapter, Methodology, and Summary and Conclusion. We also identified a significant gender disparity in the use of GAI tools, with male PSTs exhibiting a higher frequency of use compared to their female counterparts. Nonetheless, both genders expressed a positive attitude towards GAI tools in academic research, noting among other benefits that these tools provided them with confidence and independence in their research writing. However, they also recognized inaccuracies in the information provided by GAI tools, which led to skepticism about relying solely on these tools for their research projects. Consequently, they expressed a preference for support from their research supervisors, highlighting the importance of a balanced approach that combines the use of GAI tools with human supervision in academic research. While we recommend the integrating of GAI tools in teacher education programs, we strongly suggest that such integration should be complemented with comprehensive guidance on how these tools can be effectively used by PSTs to conduct original and advanced research.

Anahtar Kelimeler

Generative AI Research Awareness Use Perspectives Pre-service Teachers (PSTs) Gender

Kaynakça

  • Acilar, A., & Sæbø, Ø. (2023). Towards understanding the gender digital divide: A systematic literature review. Global knowledge, memory and communication, 72(3), 233-249. https://doi.org/10.1108/GKMC-09-2021-0147
  • Afful, J. B. A., Ngula, R. S., Twumasi, R., Tetteh, G., & Mensah, F. (2022). Supervisors’ perceptions of postgraduate students’ thesis literature review writing in a Ghanaian university. Advances in Social Sciences Research Journal, 9(1), 267-289. http://dx.doi.org/10.14738/assrj.91.11120
  • Akanzire, B.N., Nyaaba, M. & Nabang, M. (2023). Perceptions and Preparedness: Exploring Teacher Educators' Views on Integrating Generative AI in Colleges of Education, Ghana (November 3, 2023). Available at SSRN: http://dx.doi.org/10.2139/ssrn.4628153
  • Alam, A. (2021, November). Possibilities and apprehensions in the landscape of artificial intelligence in education. In 2021 International Conference on Computational Intelligence and Computing Applications (ICCICA) (pp. 1-8). IEEE. https://doi.org/10.1109/ICCICA52458.2021.9697272
  • Alshater, M. (2022). Exploring the role of artificial intelligence in enhancing academic performance: A case study of ChatGPT. Available at SSRN: https://ssrn.com/abstract=4312358 or http://dx.doi.org/10.2139/ssrn.4312358
  • An, X., Chai, C. S., Li, Y., Zhou, Y., Shen, X., Zheng, C., & Chen, M. (2023). Modeling English teachers’ behavioral intention to use artificial intelligence in middle schools. Education and Information Technologies, 28(5), 5187-5208. https://doi.org/10.1007/s10639-022-11286-z
  • Antonio, A., & Tuffley, D. (2014). The gender digital divide in developing countries. Future Internet, 6(4), 673-687. https://doi.org/10.3390/fi6040673
  • Armah, P. H. (2018). T-TEL Curriculum Reform Study.
  • Armah, P. H. (2017). Teacher education and professional learning in Ghana. The Institute for Education Studies (IFEST): Accra. Recuperado a partir de https://www.academia.edu/34610560/TEACHER_EDUCATION_AND_PROFESSIONAL_LEARNING_IN_GHANA.
  • Ausat, A. M. A., Massang, B., Efendi, M., Nofirman, N., & Riady, Y. (2023). Can chat GPT replace the role of the teacher in the classroom: A fundamental analysis. Journal on Education, 5(4), 16100-16106.
  • Aydin, Ö. (2023). Google Bard generated literature review: metaverse. Journal of AI, 7(1), 1-14.
  • Aydın, Ö., Karaarslan, E. (2022). OpenAI ChatGPT Generated Literature Review: Digital Twin in Healthcare. In Ö. Aydın (Ed.), Emerging Computer Technologies 2 (pp. 22-31). İzmir Akademi Dernegi.
  • Aydin, Ö., & Karaarslan, E. (2023). Is ChatGPT leading generative AI? What is beyond expectations?. Academic Platform Journal of Engineering and Smart Systems, 11(3), 118-134.
  • Azila-Gbettor, E. M., Mensah, C., & Kwodjo Avorgah, S. M. (2015). Challenges of writing dissertations: Perceptual differences between students and supervisors in a Ghanaian polytechnic. International Journal of Education and Practice, 3(4), 182-198. DOI: 10.18488/journal.61/2015.3.4/61.4.182.198
  • Chan, C. K. Y., & Hu, W. (2023). Students' Voices on Generative AI: Perceptions, Benefits, and Challenges in Higher Education. arXiv preprint arXiv:2305.00290.
  • Chen, Y., Chen, Y., & Heffernan, N. (2020). Personalized math tutoring with a conversational agent. arXiv preprint arXiv:2012.12121.
  • Chen X, Zou D, Xie H, Cheng G, Liu C. Two decades of artificial intelligence in education. Educ Technol Soc. 2022;25(1):28-47.
  • Choung, H., David, P., & Ross, A. (2023). Trust in AI and Its Role in the Acceptance of AI Technologies. International Journal of Human–Computer Interaction, 39(9), 1727-1739.
  • Devi, J. S., Sreedhar, M. B., Arulprakash, P., Kazi, K., & Radhakrishnan, R. (2022). A path towards child-centric Artificial Intelligence based Education. International Journal of Early Childhood, 14(3), 9915-9922.
  • Donaldson, J. L., Gallimore, L., & Swanson, D. (2019). National survey of extension 4-H professionals’ perceptions of professional development factors. Journal of extensions, 57(1), 1-14. https://doi.org/10.34068/joe.57.01.27
  • Escotet, M. Á. (2023). The optimistic future of Artificial Intelligence in higher education. Prospects, 1-10.
  • Fisher, A., Exley, K., & Ciobanu, D. (2014). Using technology to support learning and teaching. London: Routledge. https://doi.org/10.4324/9780203074497
  • Goswami, A., & Dutta, S.(2015). Gender Differences in Technology Usage—A Literature Review. Open Journal of Business and Management, 04(1):51-59. doi: 10.4236/OJBM.2016.41006
  • Haman, M., & Školník, M. (2023). Using ChatGPT to conduct a literature review. Accountability in Research, 1-3. https://doi.org/10.1080/08989621.2023.2185514
  • Haider, J., & Sundin, O. (2022). Information literacy challenges in digital culture: conflicting engagements of trust and doubt. Information, communication & society, 25(8), 1176-1191.
  • Harris, C. J. (2016) The effective integration of technology into schools’ curriculum. Distance Learning, (2), 27.
  • Hedges, J. (2002). The importance of posting and interaction with the education bureaucracy in becoming a teacher in Ghana. International journal of educational development, 22(3-4), 353-366.
  • Johnson, M., Schuster, M., Le, Q., Krikun, M., Wu, Y., Chen, Z., ... & Chen, Y. (2016). Google's neural machine translation system: Bridging the gap between human and machine translation.
  • Hwang, S., & Shin, J. (2019). Extending technological trajectories to latest technological changes by overcoming time lags. Technological Forecasting and Social Change, 143, 142-153.
  • Iddrisu, D. S., Bashiru, M., & Zakaria, A. (2018). The Impact of Transforming Teacher Education And Learning (T-Tel) In Enhancing Tamale College Of Education Tutors’competencies. Social Science Learning Education Journal, 3(4), 34-37.
  • Kaminski, J. (2011). Diffusion of innovation theory. Canadian Journal of Nursing Informatics, 6(2), 1-6.
  • Kanabar, V. (2023, June). An Empirical Study of Student Perceptions When Using ChatGPT in Academic Assignments. In International Conference on Computer Science and Education in Computer Science (pp. 385-398). Springer Nature Switzerland.
  • Kanbach, D. K., Heiduk, L., Blueher, G., Schreiter, M., & Lahmann, A. (2023). The GenAI is out of the bottle: generative artificial intelligence from a business model innovation perspective. Review of Managerial Science, 1-32.
  • Khalid, U., & Khan, A. (2022). Understanding the Digital Divide in the Contemporary Digital World. Global Political Review, VII(IV):7-14. http://dx.doi.org/10.31703/gpr.2022(vii-iv).02
  • Kouame, B. J. (2012). Improving education with emerging technologies. Trafford Publishing.Latif E, Mai G, Nyaaba M, et al. Artificial General Intelligence (AGI) for Education. arXiv Prepr arXiv230412479. Published online 2023.
  • Lee, M. S., Guo, L. N., & Nambudiri, V. E. (2022). Towards gender equity in artificial intelligence and machine learning applications in dermatology. Journal of the American Medical Informatics Association, 29(2), 400-403.
  • Leese, M. (2010). Bridging the gap: Supporting student transitions into higher education. Journal of further and Higher Education, 34(2), 239-251.
  • Limna, P., Jakwatanatham, S., Siripipattanakul, S., Kaewpuang, P., & Sriboonruang, P. (2022). A review of artificial intelligence (AI) in education during the digital era. Advance Knowledge for Executives, 1(1), 1-9.
  • Liu, Y. (2019). Gender difference in perception and use of social media tools. In Gender and diversity: Concepts, methodologies, tools, and applications (pp. 1845-1858). IGI Global. http://dx.doi.org/10.4018/978-1-5225-6912-1.ch097
  • Mansor, N. A., Hamid, Y., Anwar, I. S. K., Isa, N. S. M., & Abdullah, M. Q. (2022). The awareness and knowledge on artificial intelligence among accountancy students. Int. J. Acad. Res. Bus. Soc. Sci, 12, 1629-1640.
  • Martin, H. (2011). Digital Gender Divide or Technologically Empowered Women in Developing Countries? A Typical Case of Lies, Damned Lies, and Statistics. Social Science Research Network,
  • Molenaar, I. (2022). The concept of hybrid human-AI regulation: Exemplifying how to support young learners’ self-regulated learning. Computers and Education: Artificial Intelligence, 3, 100070.
  • Mosha, G., & Laizer, J. (2021). Undergraduate Students’ Understanding of Plagiarism. Zambia Journal Of Library & Information Science (ZAJLIS), ISSN: 2708-2695, 5(1), 21-33. Retrieved from http://41.63.0.109/index.php/journal/article/view/47.
  • Nazaretsky, T., Cukurova, M., & Alexandron, G. (2022, March). An instrument for measuring teachers’ trust in AI-based educational technology. In LAK22: 12th international learning analytics and knowledge conference (pp. 56-66). https://doi.org/10.1145/3506860.3506866
  • Nketsiah, I., Imoro, O., & Barfi, K. A. (2023). Postgraduate students’ perception of plagiarism, awareness, and use of Turnitin text-matching software. Accountability in Research, 1-17.
  • Nyaaba, M., & Zhai, X. (2024). Generative AI professional development needs for teacher educators. Journal of AI, 8(1), 1-13. https://doi.org/10.61969/jai.1385915
  • Pandey, P., & Pandey, M. M. (2021). Research methodology tools and techniques. Bridge Center.
  • Petersen, J. (2021). Innovative assessment practices. Retrieved on 26 October 2023 from https://www.google.com/url?Innovative-Assessment-Whitepaper1.pdf&usg=AOvVaw1fWCFBStSE4BqDTXT5_Voi.
  • Polat, H. (2023). Transforming Education with Artificial Intelligence: Shaping the Path Forward. ISTES BOOKS, 3-20. Retrieved from https://book.istes.org/index.php/ib/article/view/26
  • Prinzellner, Y., & Simon, A. (2022). Secondary End-Users’ Perspectives on Gender Differences in the Use of eHealth Applications in Older Adults. International Conference on Gender Research, 5(1): pp193-199. doi: 10.34190/icgr.5.1.149
  • Rahman, M. M., & Watanobe, Y. (2023). ChatGPT for education and research: Opportunities, threats, and strategies. Applied Sciences, 13(9), 5783.
  • Rashid, T., & Asghar, H. M. (2016). Full length article: Technology use, self-directed learning, student engagement and academic performance: Examining the interrelations. Computers in Human Behavior, 63604-612. http://dx.doi.org/1016/j.chb.2016.05.084.
  • Rowland, D. R. (2023). Two frameworks to guide discussions around levels of acceptable use of generative AI in student academic research and writing. Journal of Academic Language and Learning, 17(1), T31-T69. https://orcid.org/0000-0001-7854-476X
  • Sok, S., & Heng, K. (2023). ChatGPT for education and research: A review of benefits and risks. Available at SSRN 4378735.
  • Song, Y., & Kapur, M. (2017). How to Flip the Classroom – “Productive Failure or Traditional Flipped Classroom” Pedagogical Design? Educational Technology & Society, 20 (1), 292–305.
  • Tapalova, O., & Zhiyenbayeva, N. (2022). Artificial Intelligence in Education: AIEd for Personalised Learning Pathways. Electronic Journal of e-Learning, 20(5), 639-653.
  • Terwiesch, C. (2023). Would chat GPT3 get a Wharton MBA." A prediction based on its performance in the operations management course. Retrieved from https://mackinstitute.wharton.upenn.edu/wp-content/uploads/2023/01/Christian-Terwiesch-Chat-GTP.pdf
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Yıl 2024, Cilt: 8 Sayı: 1, 45 - 60

Matthew Nyaaba Patrick Kyeremeh Eric Kojo Majialuwe Collins Owusu-fordjour Esther Asebiga Barnabas A-ingkonge

https://doi.org/10.61969/jai.1400867

Öz

Kaynakça

  • Acilar, A., & Sæbø, Ø. (2023). Towards understanding the gender digital divide: A systematic literature review. Global knowledge, memory and communication, 72(3), 233-249. https://doi.org/10.1108/GKMC-09-2021-0147
  • Afful, J. B. A., Ngula, R. S., Twumasi, R., Tetteh, G., & Mensah, F. (2022). Supervisors’ perceptions of postgraduate students’ thesis literature review writing in a Ghanaian university. Advances in Social Sciences Research Journal, 9(1), 267-289. http://dx.doi.org/10.14738/assrj.91.11120
  • Akanzire, B.N., Nyaaba, M. & Nabang, M. (2023). Perceptions and Preparedness: Exploring Teacher Educators' Views on Integrating Generative AI in Colleges of Education, Ghana (November 3, 2023). Available at SSRN: http://dx.doi.org/10.2139/ssrn.4628153
  • Alam, A. (2021, November). Possibilities and apprehensions in the landscape of artificial intelligence in education. In 2021 International Conference on Computational Intelligence and Computing Applications (ICCICA) (pp. 1-8). IEEE. https://doi.org/10.1109/ICCICA52458.2021.9697272
  • Alshater, M. (2022). Exploring the role of artificial intelligence in enhancing academic performance: A case study of ChatGPT. Available at SSRN: https://ssrn.com/abstract=4312358 or http://dx.doi.org/10.2139/ssrn.4312358
  • An, X., Chai, C. S., Li, Y., Zhou, Y., Shen, X., Zheng, C., & Chen, M. (2023). Modeling English teachers’ behavioral intention to use artificial intelligence in middle schools. Education and Information Technologies, 28(5), 5187-5208. https://doi.org/10.1007/s10639-022-11286-z
  • Antonio, A., & Tuffley, D. (2014). The gender digital divide in developing countries. Future Internet, 6(4), 673-687. https://doi.org/10.3390/fi6040673
  • Armah, P. H. (2018). T-TEL Curriculum Reform Study.
  • Armah, P. H. (2017). Teacher education and professional learning in Ghana. The Institute for Education Studies (IFEST): Accra. Recuperado a partir de https://www.academia.edu/34610560/TEACHER_EDUCATION_AND_PROFESSIONAL_LEARNING_IN_GHANA.
  • Ausat, A. M. A., Massang, B., Efendi, M., Nofirman, N., & Riady, Y. (2023). Can chat GPT replace the role of the teacher in the classroom: A fundamental analysis. Journal on Education, 5(4), 16100-16106.
  • Aydin, Ö. (2023). Google Bard generated literature review: metaverse. Journal of AI, 7(1), 1-14.
  • Aydın, Ö., Karaarslan, E. (2022). OpenAI ChatGPT Generated Literature Review: Digital Twin in Healthcare. In Ö. Aydın (Ed.), Emerging Computer Technologies 2 (pp. 22-31). İzmir Akademi Dernegi.
  • Aydin, Ö., & Karaarslan, E. (2023). Is ChatGPT leading generative AI? What is beyond expectations?. Academic Platform Journal of Engineering and Smart Systems, 11(3), 118-134.
  • Azila-Gbettor, E. M., Mensah, C., & Kwodjo Avorgah, S. M. (2015). Challenges of writing dissertations: Perceptual differences between students and supervisors in a Ghanaian polytechnic. International Journal of Education and Practice, 3(4), 182-198. DOI: 10.18488/journal.61/2015.3.4/61.4.182.198
  • Chan, C. K. Y., & Hu, W. (2023). Students' Voices on Generative AI: Perceptions, Benefits, and Challenges in Higher Education. arXiv preprint arXiv:2305.00290.
  • Chen, Y., Chen, Y., & Heffernan, N. (2020). Personalized math tutoring with a conversational agent. arXiv preprint arXiv:2012.12121.
  • Chen X, Zou D, Xie H, Cheng G, Liu C. Two decades of artificial intelligence in education. Educ Technol Soc. 2022;25(1):28-47.
  • Choung, H., David, P., & Ross, A. (2023). Trust in AI and Its Role in the Acceptance of AI Technologies. International Journal of Human–Computer Interaction, 39(9), 1727-1739.
  • Devi, J. S., Sreedhar, M. B., Arulprakash, P., Kazi, K., & Radhakrishnan, R. (2022). A path towards child-centric Artificial Intelligence based Education. International Journal of Early Childhood, 14(3), 9915-9922.
  • Donaldson, J. L., Gallimore, L., & Swanson, D. (2019). National survey of extension 4-H professionals’ perceptions of professional development factors. Journal of extensions, 57(1), 1-14. https://doi.org/10.34068/joe.57.01.27
  • Escotet, M. Á. (2023). The optimistic future of Artificial Intelligence in higher education. Prospects, 1-10.
  • Fisher, A., Exley, K., & Ciobanu, D. (2014). Using technology to support learning and teaching. London: Routledge. https://doi.org/10.4324/9780203074497
  • Goswami, A., & Dutta, S.(2015). Gender Differences in Technology Usage—A Literature Review. Open Journal of Business and Management, 04(1):51-59. doi: 10.4236/OJBM.2016.41006
  • Haman, M., & Školník, M. (2023). Using ChatGPT to conduct a literature review. Accountability in Research, 1-3. https://doi.org/10.1080/08989621.2023.2185514
  • Haider, J., & Sundin, O. (2022). Information literacy challenges in digital culture: conflicting engagements of trust and doubt. Information, communication & society, 25(8), 1176-1191.
  • Harris, C. J. (2016) The effective integration of technology into schools’ curriculum. Distance Learning, (2), 27.
  • Hedges, J. (2002). The importance of posting and interaction with the education bureaucracy in becoming a teacher in Ghana. International journal of educational development, 22(3-4), 353-366.
  • Johnson, M., Schuster, M., Le, Q., Krikun, M., Wu, Y., Chen, Z., ... & Chen, Y. (2016). Google's neural machine translation system: Bridging the gap between human and machine translation.
  • Hwang, S., & Shin, J. (2019). Extending technological trajectories to latest technological changes by overcoming time lags. Technological Forecasting and Social Change, 143, 142-153.
  • Iddrisu, D. S., Bashiru, M., & Zakaria, A. (2018). The Impact of Transforming Teacher Education And Learning (T-Tel) In Enhancing Tamale College Of Education Tutors’competencies. Social Science Learning Education Journal, 3(4), 34-37.
  • Kaminski, J. (2011). Diffusion of innovation theory. Canadian Journal of Nursing Informatics, 6(2), 1-6.
  • Kanabar, V. (2023, June). An Empirical Study of Student Perceptions When Using ChatGPT in Academic Assignments. In International Conference on Computer Science and Education in Computer Science (pp. 385-398). Springer Nature Switzerland.
  • Kanbach, D. K., Heiduk, L., Blueher, G., Schreiter, M., & Lahmann, A. (2023). The GenAI is out of the bottle: generative artificial intelligence from a business model innovation perspective. Review of Managerial Science, 1-32.
  • Khalid, U., & Khan, A. (2022). Understanding the Digital Divide in the Contemporary Digital World. Global Political Review, VII(IV):7-14. http://dx.doi.org/10.31703/gpr.2022(vii-iv).02
  • Kouame, B. J. (2012). Improving education with emerging technologies. Trafford Publishing.Latif E, Mai G, Nyaaba M, et al. Artificial General Intelligence (AGI) for Education. arXiv Prepr arXiv230412479. Published online 2023.
  • Lee, M. S., Guo, L. N., & Nambudiri, V. E. (2022). Towards gender equity in artificial intelligence and machine learning applications in dermatology. Journal of the American Medical Informatics Association, 29(2), 400-403.
  • Leese, M. (2010). Bridging the gap: Supporting student transitions into higher education. Journal of further and Higher Education, 34(2), 239-251.
  • Limna, P., Jakwatanatham, S., Siripipattanakul, S., Kaewpuang, P., & Sriboonruang, P. (2022). A review of artificial intelligence (AI) in education during the digital era. Advance Knowledge for Executives, 1(1), 1-9.
  • Liu, Y. (2019). Gender difference in perception and use of social media tools. In Gender and diversity: Concepts, methodologies, tools, and applications (pp. 1845-1858). IGI Global. http://dx.doi.org/10.4018/978-1-5225-6912-1.ch097
  • Mansor, N. A., Hamid, Y., Anwar, I. S. K., Isa, N. S. M., & Abdullah, M. Q. (2022). The awareness and knowledge on artificial intelligence among accountancy students. Int. J. Acad. Res. Bus. Soc. Sci, 12, 1629-1640.
  • Martin, H. (2011). Digital Gender Divide or Technologically Empowered Women in Developing Countries? A Typical Case of Lies, Damned Lies, and Statistics. Social Science Research Network,
  • Molenaar, I. (2022). The concept of hybrid human-AI regulation: Exemplifying how to support young learners’ self-regulated learning. Computers and Education: Artificial Intelligence, 3, 100070.
  • Mosha, G., & Laizer, J. (2021). Undergraduate Students’ Understanding of Plagiarism. Zambia Journal Of Library & Information Science (ZAJLIS), ISSN: 2708-2695, 5(1), 21-33. Retrieved from http://41.63.0.109/index.php/journal/article/view/47.
  • Nazaretsky, T., Cukurova, M., & Alexandron, G. (2022, March). An instrument for measuring teachers’ trust in AI-based educational technology. In LAK22: 12th international learning analytics and knowledge conference (pp. 56-66). https://doi.org/10.1145/3506860.3506866
  • Nketsiah, I., Imoro, O., & Barfi, K. A. (2023). Postgraduate students’ perception of plagiarism, awareness, and use of Turnitin text-matching software. Accountability in Research, 1-17.
  • Nyaaba, M., & Zhai, X. (2024). Generative AI professional development needs for teacher educators. Journal of AI, 8(1), 1-13. https://doi.org/10.61969/jai.1385915
  • Pandey, P., & Pandey, M. M. (2021). Research methodology tools and techniques. Bridge Center.
  • Petersen, J. (2021). Innovative assessment practices. Retrieved on 26 October 2023 from https://www.google.com/url?Innovative-Assessment-Whitepaper1.pdf&usg=AOvVaw1fWCFBStSE4BqDTXT5_Voi.
  • Polat, H. (2023). Transforming Education with Artificial Intelligence: Shaping the Path Forward. ISTES BOOKS, 3-20. Retrieved from https://book.istes.org/index.php/ib/article/view/26
  • Prinzellner, Y., & Simon, A. (2022). Secondary End-Users’ Perspectives on Gender Differences in the Use of eHealth Applications in Older Adults. International Conference on Gender Research, 5(1): pp193-199. doi: 10.34190/icgr.5.1.149
  • Rahman, M. M., & Watanobe, Y. (2023). ChatGPT for education and research: Opportunities, threats, and strategies. Applied Sciences, 13(9), 5783.
  • Rashid, T., & Asghar, H. M. (2016). Full length article: Technology use, self-directed learning, student engagement and academic performance: Examining the interrelations. Computers in Human Behavior, 63604-612. http://dx.doi.org/1016/j.chb.2016.05.084.
  • Rowland, D. R. (2023). Two frameworks to guide discussions around levels of acceptable use of generative AI in student academic research and writing. Journal of Academic Language and Learning, 17(1), T31-T69. https://orcid.org/0000-0001-7854-476X
  • Sok, S., & Heng, K. (2023). ChatGPT for education and research: A review of benefits and risks. Available at SSRN 4378735.
  • Song, Y., & Kapur, M. (2017). How to Flip the Classroom – “Productive Failure or Traditional Flipped Classroom” Pedagogical Design? Educational Technology & Society, 20 (1), 292–305.
  • Tapalova, O., & Zhiyenbayeva, N. (2022). Artificial Intelligence in Education: AIEd for Personalised Learning Pathways. Electronic Journal of e-Learning, 20(5), 639-653.
  • Terwiesch, C. (2023). Would chat GPT3 get a Wharton MBA." A prediction based on its performance in the operations management course. Retrieved from https://mackinstitute.wharton.upenn.edu/wp-content/uploads/2023/01/Christian-Terwiesch-Chat-GTP.pdf
  • Simhadri, N., & Swamy, T. N. V. R. (2023). Awareness among teaching on AI and ML applications based on fuzzy in education sector at USA. Soft Computing, 1-9.
  • Strzelecki, A. (2023). To use or not to use ChatGPT in higher education? A study of students’ acceptance and use of technology. Interactive Learning Environments, 1-14.
  • Uçar, M. B., & Canpolat, E. (2019). Modelling Preservice Science Teachers’ Environment-Friendly Behaviours. Australian Journal of Teacher Education, 44(2). https://doi.org/10.14221/ajte.2018v44n2.1
  • Van Katwijk, L., Jansen, E., & Van Veen, K. (2023). Pre-service teacher research: A way to future-proof teachers?. European Journal of Teacher Education, 46(3), 435-455.
  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425-478. https://doi.org/10.1080/02619768.2021.1928070.
  • Yidaan, P. Y. N. (2021). Experiences of Students Pursuing a Doctoral Program: Voices From a Private University in Ghana. Pan-African Journal of Education and Social Sciences, 2(2). Retrieved from https://journals.aua.ke/pajes/article/view/112
  • Zhai, X. (2023). ChatGPT and AI: The Game Changer for Education (March 15, 2023). Available at SSRN: https://ssrn.com/abstract=4389098
  • Zhai, X., Nyaaba, M., & Ma, W. (2024). Can generative AI and ChatGPT outperform humans on cognitive-demanding problem-solving tasks in science?. Science & Education, 1-22.https://doi.org/10.1007/s11191-024-00496-1
Toplam 65 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yapay Zeka (Diğer)
Bölüm Research Articles
Yazarlar

Matthew Nyaaba 0000-0002-3341-1055

Patrick Kyeremeh Bu kişi benim 0000-0002-2681-0517

Eric Kojo Majialuwe Bu kişi benim 0009-0002-6237-5599

Collins Owusu-fordjour Bu kişi benim 0000-0003-0323-3638

Esther Asebiga Bu kişi benim 0009-0006-7249-2691

Barnabas A-ingkonge Bu kişi benim 0009-0007-4099-300X

Erken Görünüm Tarihi 25 Nisan 2024
Yayımlanma Tarihi
Gönderilme Tarihi 5 Aralık 2023
Kabul Tarihi 20 Nisan 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 8 Sayı: 1

Kaynak Göster

APA Nyaaba, M., Kyeremeh, P., Majialuwe, E. K., Owusu-fordjour, C., vd. (2024). Generative AI in Academic Research: A Descriptive Study on Awareness, Gender Usage, and Views among Pre-Service Teachers. Journal of AI, 8(1), 45-60. https://doi.org/10.61969/jai.1400867
 Kapak Resmi İndir

Journal of AI
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