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Articles/Articoli

Vol. 15 No. 2 (2024): Artificial Intelligence in Schools and University Education: Risks and Opportunities

Artificial Intelligence in Education: Perceptions of Teachers in Initial Training

DOI
https://doi.org/10.3280/ess2-2024oa18470
Submitted
settembre 10, 2024
Published
2025-01-31

Abstract

This paper explores the intersection between artificial intelligence (AI) and initial teacher education, focusing on perceptions and self-assessment of competencies in AI technology usage. Despite the increasing integration of AI in education, studies examining the self-assessment of specific technological competencies and perceptions of prospective teachers in this regard are still developing. To this end, a preliminary exploratory study was conducted through a questionnaire administered to 156 first-year students enrolled in the Primary

Education Sciences degree program at the University of Palermo. The results indicate that teachers with greater competencies in AI usage express more positive perceptions regarding its instructional efficacy, while those with lesser competencies highlight concerns related to student stress and additional time required for planning. These differences underscore the importance of adequate training to effectively and conscientiously integrate AI into education.

References

  1. Baidoo-Anu D., Ansah L. O. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1): 52-62.
  2. Bandura A. (2002). Social cognitive theory in cultural context. Applied psychology, 51(2): 269-290.
  3. Celik I., Dindar M., Muukkonen H., and Järvelä S. (2022). The Promises and Challenges of Artificial Intelligence for Teachers: a Systematic Review of Research. TechTrends, 66: 616-630. DOI: 10.1007/s11528-022-00715-y.
  4. Chan C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International journal of educational technology in higher education, 20(1), 38.
  5. Chan C. K. Y., Lee K. K. (2023). The AI generation gap: Are Gen Z students more interested in adopting generative AI such as ChatGPT in teaching and learning than their Gen X and millennial generation teachers?. Smart learning environments, 10(1), 60.
  6. Chounta I. A., Bardone E., Raudsep A., and Pedaste M. (2022). Exploring teachers’ perceptions of Artificial Intelligence as a tool to support their practice in Estonian K-12 education. International Journal of Artificial Intelligence in Education, 32(3): 725-755.
  7. Glaser N. (2023). Exploring the potential of ChatGPT as an educational technology: An emerging technology report. Technology, Knowledge and Learning, 28(4): 1945-1952.
  8. Herft A. (2023). A teacher’s prompt guide to ChatGPT aligned with ‘What Works Best’ guide. https://www.herfteducator.com/.
  9. Hughes C. E., Dieker L. A., Glavey E. M., Hines R. A., Wilkins I., Ingraham K., ... and Taylor, M. S. (2022). RAISE: Robotics & AI to improve STEM and social skills for elementary school students. Frontiers in Virtual Reality, 3, 968312.
  10. Hwang G. J., Chen N. S. (2023). Editorial position paper: Exploring the potential of generative artificial intelligence in education: Applications, challenges, and fu-ture research directions. Educational Technology & Society, 26(2), 18.
  11. Istenic A., Bratko I., and Rosanda V. (2021). Are pre‐service teachers disinclined to utilise embodied humanoid social robots in the classroom?. British Journal of Educational Technology, 52(6): 2340-2358.
  12. Jeon J., Lee S. (2023). Large language models in education: A focus on the complementary relationship between human teachers and ChatGPT. Education and Information Technologies, 28(12): 15873-15892.
  13. Ji H., Han I., and Ko Y. (2023). A systematic review of conversational AI in language education: Focusing on the collaboration with human teachers. Journal of Research on Technology in Education, 55(1): 48-63.
  14. Lin X. F., Chen L., Chan K. K., Peng S., Chen X., Xie S., ... and Hu Q. (2022). Teachers’ perceptions of teaching sustainable artificial intelligence: A design frame perspective. Sustainability, 14(13), 7811.
  15. Lu C., Gu M. M. (2024). Review of research on digital translanguaging among teach-ers and students: A visual analysis through CiteSpace. System, 123, 103314.
  16. Luckin R., Holmes W., Griffiths M., and Forcier L. B. (2016). Intelligence unleashed. An argument for AI in Education. Pearson.
  17. Lucy L., Bamman D. (2021, June). Gender and representation bias in GPT-3 generated stories. In Proceedings of the Third Workshop on Narrative Understanding (pp. 48-55). DOI: 10.18653/v1/2021.nuse-1.5.
  18. Mingyeong J. A. N. G., Lee H. W. (2023). Pre-service Teachers’ Education Needs for AI-Based Education Competency. Educational Technology International, 24(2): 143-168.
  19. Murgia E., Bruni F. (2023). ChatGPT or not ChatGPT in education? A preliminary investigation at the university among prospective teachers. In L. Perla, L.S. Agra-ti, V. Vinci, and A. Scarinci (Eds.), Living and Leading in the Next Era: Connect-ing Teaching, Research, Citizenship and Equity. Lecce: Pensa MultiMedia.
  20. Nikolic S., Daniel S., Haque R., Belkina M., Hassan G. M., Grundy S., ... and Sandison C. (2023). ChatGPT versus engineering education assessment: a multidisciplinary and multi-institutional benchmarking and analysis of this generative artificial intelligence tool to investigate assessment integrity. European Journal of Engi-neering Education, 48(4): 559-614.
  21. Pitrella V., Gentile M., Città G., Re A., Tosto C., and Perna S. (2023). La percezione dell’utilizzo dell’intelligenza artificiale nello svolgimento dei compiti a casa in un campione di insegnanti italiani. Annali online della Didattica e della Formazione Docente, 15(26): 300-318.
  22. Popenici S. A., Kerr S. (2022). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 17(1): 1-13. DOI: 10.1186/s41039-021-00175-7.
  23. Ratten V., Jones P. (2021). Covid-19 and entrepreneurship education: Implications for advancing research and practice. The International Journal of Management Education, 19(1), 100432. DOI: 10.1016/j.ijme.2020.100432.
  24. Rawas S. (2023). ChatGPT: Empowering lifelong learning in the digital age of higher education. Education and Information Technologies, 1-14.
  25. Salas-Pilco S. Z., Xiao K., and Hu X. (2023). Correction: Salas-Pilco et al. Artificial Intelligence and Learning Analytics in Teacher Education: A Systematic Review. Education Science, 13(9), 897.
  26. Scherer R., Howard S. K., Tondeur J., and Siddiq F. (2021). Profiling teachers’ readiness for online teaching and learning in higher education: Who’s ready?. Computers in Human Behavior, 118, 106675. DOI: 10.1016/j.chb.2020.106675.
  27. Scherer R., Siddiq F., and Tondeur J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers & education, 128: 13-35.
  28. Song A., Ko J. (2024). Preservice ethics teachers’ perceptions of AI ethics education. Journal of Moral Education, 1-24. DOI: 10.1080/03057240.2024.2393353.
  29. Sullivan M., Kelly A., and McLaughlan P. (2023). ChatGPT in higher education: Considerations for academic integrity and student learning. Journal of Applied Learning & Teaching, 6(1), 1-10.
  30. Tallvid M. (2016). Understanding teachers’ reluctance to the pedagogical use of ICT in the 1: 1 classroom. Education and Information Technologies, 21: 503-519.
  31. Tondeur J., Van Braak J., Ertmer P. A., and Ottenbreit-Leftwich A. (2017). Understanding the relationship between teachers’ pedagogical beliefs and technology use in education: A systematic review of qualitative evidence. Educational technology research and development, 65: 555-575.
  32. Trust T., Whalen J. (2021). Emergency remote teaching with technology during the COVID-19 pandemic: Using the whole teacher lens to examine educator’s experiences and insights. Educational Media International, 58(2): 145-160. DOI: 10.1080/09523987.2021.1930479.
  33. van den Berg G., du Plessis E. (2023). ChatGPT and generative AI: Possibilities for its contribution to lesson planning, critical thinking and openness in teacher education. Education Sciences, 13(10), 998.
  34. Zawacki-Richter O., Marín V. I., Bond M., and Gouverneur F. (2022). Systematic review of research on artificial intelligence applications in higher education – where are the educators?. International Journal of Educational Technology in Higher Education, 19(1): 1-39. DOI: 10.1186/s41239-021-00312-8.
  35. Zhang H., Lee I., Ali S., DiPaola D., Cheng Y., and Breazeal C. (2023). Integrating ethics and career futures with technical learning to promote AI literacy for middle school students: An exploratory study. International Journal of Artificial Intelligence in Education, 33(2): 290-324.
  36. Zimmerman J. (2006). Why some teachers resist change and what principals can do about it. Nassp Bulletin, 90(3): 238-249.

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