Artificial Intelligence in English Instruction: A TAM-Based Study on Benefits, Challenges, and Ethical Issues
DOI:
https://doi.org/10.31004/basicedu.v9i5.10611Keywords:
Artificial Intelligence (AI), English Instruction, Benefits, Challenges, and EthicsAbstract
The implications of AI’s technology development significantly contribute to educational practice. This study examines the integration of AI in English instruction, focusing on its advantages, challenges, and ethical dimensions. Despite the growing use of AI in education, limited research has addressed its adoption through the Technology Acceptance Model (TAM) while incorporating ethical dimensions. Eighteen educators and students who are highly engaged with AI-powered educational platforms were interviewed using Semi-structured interviews for in-depth exploration of participants' perceptions, experiences, and ethical concerns dealing with AI tools. The collected data were analyzed with thematic analysis. Grounded in the theory of TAM (Technology Acceptance Model), the research explores models such as Perceived Usefulness, Perceived Ease of Use, social influence, and facilitating conditions. The findings reveal the potential of AI to enhance personalized learning and streamline instructional processes, while also highlighting challenges related to cultural nuances, technical barriers, and ethical concerns, including data privacy and algorithm bias. This study integrates ethics as a core determinant within TAM and demonstrates that, unlike prior studies, ease of use remained highly influential in the low-resource Indonesian context, highlighting both contextual sensitivity and the importance of ethical governance in AI adoption for English instruction
References
Akgun, S., & Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI and Ethics, 2(3), 431–440. https://doi.org/10.1007/s43681-021-00096-7
Alcivar, D., Macias, M., & Vera, A. (2024). Integration of Artificial Intelligence in English Teaching. In Integration of Artificial Intelligence in English Teaching. CID - Centro de Investigación y Desarrollo. https://doi.org/10.37811/cli_w1046
Ali Derakhshan, F. G. (2024). Is ChatGPT an evil or an angel for second language education and research? A phenomenographic study of research-active EFL teachers’ perceptions. International Journal of Applied Linguistic, 34(4), 1246–1264.
Aljabr, F. S., & Al-Ahdal, A. A. M. H. (2024). Ethical and pedagogical implications of AI in language education: An empirical study at Ha’il University. Acta Psychologica, 251. https://doi.org/10.1016/j.actpsy.2024.104605
Baker, R. S., & Hawn, A. (2022). Algorithmic Bias in Education. International Journal of Artificial Intelligence in Education, 32(4), 1052–1092. https://doi.org/10.1007/s40593-021-00285-9
Blume, C. (2022). Innovation and Digitalisation of Education in Germany. https://www.sueddeutsche.de/politik/corona-sieben-
Dahri, N. A., Yahaya, N., Al-Rahmi, W. M., Aldraiweesh, A., Alturki, U., Almutairy, S., Shutaleva, A., & Soomro, R. B. (2024). Extended TAM based acceptance of AI-Powered ChatGPT for supporting metacognitive self-regulated learning in education: A mixed-methods study. Heliyon, 10(8). https://doi.org/10.1016/j.heliyon.2024.e29317
Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., & Vayena, E. (2018). AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5
Hennink, M., & Kaiser, B. N. (2022). Sample sizes for saturation in qualitative research: A systematic review of empirical tests. Social Science and Medicine, 292. https://doi.org/10.1016/j.socscimed.2021.114523
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence In Education Promises and Implications for Teaching and Learning. http://bit.ly/AIED-
Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., Santos, O. C., Rodrigo, M. T., Cukurova, M., Bittencourt, I. I., & Koedinger, K. R. (2022). Ethics of AI in Education: Towards a Community-Wide Framework. International Journal of Artificial Intelligence in Education, 32(3), 504–526. https://doi.org/10.1007/s40593-021-00239-1
Johannesen, M., Øgrim, L., & Hatlevik, O. E. (2024). Teachers’ Professional Digital Competence – The Neglected Management of Technology-rich Classrooms? Nordic Journal of Digital Literacy, 19(2), 64–81. https://doi.org/10.18261/NJDL.19.2.2
Miao, F. H. W. R. H. H. Z. (2021). AI and education: guidance for policy-makers. UNESCO. https://doi.org/10.54675/PCSP7350
Nowell, L. S., Norris, J. M., White, D. E., & Moules, N. J. (2017). Thematic Analysis: Striving to Meet the Trustworthiness Criteria. International Journal of Qualitative Methods, 16(1). https://doi.org/10.1177/1609406917733847
Rukmana, M. Y., Abdurrachman Bactiar, F., & Akbar, S. R. (2024). Technology Acceptance Model (TAM) on distance learning in University of Brawijaya. In Journal of Information Technology and Computer Science (Vol. 9, Issue 3). www.jitecs.ub.ac.id
Smith, E. E., & Storrs, H. (2023). Digital literacies, social media, and undergraduate learning: what do students think they need to know? International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00398-2
Vera, F. (2023). Integrating Artificial Intelligence (AI) in the EFL Classroom: Benefits and Challenges. https://orcid.org/0000-0002-4326-1660
Wu, H., Wang, Y., & Wang, Y. (2024). “To Use or Not to Use?” A Mixed-Methods Study on the Determinants of EFL College Learners’ Behavioral Intention to Use AI in the Distributed Learning Context. In International Review of Research in Open and Distributed Learning (Vol. 25).
Yeung, M. W. L., & Yau, A. H. Y. (2022). A thematic analysis of higher education students’ perceptions of online learning in Hong Kong under COVID-19: Challenges, strategies and support. Education and Information Technologies, 27(1), 181–208. https://doi.org/10.1007/s10639-021-10656-3
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? In International Journal of Educational Technology in Higher Education (Vol. 16, Issue 1). Springer Netherlands. https://doi.org/10.1186/s41239-019-0171-0
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