Exploring EFL Students' Needs in English for Online Business Course through AI Learning Analytics
Article Sidebar
Main Article Content
Abstract
The rapid transformation from the traditional to the digital business world has created new challenges for English for Specific Purposes education. The lack of appropriate course books for online business English communication requires a systematic investigation of need analysis and learning analytics to guide curriculum and material development in current digital business education. This paper, therefore, aims to explore Thai EFL university students’ perceived needs on “English for Online Business” and to develop an English for Online Business course for EFL university students by using AI learning analytics. Fifty-nine participants were voluntarily asked to complete a needs analysis questionnaire with open-ended questions reporting what high-priority or low-priority needs of English language skills were perceived by these Thai university students. The data obtained from the questionnaire were first analyzed by frequency, percentage, and standard deviation. The findings showed the top three high-priority needs perceived by students, including reading product details, writing promotional posts on social media, and listening to customers’ feedback. The students’ responses were also thematically categorized into two domains: business English communication and international online business platforms. Three data sets (needs analysis, the students’ English proficiency levels, and the course description) were processed by using AI learning analytics, suggesting the teaching methods, activities, and materials for the mixed-ability group. This paper proposes AI learning analytics to enhance English language learning and tailor the English course. Limitations and recommendations for practical implementation guidelines are also discussed.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
This article is published under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0), which allows others to share the article with proper attribution to the authors and prohibits commercial use or modification. For any other reuse or republication, permission from the journal and the authors is required.References
Aizawa, I. (2023). Online meeting competence and learner engagement in digital classrooms: Implications for ESP needs analysis. Journal of Language Teaching and Research, 14(2), 112–125.
Alavi, S. (2024). Designing sustainable ESP curricula through outcomes-based education: A mixed-method study. English for Specific Purposes Journal, 65, 54–70.
Alhasani, A. (2024). Revisiting needs analysis in English language education: New erspectives and emerging trends. International Journal of Research and Innovation in Social Science, 8(5), 1335–1342.
Antoniak, M. (2023). Using large language models with care. AI2 Blog. Retrieved 22 June 2022, From https://blog.allenai.org/using-large-language-models-with-care-eeb17b0aed27
Bangkok University. (2024). Bachelor of Arts program in Business English (International Program) [Degree plan and curriculum]. Bangkok University. Retrieved 1 February 2025, from https://contents.bu.ac.th/contents/files /uploads/department-20240918050442.pdf
Barghamadi, M. (2020). A critical study of the principles and approaches to needs analysis. Studies in English Language and Media, 7, 1–16.
Buasuwan, P. (2018). Rethinking Thai higher education for Thailand 4.0. Asian Education and Development Studies, 7(2), 157–173.
Chavangklang, T., & Chavangklang, P. (2024). Exploring the Impact of AI and Digital Tools on EFL Writing Instruction in Higher Education: A Meta-Analysis of Global and Thai Contexts. Jayaphuekpirom Journal, 6(2), 80-93.
Cheng, A. (2022). Medium of instruction in Hong Kong secondary schools: Integrating L1 in English-medium classrooms. Asian Englishes, 24(1), 2-8.
Chonraksuk, J., & Boonlue, S. (2024). Development of an AI predictive model to categorize and predict online learning behaviors of students in Thailand. Heliyon, 10(11), 1-10.
Crocco, O. S., & Pitiyanuwat, S. (2022). Higher education in Thailand. In C. S. Lee (Ed.), International handbook on education in Southeast Asia (pp. 1–24). Springer Nature Singapore.
Deng, Y. (2024). Developing ESP speaking modules for Chinese business undergraduates: Insights from needs analysis. English Language Teaching, 17(1), 75–89.
Dugošija, T. (2024). Benefits and challenges of AI in English language teaching. Knowledge - International Journal, 62(2), 275–280. https://ojs.ikm.mk/ index.php/kij/article/view/6590
Eden, C. A., Chisom, O. N., & Adeniyi, I. S. (2024). Integrating AI in education: Opportunities, challenges, and ethical considerations. Magna Scientia Advanced Research and Reviews, 10(2), 006-013.
Fang, B., & Broussard, K. (2024). Augmented course design: Using AI to boost efficiency and expand capacity. Educause Review, Teaching and Learning. Retrieved 12 February 2025, from https://er.educause.edu/articles/2024/8/augmented -course-design-using-ai-to-boost-efficiencyand-expand-capacity.
Gayed, J. M. (2025). Educators’ perspective on artificial intelligence: equity, preparedness, and development, Cogent Education, 12(1), 1-21. DOI: 10.1080/2331186X.2024.2447169
Huang, L., Yu, W., Ma, W., Zhong, W., Feng, Z., Wang, H., Chen, Q., Peng, W., Feng, X., Qin, B., & Liu, T. (2023). A survey on hallucination in large language models: Principles, taxonomy, Retrieved 1 February 2025, from https://arxiv.org/abs/ 2311.05232
Hutchinson, T., & Waters, A. (1987). English for specific purposes: A learning-centred approach. UK: Cambridge University Press.
Jacqueline, A. A. (2024). Digital literacy in the 21st century: preparing students for the future workforce. Res. Output J. Arts Manage, 3(3), 40-43.
Khan, N., Sarwar, A., Chen, T. B., & Khan, S. (2022). Connecting digital literacy in higher education to the 21st-century workforce. Knowledge Management & E-Learning, 14(1), 46–61.
Komalasari, A. (2021). Developing 21st century education and digital literacy skills through intercultural city stories project. PIONEER: Journal of Language and Literature, 13(1), 1–15.
Liu, J. (2024). Enhancing English language education through big data analytics and generative AI. Journal of Web Engineering, 23(2), 227-249.
Liu, W. (2025). Language teacher AI literacy: insights from collaborations with ChatGPT. J. China Comput. Assist. Lang. Learn, 2025, 1-30. https://doi.org/10. 15 15 /jccall-2024-0030
Liu, X. (2024). Online learning based on learning analytics in big data for college English Language Teaching. International Journal of Computational Intelligence Systems, 17(1), 192-207.
Moorhouse, B. L. (2024). Beginning and first-year language teachers’ readiness for the generative AI age. Computers and Education: Artificial Intelligence, 6(100201), 1-8. https://doi.org/10.1016/j.caeai.2024.10020
Rajamangala University of Technology Lanna. (2023, November 10). English for online business. Learning Management System of RMUTL. Retrieved February 1, 2025, from https://lms.rmutl.ac.th/tqf/detail/27453953985913624/8c2447 587ba32968884a3f3634
Rajamangala University of Technology Rattanakosin. (2025). Bachelor of Business Administration program in Business English. BUA, RMUTR. Retrieved February 6, 2025, from https://bua.rmutr.ac.th/wpcontent/uploads/2022/07/bua_ bpc_rmutr_c_eng.pdf
Srisa-Ard, B. (2003). Research for teachers. Bangkok: Suweeviriyasarn.
Su, J., & Zhong, Y. (2025). Reimagining teacher development in the era of generative AI: A scoping review. Teaching and Teacher Education, 151, 1-11. https://doi.org/10.1016/j.tate.2025.104654
Susanti, R. (2023). Digital marketing students’ English needs: A mixed-method needs analysis. Indonesian Journal of Applied Linguistics, 13(1), 21–38.
Thammasat University. (2023). Minors program in English for Professional Communication [Curriculum revised 2023]. Institute of Language and Communication, Thammasat University. Retrieved 6 February 2025, from https://www.reg.tu.ac.th/en/ Picture /AttFile/a0d89085-bbde-44409535-f62690120984
Thompson, K., Liao, H., & Al-Saleem, S. (2025). Upskilling teachers to use generative artificial intelligence. Australasian Journal of Educational Technology, 41(1), 1–18. https://doi.org/10.14742/ajet.9652
Ubon Ratchathani University. (2025). Bachelor of Arts (English for Digital Age Business). Faculty of Humanities, Ubon Ratchathani University. Retrieved 6 May 2025, from https://www.la.ubu.ac.th/courses/docs/engdigi.pdf
Waluyo, B., & Kusumastuti, S. (2024). Generative AI in student English learning in Thai higher education: More engagement, better outcomes? Social Sciences & Humanities Open, 10(101146), 1-10. https://doi.org/10.1016/j.ssaho.2024. 101146
Yan, L., Greiff, S., Teuber, Z., & Gašević, D. (2024). Promises and challenges of generative artificial intelligence for human learning. Nature Human Behaviour, 8(10), 1839–1850. https://doi.org/10.1038/s41562-024-02004-5
Zaman, B. U. (2024). The weighty responsibility of creating AI navigating control and ethics. Retrieved 6 May 2025, from https://doi.org/10.20944/preprints20 2404.1900.v1
