ELSA-Supported Blended Learning: Enhancing Vocational Students’ Speaking and Motivation
Abstract
Developing employability-ready English speaking skills remains challenging and persistent in Indonesian vocational schools across contexts. This mixed-methods study investigated the effectiveness of ELSA, an AI-driven speaking app, embedded in a four-week blended course with two weekly 90-minute sessions for 30 Grade-11 Agribusiness students. Surveys (validated), CEFR-aligned observations, and interviews examined gains in pronunciation, fluency, confidence, and motivation, and documented implementation factors. Results show marked improvement in prosody, articulation, and extended turns; learners reported higher confidence, autonomy, and sustained engagement driven by real-time feedback, progress tracking, and gamified tasks. Skills transferred to vocationally authentic performances (e.g., product descriptions, customer service, job-interview simulations). However, efficacy depended on device availability, stable connectivity, digital literacy, and teacher mediation; freemium limits also constrained practice. The study concludes that ELSA-supported blended learning offers a practical, scalable model to strengthen oral proficiency and motivation in vocational EFL programs, provided institutions ensure equitable access, teacher support, and curricular alignment.
Keywords
Full Text:
PDFReferences
Al-Said, K. M. (2021). The effect of gamification on EFL learners’ motivation and engagement. Teaching English with Technology, 21(3), 27–44. https://doi.org/10.5604/01.3001.0014.9775
Arrosagaray, M., González-Peiteado, M., Pino-Juste, M., & Rodríguez-López, B. (2019). A comparative study of Spanish adult students’ attitudes to ICT in classroom, blended and distance language learning modes. Computers & Education, 134, 31–40. https://doi.org/10.1016/j.compedu.2019.01.016
British Educational Research Association. (2018). Ethical guidelines for educational research (4th ed.). https://www.bera.ac.uk/publication/ethical-guidelines-for-educational-research-2018
Burston, J. (2022). Mobile-assisted language learning: A selective annotated bibliography of implementation studies 2018–2021. Language Learning & Technology, 26(2), 1–22. https://doi.org/10.10125/73417
Cambridge Assessment English. (2020). English profile: Common European Framework of Reference (CEFR) descriptors. Cambridge University Press. https://www.cambridgeenglish.org/cefr
Crystal, D. (2020). The Cambridge encyclopedia of the English language (3rd ed.). Cambridge University Press.
Darasawang, P., Reinders, H., & Watson Todd, R. (2023). Mobile applications for language learning: Student perceptions and outcomes. Computer Assisted Language Learning, 36(3), 241–260. https://doi.org/10.1080/09588221.2021.1878236
Deci, E. L., & Ryan, R. M. (2020). Self-determination theory: Basic psychological needs in motivation, development, and wellness (2nd ed.). Guilford Press.
Derakhshan, A., Coombe, C., Zhaleh, K., & Tabatabaeian, M. (2022). Examining the roles of English language teachers in the post-COVID-19 era: A review. The Electronic Journal for English as a Second Language, 26(1), 1–16.
EF Education First. (2023). EF English proficiency index 2023. https://www.ef.com/epi
Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1–4. https://doi.org/10.11648/j.ajtas.20160501.11
Fetters, M. D., Curry, L. A., & Creswell, J. W. (2013). Achieving integration in mixed methods designs: Principles and practices. Health Services Research, 48(6pt2), 2134–2156. https://doi.org/10.1111/1475-6773.12117
Godwin-Jones, R. (2021). Emerging technologies: Digital literacy and autonomous language learning. Language Learning & Technology, 25(3), 1–8. https://doi.org/10.10125/73477
Gusrianto, & Iswahyuni, A. (2023). Improving vocational students’ speaking skills through project-based learning. Journal of English Language Teaching and Linguistics, 8(2), 345–359. https://doi.org/10.21462/jeltl.v8i2.1051
Hashemifardnia, A., Namaziandost, E., & Tavakoli, M. (2023). The role of emotional intelligence in L2 speaking skills: A mixed-methods study. Language Teaching Research. Advance online publication. https://doi.org/10.1177/13621688231162456
Horwitz, E. K. (2016). Becoming a language teacher: A practical guide to second language learning and teaching (2nd ed.). Pearson.
Johnson, R. B., & Onwuegbuzie, A. J. (2004). Mixed methods research: A research paradigm whose time has come. Educational Researcher, 33(7), 14–26. https://doi.org/10.3102/0013189X033007014
Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi Republik Indonesia. (2022). Kurikulum Merdeka: Panduan implementasi untuk SMK. Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi Republik Indonesia.
Khatoony, S., & Nezhadmehr, M. (2020). EFL teachers’ challenges in integration of technology for online classrooms during Coronavirus (COVID-19) pandemic in Iran. The Asian EFL Journal, 27(4.1), 46–73.
Kirkpatrick, A. (2021). World Englishes: Implications for international communication and English language teaching (2nd ed.). Cambridge University Press.
Kukulska-Hulme, A., & Viberg, O. (2018). Mobile collaborative language learning: State of the art. British Journal of Educational Technology, 49(2), 207–218. https://doi.org/10.1111/bjet.12580
Lantolf, J. P., & Thorne, S. L. (2006). Sociocultural theory and the genesis of second language development. Oxford University Press.
Li, Z., Link, S., & Hegelheimer, V. (2021). The impact of automated feedback on ESL learners’ pronunciation: A longitudinal study. Language Learning & Technology, 25(2), 1–21. https://doi.org/10.10125/73415
Miles, M. B., Huberman, A. M., & Saldaña, J. (2014). Qualitative data analysis: A methods sourcebook (3rd ed.). SAGE Publications.
Nguyen, T. T., & Vu, T. T. (2022). Enhancing EFL learners’ speaking skills through AI-based applications. CALL-EJ, 23(2), 55–73.
Organisation for Economic Co-operation and Development. (2021). Digital education outlook 2021: Pushing the frontiers with AI, blockchain and robots. OECD Publishing. https://doi.org/10.1787/589b283f-en
Reinders, H., & Benson, P. (2017). Research agenda: Language learning beyond the classroom. Language Teaching, 50(4), 561–578. https://doi.org/10.1017/S0261444817000192
Richards, J. C. (2015). Key issues in language teaching. Cambridge University Press.
Stockwell, G., & Reinders, H. (2019). Technology, motivation and autonomy. In M. Lamb, K. Csizér, A. Henry, & S. Ryan (Eds.), The Palgrave handbook of motivation for language learning (pp. 1–18). Palgrave Macmillan. https://doi.org/10.1007/978-3-030-28380-3_12
Syam, A., Rahman, F., & Yusuf, F. (2024). Integrating AI tools in EFL classrooms: Effects on learner engagement and speaking proficiency. Asian EFL Journal, 26(1), 102–125.
Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach’s alpha. International Journal of Medical Education, 2, 53–55. https://doi.org/10.5116/ijme.4dfb.8dfd
Ushioda, E. (2011). Motivating learners to speak as themselves. In G. Murray, X. Gao, & T. Lamb (Eds.), Identity, motivation and autonomy in language learning (pp. 11–24). Multilingual Matters.
Widyasari, D., Pratiwi, R., & Nugroho, H. (2023). ELSA Speak in improving students’ pronunciation and speaking confidence. International Journal of Language Education, 7(4), 215–229. https://doi.org/10.26858/ijole.v7i4.45621
Zhai, X., & Wibowo, A. (2023). The role of digital literacy in vocational education: Evidence from Indonesia. Education and Information Technologies, 28(6), 7475–7495. https://doi.org/10.1007/s10639-023-11584-9
DOI: https://doi.org/10.31004/jele.v10i5.1386
Refbacks
- There are currently no refbacks.
Copyright (c) 2025 Wahyudin, Bachtiar, Aminudin Zuhairi
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
