Article Sidebar

Download
PDF
Statistic
Read Counter : 0 Download : 0

Main Article Content

Abstract

This study aimed to explore the integration of a deep learning-based pedagogical approach, teacher self-efficacy, and AI-based instructional media in enhancing students’ motivation in learning English at SMA Muhammadiyah 1 Temanggung. The study investigated how innovative teaching approaches, teachers’ confidence in their instructional abilities, and the integration of artificial intelligence in classroom practices contribute to creating a more engaging, interactive, and student-centered learning environment. The topic was considered important because students’ motivation has become a major challenge in English language learning, particularly in technology-mediated classrooms and non-urban educational settings where learning resources and instructional innovation may still be limited. This research employed a qualitative approach, data were collected through interviews, classroom observations, and focus group discussions involving English teachers and students at SMA Muhammadiyah 1 Temanggung. The collected data were analysed thematically to identify recurring patterns, meanings, and experiences related to students’ motivation in learning English. This study was expected to contribute to the development of more effective, student-centered, and technology-enhanced instructional practices in English language teaching. The findings of this study were also expected to support teachers and educational institutions in developing more adaptive and motivating learning environments for students in the digital era.

Keywords

AI-Based Instructional Media Deep Learning Approach English Language Learning Learning Motivation Teacher Self-Efficacy

Article Details

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

In submitting the manuscript to the FOSTER: Journal of English Language Teaching, the authors certify that:

  • They are authorized by their co-authors to enter into these arrangements.
  • The work described has not been formally published before, except in the form of an abstract or as part of a published lecture, review, thesis, or overlay journal.
  • That it is not under consideration for publication elsewhere,
  • The publication has been approved by the author(s) and by responsible authorities – tacitly or explicitly – of the institutes where the work has been carried out.
  • They secure the right to reproduce any material that has already been published or copyrighted elsewhere.
  • They agree to the following license and copyright agreement.

License and Copyright Agreement

Authors who publish with FOSTER: Journal of English Language Teaching agree to the following terms:

  1. Authors retain copyright and grant the FOSTER: Journal of English Language Teaching right of first publication with the work simultaneously licensed under Creative Commons Attribution License (CC BY 4.0) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
  2. Authors can enter into separate, additional contractual arrangements for the non-exclusive distribution of the FOSTER: Journal of English Language Teaching published version of the work (e.g., post it to an institutional repository or edit it in a book), with an acknowledgement of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) before and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
How to Cite
Novia, S. F., Sutrisno, D., & Sharif, T. I. S. T. (2026). Enhancing Students’ Motivation in English Learning through Deep Learning, Teacher Self-Efficacy, and AI-Based Instruction. FOSTER: Journal of English Language Teaching, 7(3), 268-281. https://doi.org/10.24256/foster-jelt.v7i3.471
Crossref
Scopus
Google Scholar
Europe PMC

References

  1. Akram, M. (2020). Teacher self-efficacy and teaching effectiveness: A review of literature. Journal of Educational Research, 23(2), 45–56.
  2. Alonso-Tapia, J., Merino-Tejedor, E., & Huertas, J. A. (2023). Academic engagement: assessment, conditions, and effects—a study in higher education from the perspective of the person-situation interaction. European Journal of Psychology of Education, 38, 631–655. https://doi.org/https://doi.org/10.1007/s10212-022-00621-0
  3. AlTwijri, L., & Alghizzi, T. M. (2024). Investigating the integration of artificial intelligence in English as foreign language classes for enhancing learners’ affective factors: A systematic review. Heliyon, 10. https://doi.org/https://doi.org/10.1016/j.heliyon.2024.e31053
  4. Bandura, A. (1997). Self-efficacy: The exercise of control. W.H. Freeman.
  5. Biggs, J., & Tang, C. (2021). Teaching for quality learning at university (5th ed.). McGraw-Hill.
  6. Braun, V., & Clarke, V. (2021). Thematic analysis: A practical guide. SAGE Publications.
  7. Chiu, T. K. F., Ahmad, Z., & Çoban, M. (2024). Development and validation of teacher artificial intelligence (AI) competence self-efficacy (TAICS) scale. Education and Information Technologies, 30, 6667–6685. https://doi.org/https://doi.org/10.1007/s10639-024-13094-z
  8. Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry and research design: Choosing among five approaches (4th ed.). SAGE Publications.
  9. Dörnyei, Z. (2021). Motivational strategies in the language classroom. In Cambridge University Press.
  10. Fawzia, S., & Karim, A. (2024). Exploring the connection between deep learning and learning assessments: a cross-disciplinary engineering education perspective. Humanities and Social Sciences Communications, 11. https://doi.org/https://doi.org/10.1057/s41599-023-02542-9
  11. Gligorea, I., Cioca, M., Oancea, R., Gorski, A.-T., Gorski, H., & Tudorache, P. (2023). Adaptive learning using artificial intelligence in e-learning: A literature review. Education Sciences, 13(12). https://doi.org/https://doi.org/10.3390/educsci13121216
  12. Han, J., Geng, X., & Wang, Q. (2021). Sustainable development of university EFL Learners’ engagement, satisfaction, and self-efficacy in online learning environments: chinese experiences. Sustainability, 13(21). https://doi.org/https://doi.org/10.3390/su132111655
  13. Huang, Kuang, F., & Ling, Y. (2022). EFL learners’ engagement in different activities of blended learning environment. Asian-Pacific Journal of Second and Foreign Language Education, 7. https://doi.org/https://doi.org/10.1186/s40862-022-00136-7
  14. Huang, R., Spector, J. M., & Yang, J. (2023). Educational technology and artificial intelligence in education: A review. Educational Technology Research and Development, 71(2), 567–589.
  15. Jerrim, J. (2021). Teacher effectiveness and student outcomes: Evidence from international assessments. Educational Review, 73(4), 421–438.
  16. Lazarides, R., & Warner, L. M. (2020). Teacher self-efficacy. Oxford Research Encyclopedia of Education. https://doi.org/https://doi.org/10.1093/acrefore/9780190264093.013.890
  17. Lee, J. S. (2022). The role of grit and classroom enjoyment in EFL learners’ willingness to communicate. Journal of Multilingual and Multicultural Development, 43(5), 452–468. https://doi.org/https://doi.org/10.1080/01434632.2020.1746319
  18. Lee, J. S., & Hsieh, J. C. (2019). Affective variables and willingness to communicate of EFL learners in in-class, out-of-class, and digital contexts. System, 82, 63–73. https://doi.org/https://doi.org/10.1016/j.system.2019.03.002
  19. Li, L. (2023). Critical thinking from the ground up: teachers’ conceptions and practice in EFL classrooms. Teachers and Teaching, 29(6), 571–593. https://doi.org/https://doi.org/10.1080/13540602.2023.2191182
  20. Liang, W. (2023). Towards a set of design principles for technology-assisted critical-thinking cultivation: A synthesis of research in English language education. Thinking Skills and Creativity, 47. https://doi.org/https://doi.org/10.1016/j.tsc.2022.101203
  21. Lin, C.-C., Huang, A. Y. Q., & Lu, O. H. T. (2023). Artificial intelligence in intelligent tutoring systems toward sustainable education: a systematic review. Smart Learning Environments, 10. https://doi.org/https://doi.org/10.1186/s40561-023-00260-y
  22. Liu, G., & Ma, C. (2024). Measuring EFL learners’ use of ChatGPT in informal digital learning of English based on the technology acceptance model. Innovation in Language Learning and Teaching, 18(2), 125–138. https://doi.org/https://doi.org/10.1080/17501229.2023.2240316
  23. Lo, K. W. K., Ngai, G., Chan, S. C. F., & Kwan, K. (2022). How students’ motivation and learning experience affect their service-learning outcomes: A structural equation modeling analysis. Frontiers in Psychology, 13. https://doi.org/https://doi.org/10.3389/fpsyg.2022.825902
  24. Mulyono, H., & Saskia, R. (2021). Affective variables contributing to IndonesianEFL students’ willingness to communicate withinface-to-face and digital environments. Cogent Education, 8(1). https://doi.org/https://doi.org/10.1080/2331186X.2021.1911282
  25. Namaziandost, E., Çakmak, F., Heydarnejad, T., & Rezai, A. (2024). The predictive effects of learner autonomy and academic engagement on willingness to communicate, foreign language learning self-esteem, and L2 grit in an EFL context. Acta Psychologica, 250. https://doi.org/10.1016/j.actpsy.2024.104528
  26. OECD. (2023). PISA 2022 results (Volume I): The state of learning and equity in education. OECD Publishing.
  27. Patton, M. Q. (2015). Qualitative research & evaluation methods (4th ed.). SAGE Publications.
  28. Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemporary Educational Psychology, 61. https://doi.org/https://doi.org/10.1016/j.cedpsych.2020.101860
  29. UNESCO. (2022). Transforming education from within: Current trends in global education. UNESCO.
  30. Vo, H., & Ho, H. (2024). Online learning environment and student engagement: the mediating role of expectancy and task value beliefs. The Australian Educational Researcher, 51, 2183–2207. https://doi.org/https://doi.org/10.1007/s13384-024-00689-1
  31. Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). SAGE Publications.
  32. Zeng, Y., Wang, Y., & Li, S. (2022). The relationship between teachers’ information technology integration self-efficacy and TPACK: A meta-analysis. Frontiers in Psychology, 13. https://doi.org/https://doi.org/10.3389/fpsyg.2022.1091017