AI-supported classroom planning, student engagement, and EFL achievement

Evidence from a pretest–posttest study in India

Authors

DOI:

https://doi.org/10.32674/ctxwbc05

Keywords:

AI-based classroom planning;, ESL achievement;, student engagement;, classroom climate;, mediation analysis;, multilingual education;, transnational learning;

Abstract

This study examines the association between AI-based classroom planning and classroom climate and English as a foreign language (EFL) achievement among 240 secondary school students in West Bengal, India, with student engagement as a mediating variable. A single-group pretest–posttest design was employed across a three-week AI-supported intervention. Using SPSS 26 and AMOS 26, paired-sample t tests revealed statistically significant pre to-post improvements in classroom climate (t(239) = −76.90, p < .001, d = −4.96), student engagement (t(239) = −64.46, p < .001, d = −4.16), and EFL achievement (t(239) = −61.77, p < .001, d = −3.99). These effect sizes are unusually large and should be interpreted cautiously given the single-group design, short intervention duration, and potential testing and novelty effects. Structural equation modeling (SEM) confirmed partial mediation via student engagement (β = .479, p = .001, 95% CI [.320, .641]), explaining 63.3% of the variance in EFL achievement. These findings offer a scalable, evidence-based model for AI-supported language pedagogy in underresourced, multilingual EFL contexts in the Global South.

Author Biographies

  • Palash Majumder, Lovely Professional University, India

    PALASH MAJUMDER is a Research Scholar in the School of Education at Lovely Professional University, Phagwara, Punjab, India. His major research interests lie in the areas of educational technology, psychometrics, English language teaching, student engagement and parental involvement in educational research. Email: rajumajumder56@gmail.com

     

  • Nimisha Beri, National Council of Educational Research and Training, New Delhi, India

    NIMISHA BERI, PhD, is an Associate Professor in the Department of Teacher Education at the National Council of Educational Research and Training (NCERT), New Delhi, India. Her major research interests lie in the areas of teacher education, educational psychology, and language pedagogy.

     

     
  • Narendra Kumar, Central University of Rajasthan, India

    NARENDRA KUMAR, PhD, is an Assistant Professor in the Department of Education at the Central University of Rajasthan, India. His major research interests include educational assessment, curriculum studies, and technology-enhanced learning.

References

Bannister, P., Alcalde Peñalver, E., & Santamaría Urbieta, A. (2024). International students and generative artificial intelligence: A cross-cultural exploration of higher education academic integrity policy. Journal of International Students, 14(3), 149–170. https://doi.org/10.32674/jis.v14i3.6277

Chiu, T. K. F., Moorhouse, B. L., Chai, C. S., & Ismailov, M. (2024). Teacher support and student motivation to learn with artificial intelligence (AI) based chatbot. Interactive Learning Environments, 32(7), 3240–3256. https://doi.org/10.1080/10494820.2023.2172044

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.

Cummins, J. (2000). Language, power and pedagogy: Bilingual children in the crossfire. Multilingual Matters.

Derakhshan, A., Fathi, J., Pawlak, M., & Kruk, M. (2022). Classroom social climate, growth language mindset, and student engagement: The mediating role of boredom in learning English as a foreign language. Journal of Multilingual and Multicultural Development, 45(8), 3415–3433. https://doi.org/10.1080/01434632.2022.2099407

Duffy, L., & Binghang, L. (2026). “It’s easier talking to a machine”: Privacy, motivation, and the underuse of English language labs in a Sino-foreign university in China. Journal of International Students, 16(10), 89–104. https://doi.org/10.32674/g5wkva87

Duke, B. (2026). Artificial intelligence for inclusive and sustainable international education: A critical conceptual review. Journal of International Students, 16(10), 167–198. https://doi.org/10.32674/96t36095

Fraser, B. J. (2015). Classroom learning environments. In R. Gunstone (Ed.), Encyclopedia of science education (pp. 154–157). Springer. https://doi.org/10.1007/978-94-007-2150-0_186

Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59–109. https://doi.org/10.3102/00346543074001059

Guo, Y., & Wang, Y. (2025). Exploring the effects of artificial intelligence application on EFL students’ academic engagement and emotional experiences: A mixed-methods study. European Journal of Education, 60(1), Article e12812. https://doi.org/10.1111/ejed.12812

Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.

Ittefaq, M., Zain, A., Arif, R., Ahmad, T., Khan, L., & Seo, H. (2025). Factors influencing international students’ adoption of generative artificial intelligence: The mediating role of perceived values and attitudes. Journal of International Students, 15(7), 127–156. https://doi.org/10.32674/fnwdpn48

Kukulska-Hulme, A. (2009). Will mobile learning change language learning? ReCALL, 21(2), 157–165. https://doi.org/10.1017/S0958344009000202

Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.

Muthee, J. M. (2009). Classroom climate inventory [Measurement instrument]. Department of Psychology, University of Kerala.

Reschly, A. L., & Christenson, S. L. (2012). Jingle, jangle, and conceptual haziness: Evolution and future directions of the engagement construct. In S. L. Christenson, A. L. Reschly, & C. Wylie (Eds.), Handbook of research on student engagement (pp. 3–19). Springer. https://doi.org/10.1007/978-1-4614-2018-7_1

Reyes, M. R., Brackett, M. A., Rivers, S. E., White, M., & Salovey, P. (2012). Classroom emotional climate, student engagement, and academic achievement. Journal of Educational Psychology, 104(3), 700–712. https://doi.org/10.1037/a0027268

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, Article 101860. https://doi.org/10.1016/j.cedpsych.2020.101860

Sharma, H., & Chowdhry, M. (2022). Student engagement scale [Measurement instrument]. National Psychological Corporation.

Thapa, A., Cohen, J., Guffey, S., & Higgins-D’Alessandro, A. (2013). A review of school climate research. Review of Educational Research, 83(3), 357–385. https://doi.org/10.3102/0034654313483907

UNESCO. (2021). Recommendation on the ethics of artificial intelligence. United Nations Educational, Scientific and Cultural Organization. https://unesdoc.unesco.org/ark:/48223/pf0000381137

Wang, M.-T., Degol, J. L., Amemiya, J., Parr, A., & Guo, J. (2020). Classroom climate and children’s academic and psychological wellbeing: A systematic review and meta-analysis. Developmental Review, 57, Article 100912. https://doi.org/10.1016/j.dr.2020.100912

Wei, L. (2023). Artificial intelligence in language instruction: Impact on English learning achievement, L2 motivation, and self-regulated learning. Frontiers in Psychology, 14, Article 1261955. https://doi.org/10.3389/fpsyg.2023.1261955

Xu, J., & Li, J. (2024). Effects of AI affordances on student engagement in EFL classrooms: A structural equation modeling and latent profile analysis. European Journal of Education, 59(4), Article e12808. https://doi.org/10.1111/ejed.12808

Yılmaz Bodur, Z., Kılıç, A. F., & Aktan, S. (2023). Perceived instructional environment and English achievement: The mediating role of student engagement. The Journal of Educational Research, 116(2), 100–112. https://doi.org/10.1080/00220671.2023.2203093

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? International Journal of Educational Technology in Higher Education, 16(1), Article 39. https://doi.org/10.1186/s41239-019-0171-0

Zhang, H., Du, L., Luo, S., Xun, H., Yang, A., & Tang, Y. (2025). Unlocking EFL achievement through informal digital learning: The mediating roles of anxiety and enjoyment among school-age students in the Chinese mainland. Asian-Pacific Journal of Second and Foreign Language Education, 10(1), Article 45. https://doi.org/10.1186/s40862-025-00352-x

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Published

2026-08-19

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Vol. 16 No. 18 (2026): Journal of International Students

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Research Articles (English, regular edition)

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Copyright (c) 2026 Palash Majumder, Nimisha Beri, Narendra Kumar

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

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How to Cite

Majumder, P., Beri, N., & Kumar, N. (2026). AI-supported classroom planning, student engagement, and EFL achievement: Evidence from a pretest–posttest study in India. Journal of International Students, 16(18), 127-142. https://doi.org/10.32674/ctxwbc05