The Effects of AI Tools, Self-Efficacy, and Speaking Anxiety on English Speaking Performance Among TEFL Undergraduate Students

Authors

  • Hou Malika Build Bright University, Cambodia
  • Tang Kimleng Build Bright University, Cambodia
  • Raya Sonysa Build Bright University, Cambodia
  • Heang Pichchansonita Build Bright University, Cambodia
  • Chhen Sela Build Bright University, Cambodia

DOI:

https://doi.org/10.53103/cjlls.v6i6.317

Keywords:

AI Tools, Communicative Competence, English Speaking Performance, Self-Efficacy, Speaking Anxiety, TEFL Undergraduates

Abstract

The purpose of this study was to examine the direct and indirect effects of AI tool use, speaking self-efficacy, foreign language speaking anxiety, and English speaking performance among Cambodian Teaching English as a Foreign Language (TEFL) undergraduates. Guided by Bandura's Social Cognitive Theory and Krashen's Affective Filter Hypothesis, a cross-sectional predictive and mediational survey design was employed with 129 TEFL pre-service teachers from university campuses in Battambang and Banteay Meanchey. A 45-item questionnaire measuring four constructs (AI tool use, speaking self-efficacy, foreign language speaking anxiety, and English speaking performance) on a four-point Likert scale was used to collect data. The descriptive results showed moderate-to-high levels of AI tool use (M = 2.86), speaking self-efficacy (M = 2.83), speaking anxiety (M = 2.71), and self-perceived speaking performance (M = 2.80). AI tool use was positively associated with speaking performance (r = .248, p < .01), self-efficacy (r = .343, p < .001), and anxiety (r = .384, p < .001); self-efficacy was highly correlated with speaking performance (r = .735, p < .001). AI tool use was a significant predictor of performance after controlling for the other predictors (R² = .541, β = .729, p < .001), but only self-efficacy was a direct predictor. Mediation analysis supported an indirect relationship between AI tool use and performance through self-efficacy (B = 0.209, SE = 0.054, Sobel z = 3.866, p < .001). The findings suggest that AI tools may enhance speaking performance through self-efficacy, rather than independently, and highlight the need for confidence-building activities when integrating AI into TEFL curricula. The cross-sectional, self-report design, however, limits causal interpretation.

References

Ballıdağ, M., & Aydın, S. (2025). A comparison of the effects of AI-based chatbots and peer interactions on speaking anxiety among EFL learners. Future in Educational Research, 3(2), 224–238. https://doi.org/10.1002/fer3.70005

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall.

Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman.

Bandura, A. (2006). Guide for constructing self-efficacy scales. In F. Pajares & T. Urdan (Eds.), Self-efficacy beliefs of adolescents (pp. 307–337). Information Age Publishing.

Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182. https://doi.org/10.1037/0022-3514.51.6.1173

Canale, M., & Swain, M. (1980). Theoretical bases of communicative approaches to second language teaching and testing. Applied Linguistics, 1(1), 1–47. https://doi.org/10.1093/applin/I.1.1

Celce-Murcia, M. (2007). Rethinking the role of communicative competence in language teaching. In E. A. Soler & M. P. S. Jordà (Eds.), Intercultural language use and language learning (pp. 41–57). Springer. https://doi.org/10.1007/978-1-4020-5639-0_3

Creswell, J. W., & Creswell, J. D. (2023). Research design: Qualitative, quantitative, and mixed methods approaches (6th ed.). SAGE Publications.

Dörnyei, Z., & Dewaele, J. (2022). Questionnaires in second language research: Construction, administration, and processing (3rd ed.). Routledge. 182. https://doi.org/10.4324/9781003331926

Fahri, M., Mahfuzo, M.R., & Badry, A. (2025). Foreign Language Enjoyment, Self-Efficacy, and Willingness to Communicate: Evidence from Arabic Language Education Students. Jurnal Pendidikan Bahasa Arab dan Kebahasaaraban, 4(2). https://doi.org/10.15575/ta.v4i2.49443

Faradiba, A.W., Dollah, S., & Bakri, F. (2025). Types of Speaking Anxiety Experienced by EFL Students During Classroom Presentations: A Case Study at IAIN Bone. International Journal of Language, Education, and Literature (IJLEL), 2(1), 34-36. https://journal.unm.ac.id/index.php/IJLEL/index

Feng. L. (2024). Investigating the Effects of Artificial Intelligence-Assisted Language Learning Strategies on Cognitive Load and Learning Outcomes: A Comparative Study. Journal of Educational Computing Research, 62 (8). https://doi.org/10.1177/07356331241268349

Griche, M.S. & Bennis, M. (2026). Generative artificial intelligence integration in foreign language education in higher education: A systematic literature review. Technology in Language Teaching & Learning, 8. https://doi.org/10.29140/tltl.2026.102827

Heng, K., & Doeur, B. (2022). Digital transformation and technology adoption in Cambodian higher education: Challenges, opportunities, and future prospects. Cambodian Journal of Education, 2(1), 1102–1117. https://doi.org/10.62037/cjer.2022.02.01.09

Horwitz, E. K., Horwitz, M. B., & Cope, J. (1986). Foreign language classroom anxiety. The Modern Language Journal, 70(2), 125–132. https://doi.org/10.2307/327317

Huang, Y., & Kakham, P. (2026) The impacts of AI conversational agents on EFL learners' oral proficiency and foreign language speaking anxiety. Front. Educ. https://doi.org/10.3389/feduc.2026.1799269

Huang, X., Zou, D., Cheng, G., & Xie, H. (2023). Trends and research issues of AI in language education: A systematic review and research agenda. Educational Technology & Society, 26(1), 112–131.

Istikharoh, L. & Utami, S.Y. (2024). EFL students' self-efficacy in technology-assisted language learning. Journal of Language, Education, and Humanities, 12(1). https://doi.org/10.22373/ej.v12i1.23920

Keo, V., & Lan, B. (2025). Exploring Educational Technology Integration in Cambodian Higher Education: Challenges and Opportunies. The Journal of English Teaching for Young and Adult Learners, 4(2), 56-75.

Kline, R. B. (2023). Principles and practice of structural equation modeling (5th ed.). Guilford Press.

Krashen, S. (1982). Principles and practice in second language acquisition. Pergamon Press.

Kuluşaklı, E., & Genç, G. (2024). Exploring the potential of ChatGPT in developing English speaking skills: A mixed-methods study. Arab World English Journal, 15(1), 32–48. https://doi.org/10.24093/awej/vol15no1.3

Li, Y., Zhou, X., Yin, Hb. et al. (2025). Design language learning with artificial intelligence (AI) chatbots based on activity theory from a systematic review. Smart Learn. Environ. 12, 24. https://doi.org/10.1186/s40561-025-00379-0

Lai, C.Y., Cheung, K.Y., & Chan, C.S. (2023). Exploring the role of intrinsic motivation in ChatGPT adoption to support active learning: An extension of the technology acceptance model. Computers and Education: Artificial Intelligence, 5. https://doi.org/10.1016/j.caeai.2023.100178

Luoma, S. (2004). Assessing speaking. Cambridge University Press. https://doi.org/10.1017/CBO9780511733017

MacIntyre, P. D. (2017). An overview of language anxiety research and trends in its development. In C. Gkonou, M. Daubney, & J. M. Dewaele (Eds.), New insights into language anxiety: Theory, research and educational implications (pp. 11–30). Multilingual Matters. https://doi.org/10.21832/9781783097722-003

Moorhouse, B.L. (2024). Beginning and first-year language teachers’ readiness for the generative AI age. Computers and Education: Artificial Intelligence, 6. https://doi.org/10.1016/j.caeai.2024.100201

Peng, Q. & Shuhong, L. (2025) Emotional factor matters in language learning? A meta-analysis of emotional intelligence on language achievement. Front. Psychol. 16:1502112. https://doi.org/10.3389/fpsyg.2025.1502112

Neupane, B.P., Paudel, P., Dahal, N., Karki, S., & Paudel, G.R. (2025). English Language Teaching in the Age of Artificial Intelligence: Tools, Techniques, and Methodologies. Advances in Mobile Learning Educational Research, 5 (1). https://doi.org/10.25082/AMLER.2025.01.011

Shazly, R.E. (2021). Effects of artificial intelligence on English speaking anxiety and speaking performance: A case study. Expert Systems. https://doi.org/10.1111/exsy.12667

Shen, J., Qian, B., Ma, Q., & Deris, F.D. (2025). Exploring the Impact of AI-Assisted Speaking Practice on EFL Learners' Speaking Proficiency and Motivation: A Mixed-Method Study. International Journal of Academic Research in Progressive Education and Development, 43-52. http://dx.doi.org/10.6007/IJARPED/v14-i4/26672

Sobel, M. E. (1982). Asymptotic intervals for indirect effects in structural equations models. Sociological Methodology, 13, 290–312. https://doi.org/10.2307/270723

Sol, K., Heng, K., & Sok, S. (2025). Using ai in English language learning: An exploration of Cambodian efl university students’ experiences and perceptions. Journal of Science of Learning and Innovations, 2(2), 113-144. https://doi.org/10.1163/29497736-bja00015

Sonsaat-Hegelheimer, S., & Kurt, S. The impact of generative AI-powered chatbots on L2 comprehensibility. Journal of Second Language Pronunciation, 10 (3), 339-374. https://doi.org/10.1075/jslp.24053.son

Torres, P.J. & Kahveci, Y.E. (2025). Effectiveness of Artificial Intelligence (AI) in language teaching. Computers and Education: Artificial Intelligence, 9. 10.1016/j.caeai.2025.100522

Wang, C. & Sun, T. (2020). Relationship between self-efficacy and language proficiency: A meta-analysis. System, 95. https://doi.org/10.1016/j.system.2020.102366

Wang, C., Zou, B., Du, Y. & Wang, Z. (2024). The impact of different conversational generative AI chatbots on EFL learners: An analysis of willingness to communicate, foreign language speaking anxiety, and self-perceived communicative competence. System, 127. https://doi.org/10.1016/j.system.2024.103533

Wang, Z., Zou, D., Lee, L.K., Xie, H., & Wang, F.L. ((2023). A Systematic Review of Generative Artificial Intelligence in Language Education. International Conference on Computers in Education. https://doi.org/10.58459/icce.2023.1199

Xia, Q., Aldharman, N.S. & Chiu, T.K.F. (2026). How Do Autonomy, Critical Thinking, and Artificial Intelligence Value Perception Affect University Student Self-regulated Learning?. TechTrends 70, 902–911. https://doi.org/10.1007/s11528-026-01203-3

Xu, S., Su, Y. & Liu, K. (2025). Investigating student engagement with AI-driven feedback in translation revision: A mixed-methods study. Educ Inf Technol 30, 16969–16995. https://doi.org/10.1007/s10639-025-13457-0

Yang, K., & Gan, Z. (2024). A systematic review of reading self-efficacy in second or foreign language learning. System, 125. https://doi.org/10.1016/j.system.2024.103436

Yu, H., & Guo, Y. (2023). Harnessing the Potential of Chat GPT in Education: Unveiling its Value, Navigating Challenges, and Crafting Mitigation Pathways, in 2023 5th International Workshop on Artificial Intelligence and Education (WAIE), 48-52. https://doi.org/10.1109/WAIE60568.2023.00016

Zhang, W. (2026). The impact of AI chatbots on EFL learners’ oral proficiency and willingness to communicate. System, 136. https://doi.org/10.1016/j.system.2025.103919

Zeynalova, R. (2026). Language Acquisition Theories and Their Applications in Modern Language Education. EuroGlobal Journal of Linguistics and Language Education, 3 (2). https://orcid.org/0009-0004-8712-7975

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Published

2026-11-06

How to Cite

Malika, H., Kimleng, T., Sonysa, R., Pichchansonita, H., & Sela, C. (2026). The Effects of AI Tools, Self-Efficacy, and Speaking Anxiety on English Speaking Performance Among TEFL Undergraduate Students. Canadian Journal of Language and Literature Studies, 6(6), 33–61. https://doi.org/10.53103/cjlls.v6i6.317

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