Impact of Computer-Assisted Language Learning (CALL) on Pronunciation Proficiency Among ESL Learners

Authors

  • Sehrish Iftikhar

    Centre of Fundamental and Continuing Education, Universiti Malaysia Terengganu, Terengganu 21030, Malaysia
  • Raihana Binti Romly

    Centre of Fundamental and Continuing Education, Universiti Malaysia Terengganu, Terengganu 21030, Malaysia
  • Suraj Begum

    Department of Science and Humanities, Sri Krishna College of Engineering and Technology, Coimbatore 641008, India

DOI:

https://doi.org/10.30564/fls.v7i10.11349
Received: 29 July 2025 | Revised: 13 August 2025 | Accepted: 26 August 2025 | Published Online: 16 October 2025

Abstract

The integration of Computer-Assisted Language Learning (CALL) has transformed pronunciation skills and is no longer confined to traditional classrooms. The study aims to demonstrate the impact of Computer-Assisted Language Learning (CALL) materials on students' pronunciation skills and examine the ESL learners' perceptions of CALL tools. This study employed a quasi-experimental pre- and post-test design, complemented by Technology Acceptance Model 2 (TAM 2) survey with 119 participants in a single institution. Learners' pronunciation was evaluated across segmental accuracy, word stress, fluency and comprehensibility through performance test and their perceptions were assessed by TAM 2 model. The model, for its certain features, deals with the acceptance of technology among the users. Recent advancements of Computer-Assisted Pronunciation Training (CAPT) as a part of CALL, are rapidly increasing, focusing on the efficacy of second language acquisition among the English language learners. Incorporating CAPT in this study emphasizes its proven ability to facilitate accurate pronunciation. The current article investigates the impact of modern technologies and multiple language software packages including MyET, Pronunciation Coach and SpeakPipe to practice and improve pronunciation skills on language learning at the undergraduate level among students in Pakistan. The results indicate that CALL tools effectively enhance measurable pronunciation performance and learners' positive perceptions highlight the potential of CALL to complement traditional speaking instruction by fostering engagement, promoting learner autonomy and providing authentic computer-mediated opportunities for developing pronunciation skills. The study sheds light on practical implications for educators, institutions and policymakers in adopting CALL pronunciation tools to enhance pronunciation skills.

Highlights:

  • Incorporated detailed discussion of underlying mechanisms such as multimodal feedback, repetition, and learner autonomy in CALL.
  • Acknowledged key limitations, including the single-institution convenience sample, reliance on self-reported data, and the absence of long-term follow-up.
  • Strengthened the theoretical foundation and aligned the discussion with recent studies in CALL and pronunciation research.

Keywords:

CALL Applications; Computer-Assisted Pronunciation Training (CAPT); Students' Pronunciation; TAM2 Model; MyET; Pronunciation Coach; SpeakPipe

References

[1] Mir, S.H., Afsar, A., 2024. The pronunciation constraints of syllable stress-coloration in Pakistani English. Journal of Humanities, Social and Management Sciences. 5(1), 21–35. DOI: https://doi.org/10.47264/idea.jhsms/5.1.2

[2] Noor, A., Aslam, D.M.J.I.R., Abid, M.A., 2025. Exploring the impacts of English language dominance on the linguistic standing of Urdu and Punjabi languages. Journal of Applied Linguistics and TESOL (JALT). 8(1), 484–499.

[3] Ejaz, I., Abbas, G., Wasif, M., et al., 2025. Factors affecting the speaking skills of ESL students in rural areas of Pakistan. Southern Journal of Arts & Humanities. 3(1), 15–37.

[4] Rahman, T., 2020. Pakistani English. In: The Handbook of Asian Englishes. John Wiley & Sons, Inc.: Hoboken, NJ, USA. pp. 279–296.

[5] Urwat, M.S., Nadeem, M., Zafar, M.S., et al., 2022. Why do university students in Pakistan confront problems in spoken English. Journal of Education, Society and Behavioural Science. 35, 40–49. DOI: https://doi.org/10.9734/jesbs/2022/v35i830447

[6] Pourhosein Gilakjani, A., Rahimy, R., 2020. Using computer-assisted pronunciation teaching (CAPT) in English pronunciation instruction: a study on the impact and the teacher’s role. Education and Information Technologies. 25(2), 1129–1159.

[7] Gilakjani, A.P., Sabouri, N.B., 2016. Learners' listening comprehension difficulties in English language learning: a literature review. English Language Teaching. 9(6), 123–133.

[8] Zhang, F., Yin, P., 2009. A study of pronunciation problems of English learners in China. Asian Social Science. 5(6), 141–146.

[9] Pothuri, S.B., 2025. Computer-Assisted Language Learning in Enhancing Speaking Skills. Elsevier: Amsterdam, Netherlands.

[10] Rogerson-Revell, P.M., 2021. Computer-assisted pronunciation training (CAPT): current issues and future directions. Relc Journal. 52(1), 189–205.

[11] Talpur, N., Kalwar, T., Talpur, M.J., 2021. Computer-assisted language learning in Pakistani context during COVID-19 pandemic. REiLA: Journal of Research and Innovation in Language. 3(3), 210–225.

[12] Jawaid, A., Batool, M., Arshad, W., et al., 2024. English language pronunciation challenges faced by tertiary students. Contemporary Journal of Social Science Review. 2(4), 2104–2111.

[13] Memon, A., Siddiqui, N., Jat, A.R.L., 2024. Developing English language productive skills through task-based language learning model at tertiary level education in Karachi. International Journal of Academic Research for Humanities. 4(2), 37–48.

[14] Li, Y., 2024. The role of L1-dialect in L2 production: acoustic measures on Xining and Leshan dialect speakers’ production of English vowels. Journal of Second Language Pronunciation. 10(2), 232–257.

[15] Nasir, M., Nazar, F., Abbas, M.K., et al., 2023. Enhancing pronunciation skills of intermediate students through computer-assisted language learning (CALL). Al-Qanṭara. 9(3), 142–160.

[16] Zhang, G., 2024. Enhancing English pronunciation assessment in computer-assisted language learning for college students. Journal of Combinatorial Mathematics and Combinatorial Computing. 120, 275–283.

[17] Fazal, N., Tahir, M.S., Chaudhary, M., et al., 2024. Effectiveness of AI integration into computer-assisted language learning (CALL) on student writing skills based on gender. Pakistan Journal of Humanities and Social Sciences. 12(1), 224–230.

[18] Levy, M., 1997. Computer-Assisted Language Learning: Context and Conceptualization. Oxford University Press: Oxford, UK.

[19] Chapelle, C.A., 2010. The spread of computer-assisted language learning. Language Teaching. 43(1), 66–74.

[20] Khan, A., 2024. The attitude of Pakistani undergraduates towards speaking English. International Journal of Social Science & Entrepreneurship. 4(2), 165–179.

[21] Javed, F., 2017. A historical perspective of Pakistan’s language in education policy. Language in India. 17(8), 45–55.

[22] Yolchiyeva, M., 2024. The importance of pronunciation in learning foreign language and prospects of improving pronunciation competence. Modern Science and Research. 3(5), 343–347.

[23] AbuSeileek, A., 2007. Computer-assisted pronunciation instruction as an effective means for teaching stress. The JALT CALL Journal. 3(1–2), 3–24.

[24] Mahdi, H.S., Al Khateeb, A.A., 2019. The effectiveness of computer-assisted pronunciation training: a meta-analysis. Review of Education. 7(3), 733–753.

[25] Ratnaningsih, D., Purba, D., Wiratno, D., et al., 2019. The influence of computer-assisted language learning (CALL) to improve English speaking skills. In: English linguistics, literature, and language teaching in a changing era. Routledge: London, UK. pp. 144–149.

[26] Gómez González, M.D., Lago Ferreiro, A., 2024. Computer-assisted pronunciation training (CAPT): an empirical evaluation of EPSS multimedia lab. Language Learning & Technology. 28(1), 1–44.

[27] Bogach, N., Boitsova, E., Chernonog, S., et al., 2021. Speech processing for language learning: a practical approach to computer-assisted pronunciation teaching. Electronics. 10(3), 235.

[28] Chen, X., Zou, D., Xie, H.R., et al., 2021. Twenty-five years of computer-assisted language learning: a topic modeling analysis. Language Learning & Technology. 25(3), 151–185.

[29] Ghounane, N., Rabahi, H., 2021. The use of computer-assisted pronunciation training in teaching English pronunciation for first-year EFL students at Saida University. International Journal of Applied Linguistics and English Literature. 10(6), 76–83.

[30] Lee, S.T., 2008. Teaching pronunciation of English using computer-assisted learning software: an action research study in an institute of Taiwan [Doctoral dissertation]. Australian Catholic University: Melbourne, Australia.

[31] Newvine, U., 2023. Intelligent Computer-Assisted Language Learning in the English as a Foreign Language Classroom. University of California, Riverside: Riverside, CA, USA.

[32] Yu, X., Gaspar, C., 2022. A tecnologia capacita: uma investigação do ICALL no desenho de materiais de aprendizagem autorregulada. Diacrítica. 36(2), 232.

[33] Chen, X., Meurers, D., Rebuschat, P., 2022. ICALL offering individually adaptive input: Effects of complex input on L2 development. Language Learning & Technology. 26(1), 1–21. DOI: https://doi.org/10.64152/10125/73496

[34] Namaziandost, E., Rezai, A., 2024. Interplay of academic emotion regulation, academic mindfulness, L2 learning experience, academic motivation, and learner autonomy in intelligent computer-assisted language learning: a study of EFL learners. System. 125, 103419.

[35] Patty, J., 2024. The use of AI in language learning: what you need to know. Jurnal Review Pendidikan dan Pengajaran (JRPP). 7(1), 642–654.

[36] Ardini, S.N., Sunarya, S., Latifah, K., 2024. Development of mobile application through the concept of artificial intelligence to enhance pronunciation skill in EFL. KnE Social Sciences. 56–66.

[37] Dennis, N.K., 2024. Using AI-powered speech recognition technology to improve English pronunciation and speaking skills. IAFOR Journal of Education. 12(2), 107–126.

[38] Pinto-Llorente, A.M., 2022. Assessing the impact of a digital ecosystem to learn English pronunciation. In: Research Anthology on Applied Linguistics and Language Practices. IGI Global Scientific Publishing: Hershey, PA, USA. pp. 747–767.

[39] Kobilova, N.R., 2024. The importance of imitation technique in teaching English pronunciation. Academic Research in Educational Sciences. 5(CSPU Conference 1), 728–732.

[40] Chang, C.Y., 2018. The effects of communicative framework instruction using computer-assisted pronunciation training (CAPT) on English pronunciation ability of Chinese undergraduate students. An Online Journal of Education, 14(1), OJED1401002.

[41] Saleh, A.J., Gilakjani, A.P., 2021. Investigating the impact of computer-assisted pronunciation teaching (CAPT) on improving intermediate EFL learners’ pronunciation ability. Education and Information Technologies. 26, 489–515.

[42] Bergdahl, N., 2025. Second language learning designs in online adult education. Computer Assisted Language Learning. 38(1–2), 1–29.

[43] Mohammed, A., 2017. The role of language laboratory in English language learning settings. English Language Teaching. 10(2), 86–93.

[44] Mayer, R.E., Lee, H., Peebles, A., 2014. Multimedia learning in a second language: a cognitive load perspective. Applied Cognitive Psychology. 28(5), 653–660.

[45] Almasifar, N., Heidari, F., 2024. The effect of computer-assisted pronunciation training on EFL learners’ use of suprasegmental features and foreign language speaking anxiety. English Teaching & Learning. 48(4), 625–648.

[46] Shamsi, E., Bozorgian, H., 2023. The pedagogy for teaching suprasegmental features. Journal of Second Language Pronunciation. 9(3), 312–322.

[47] Du, Y., 2024. The impact of emojis on verbal irony comprehension in computer-mediated communication: a cross-cultural study. International Journal of Human-Computer Interaction. 41(8), 4979–4986. DOI: https://doi.org/10.1080/10447318.2024.2356398

[48] Baskota, P., Poudel, T., 2024. Artificial intelligence and computer-mediated communication: the text analysis and undergrad’s class observation. Discover Education. 3(1), 131.

[49] Hsu, H.W., 2024. An examination of automatic speech recognition (ASR)-based computer-assisted pronunciation training (CAPT) for less-proficient EFL students using the technology acceptance model. International Journal of Technology in Education. 7(3), 456–473.

[50] Guskaroska, A., 2024. Exploring technology acceptance of ASR for pronunciation learning [Doctoral dissertation]. Iowa State University: Ames, IA, USA.

[51] Aufa, A.F., 2025. Evaluating Busuu.com application for speaking skills through Technology Acceptance Model (TAM): EFL student’s perception. IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature. 13(1), 305–332.

[52] Venkatesh, V., Davis, F.D., 2000. A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science. 46(2), 186–204.

[53] Fishbein, M., Ajzen, I., 1975. Belief, attitude, intention and behavior: an introduction to theory and research. Addison-Wesley: Reading, MA, USA.

[54] Itayem, G., 2014. Using the iPad in language learning: perceptions of college students [Master’s dissertation]. University of Toledo: Toledo, OH, USA.

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How to Cite

Iftikhar, S., Binti Romly, R., & Begum, S. (2025). Impact of Computer-Assisted Language Learning (CALL) on Pronunciation Proficiency Among ESL Learners. Forum for Linguistic Studies, 7(10), 1438–1453. https://doi.org/10.30564/fls.v7i10.11349

Issue

Vol. 7 , Iss. 10 (October 2025)

Article Type

Article

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Copyright © 2025 Sehrish Iftikhar, Raihana Binti Romly, Suraj Begum

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This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.