Exploring a Decade of Research: A Systematic Review of Computer-Based English Speaking Tests

Authors

  • Hengzhi Hu

    Faculty of Education, Universiti Kebangsaan Malaysia, Bangi Selangor 43600, Malaysia
  • Qiuyu Gong

    Faculty of Education, Universiti Kebangsaan Malaysia, Bangi Selangor 43600, Malaysia
  • Nur Ehsan Mohd Said

    Faculty of Education, Universiti Kebangsaan Malaysia, Bangi Selangor 43600, Malaysia
    Centre for Shaping Advanced & Professional Education, Universiti Kebangsaan Malaysia, Selangor 43600, Malaysia

DOI:

https://doi.org/10.30564/fls.v7i4.8978
Received: 5 March 2025 | Revised: 4 April 2025 | Accepted: 11 April 2025 | Published Online: 14 April 2025

Abstract

The rapid integration of technology into educational assessment has revolutionized the evaluation of English speaking proficiency. Computer-based English speaking tests (CBESTs) have emerged as scalable and efficient solutions, which offer enhanced consistency and accessibility in high-stakes and large-scale testing contexts. However, existing studies on CBESTs have primarily focused on specific aspects of their design, implementation, and impact, leaving a fragmented understanding of their broader implications. As such, this systematic review synthesizes empirical research on CBESTs published between 2014 and 2024 to identify overarching trends, challenges, and opportunities. Employing the PRISMA methodology, the review analyzed 36 studies identified from three databases: Web of Science, Scopus, and Google Scholar. The findings highlight diverse research foci, including advancements in automated scoring, test validity, and the influence of cognitive and affective factors on performance. Studies also explored test-taker perceptions and experiences, which revealed mixed attitudes toward fairness and authenticity. Research methodologies ranged from quantitative correlational studies and qualitative case studies to mixed-methods designs, reflecting a diverse yet fragmented body of work. The review highlights the need for continued innovation in CBEST design and emphasizes the importance of hybrid models that integrate automation with human judgment. For test developers and policymakers, the findings underscore the importance of equitable implementation, technical refinement, and alignment with pedagogical goals. Future research should explore underrepresented areas such as long-term learning impacts and broader inclusivity to enhance the utility and fairness of CBESTs.

Keywords:

Computer-Based Tests; Assessment; English Speaking; Systematic Review

References

[1] Hu, H., Zhou, Q., 2024. The subterranean English training market: Examining grassroots resistance amidst China's double-reduction policies. In: Alam, M.B. (ed.). Shadow Education in Asia: Policies and Practices. IGI Global: Hershey, PA, USA. pp. 160–180.

[2] Liu, Y., 2023. The Application of Portfolio Assessment in English Continuation Writing for Senior High Schools. Journal of Advanced Research in Education. 2(4), 41–46. DOI: https://doi.org/10.56397/JARE.2023.07.07

[3] Brahim, Y., 2023. Computer-Based Vs. Face-to-Face Speaking Assessment: Fitness for Purpose from a Communicative Language Testing View. International Journal of Social Science and Human Research. 6(1), 22–30. DOI: https://doi.org/10.47191/ijsshr/v6-i1-04

[4] Tan, J., 2021. Research on Computer-Aided English Language Evaluation System. Journal of Physics Conference Series. 1992(3), 032103. DOI: https://doi.org/10.1088/1742-6596/1992/3/032103

[5] Kunnan, A.J. (ed.), 2024. The Concise Companion to Language Assessment. Wiley: Hoboken, NJ, USA. pp. 1–720.

[6] Li, W., 2023. A Critique of the Computer-Based English Speaking Test in Fujian (CEST-FJ). English Language Teaching and Linguistics Studies. 5(3), 123–141. DOI: https://doi.org/10.22158/eltls.v5n3p123

[7] Shoja, L., Maadikhah, M.M., 2024. From CALT to AI: Reviewing the Evolution of Technology-based Language Testing and Assessment [Presentation]. Ilam University: Ilam, Iran. DOI: https://doi.org/10.13140/RG.2.2.13997.81125

[8] Hu, H., Said, N.E.M., Hashim, H., et al., 2022. Killing Two Birds with One Stone? A Study on Achievement Levels and Affective Factors in Content and Language Integrated Learning (CLIL). International Journal of Learning, Teaching and Educational Research. 21(4), 150–167. DOI: https://doi.org/10.26803/ijlter.21.4.9

[9] Zheng, L., Ismail, H.H., Hashim, H., et al., 2025. Storytelling in English Language Education in China: A Systematic Review of Empirical Research from the Past Decade (2014–2024). Forum for Linguistic Studies. 7(2), 280–295. DOI: https://doi.org/10.30564/fls.v7i2.8314

[10] Aydoğdu, Ç., Kaplan, Y.Ü., 2024. Voices Regarding Online Assessment: Students' Perceptions, Challenges and Proposed Solutions. Anemon Muş Alparslan Üniversitesi Sosyal Bilimler Dergisi. 12(3), 844–865. DOI: https://doi.org/10.18506/anemon.1446039

[11] Sun, H., 2022. How to Teach Spoken English in Junior High Schools to Cope with the “Human-Computer Dialogue" Test. Learning Week. 10(10), 77–79. DOI: https://doi.org/10.16657/j.cnki.issn1673-9132.2022.10.026

[12] Giraldo, F., 2023. Fostering Pre-Service Teachers' Language Assessment Literacy. Sello Editorial Universidad de Caldas: Caldas, Colombia. pp. 1–256. DOI: https://doi.org/10.2307/jj.8973304

[13] Feng, S., 2020. A Preliminary Study on English APP-Assisted Oral English Personalized Learning. Education Research. 3(4), 17–18. DOI: https://doi.org/10.32629/er.v3i4.2655

[14] Zhu, B., Zhong, Z., 2024. Application Research of Computer-Assisted Technologies in EAP Module Learning. Advances in Educational Technology and Psychology. 8(2), 123–128. DOI: https://doi.org/10.23977/aetp.2024.080218

[15] Zhang, X., 2020. Improve English Speaking Skills in the “Human-Computer Dialogue" Examination. Asia Pacific Education. 22, 191–192. DOI: https://doi.org/10.12240/j.issn.2095-9214.2020.22.091

[16] Hu, H., Du, K., 2022. TikTok in Mobile-Assisted English Language Learning: An Exploratory Study. International Journal of Information and Education Technology. 12(12), 1311–1320. DOI: https://doi.org/10.18178/ijiet.2022.12.12.1755

[17] Hu, H., 2022. Computer-Delivered English Listening and Speaking Test in Zhongkao: Test-Taker Perception, Motivation and Performance. Proceedings of SOCIOINT 2022-9th International Conference on Education and Education of Social Sciences; 13–14 June 2022; International Organization Center of Academic Research (OCERINT), Istanbul, Turkey (Virtual-Online). pp. 59–75.

[18] Klebanov, B.B., Madnani, N., 2021. Automated Essay Scoring. Morgan & Claypool Publishers: Vermont, USA.

[19] Ghumssani, B.H.H., 2024. Saudi EFL Universities Students' Perceptions of Taking Computer-Based Tests and Paper-Based Tests. Arab World English Journal. 1–23. DOI: https://doi.org/10.24093/awej/th.314

[20] PRISMA, 2024. PRISMA Flow Diagram. Available from: https://www.prisma-statement.org/prisma-2020-flow-diagram (cited 11 November 2024).

[21] Brown, C.C., 2021. Librarian's Guide to Online Searching: Cultivating Database Skills for Research and Instruction. Libraries Unlimited: Santa Barbara, CA, USA.

[22] Hu, H., Said, N.E.M., Hashim, H., et al., 2023. Sustaining Content and Language Integrated Learning in China: A Systematic Review. Sustainability. 15(5), 3894. DOI: https://doi.org/10.3390/su15053894

[23] Hayashi, Y., Kondo, Y., 2024. Automated Speech Scoring of Dialogue Response by Japanese Learners of English as a Foreign Language. Innovation in Language Learning and Teaching. 18(1), 32–46. DOI: https://doi.org/10.1080/17501229.2023.2217181

[24] Zhou, Y., 2015. Computer-Delivered or Face-to-Face: Effects of Delivery Mode on the Testing of Second Language Speaking. Language Testing in Asia. 5(1), 2. DOI: https://doi.org/10.1186/s40468-014-0012-y

[25] Min, Y., Li, C., Wang, X., et al., 2020. Computer Based English Speaking Test Based on Artificial Neural Network. Computer Science & IT Research Journal. 1(1), 29–36. DOI: https://doi.org/10.51594/csitrj.v1i1.132

[26] Zhang, W., Wilson, A., 2023. From Self-Regulated Learning to Computer-Delivered Integrated Speaking Testing: Does Monitoring Always Monitor? Frontiers in Psychology. 14, 1028754. DOI: https://doi.org/10.3389/fpsyg.2023.1028754

[27] Kanzawa, K., Mitsunaga, H., Edmonds, G., et al., 2022. Development and Administration of a Skype-Based English Speaking Test in a Japanese High School. Bulletin of Kyoto Institute of Technology. 14, 27–47.

[28] Beccaro, W., Arjona Ramirez, M., Liaw, W., et al., 2024. Analysis of Oral Exams with Speaker Diarization and Speech Emotion Recognition: A Case Study. IEEE Transactions on Education. 67(1), 74–86. DOI: https://doi.org/10.1109/TE.2023.3321155

[29] Lu, Z., Li, Z., Hou, L., 2016. On the Validity and Reliability of a Computer-Assisted English Speaking Test. Proceedings of the 2016 International Conference on Intelligent Control and Computer Application; 16–17 January 2016; Zhengzhou, China. Atlantis Press: Zhengzhou, China. pp. 187–193.

[30] Zhan, Y., Wan, Z.H., 2016. Test Takers' Beliefs and Experiences of a High-Stakes Computer-Based English Listening and Speaking Test. RELC Journal. 47(3), 363–376. DOI: https://doi.org/10.1177/0033688216631174

[31] Khabbazbashi, N., Nakatsuhara, F., Inoue, C., et al., 2022. The Design and Validation of an Online Speaking Test for Young Learners in Uruguay: Challenges and Innovations. International Journal of TESOL Studies. 4(1), 141–168. DOI: https://doi.org/10.46451/ijts.2022.01.10

[32] Yang, Y., 2017. Test Anxiety Analysis of Chinese College Students in Computer-Based Spoken English Test. Educational Technology & Society. 20(2), 1–12.

[33] Zhang, W., Zhang, L.J., Wilson, A.J., et al., 2021. Supporting Learner Success: Revisiting Strategic Competence Through Developing an Inventory for Computer-Assisted Speaking Assessment. Frontiers in Psychology. 12, 689581. DOI: https://doi.org/10.3389/fpsyg.2021.689581

[34] Joo, M., 2022. Effects of Pre-Task and On-Line Planning on Complexity, Fluency, and Accuracy in Computer-Based English Speaking and Writing Tests. Korean Journal of English Language and Linguistics. 22, 938–956. DOI: https://doi.org/10.15738/kjell.22..202210.938

[35] François, J., Albakry, M., 2021. Effect of Formulaic Sequences on Fluency of English Learners in Standardized Speaking Tests. Language Learning & Technology. 25(2), 26–41. Available from: http://hdl.handle.net/10125/73429

[36] Zhou, Y., Yoshitomi, A., 2019. Test-Taker Perception of and Test Performance on Computer-Delivered Speaking Tests: The Mediational Role of Test-Taking Motivation. Language Testing in Asia. 9(1), 10. DOI: https://doi.org/10.1186/s40468-019-0086-7

[37] Shin, D., Kwon, S.K., Noh, W.I., et al., 2024. Exploring the Role of the Metaverse in English Speaking Proficiency Tests. Journal of Computer Assisted Learning. DOI: https://doi.org/10.1111/jcal.13108

[38] Moon, Y.-S., Choi, I.-C., 2019. Salient Linguistic Features of EFL Learner Spoken Corpus Elicited by a Computerized Speaking Test. Multimedia-Assisted Language Learning. 22(3), 54–83. DOI: https://doi.org/10.15702/mall.2019.22.3.54

[39] Jang, B.Y., Kwon, O.W., 2016. Computer-Based Fluency Evaluation of English Speaking Tests for Koreans. Phonetics and Speech Sciences. 6(2), 9–20. DOI: https://doi.org/10.13064/KSSS.2014.6.2.009

[40] Chaisuriya, A., 2023. Readiness for Computer-Based English Tests Among College Students in Regional Thailand. Theory and Practice in Language Studies. 13(2), 370–375. DOI: https://doi.org/10.17507/tpls.1302.11

[41] Kanzaki, M., 2017. TOEIC Speaking Test: A Correlational Study and Test Takers' Reactions. In: Clements, P., Krause, A., Brown, H. (eds.). Transformation in Language Education. JALT: Tokyo, Japan. pp. 441–448.

[42] Yonezaki, M., 2016. A Comparative Analysis of Semi-Direct Speaking Testing and Direct Speaking Testing for Japanese EFL Learners. International Journal of Curriculum Development and Practice. 18(1), 27–38. DOI: https://doi.org/10.18993/jcrdaen.18.1_27

[43] Sangsuwan, W., Rukthong, A., 2023. Test-Takers' Performances on and Perceptions of Two Different Modes of Online Speaking Tests. LEARN Journal: Language Education and Acquisition Research Network. 16(2), 168–183.

[44] Liu, J., Zhang, B., 2020. Multi-Level Rasch Model Analysis of Computer-Assisted Automated Scoring of English Listening and Speaking Tests. Proceedings of 2020 International Conference on Computer Engineering and Application; 18–20 March 2020; Guangzhou, China. pp. 632–636. DOI: https://doi.org/10.1109/ICCEA50009.2020.00138

[45] Brena, R.F., Zuvirie, E., Preciado, A., et al., 2021. Automated Evaluation of Foreign Language Speaking Performance with Machine Learning. International Journal on Interactive Design and Manufacturing. 15, 317–331. DOI: https://doi.org/10.1007/s12008-021-00759-z

[46] Nguyen, T.H.H., Nguyen, B.T.T., Hoang, G.T.L., et al., 2024. Computer-Delivered vs. Face-to-Face Score Comparability and Test Takers' Perceptions: The Case of the Two English Speaking Proficiency Tests for Vietnamese EFL Learners. Language Testing in Asia. 14(1), 6. DOI: https://doi.org/10.1186/s40468-024-00277-1

[47] Tarighat, S., Khodabakhsh, S., 2016. Mobile-Assisted Language Assessment: Assessing Speaking. Computers in Human Behavior. 64, 409–413. DOI: https://doi.org/10.1016/j.chb.2016.07.014

[48] Wiannastiti, M., 2016. Assessing Speaking for a Large Number of Students by Using Bingar Application. Proceedings of the 5th ELTLT International Conference Proceedings; 8–9 October 2016; State University of Semarang: Semarang, Indonesia. pp. 426–430.

[49] Lee, S., Winke, P., 2017. Young Learners' Response Processes When Taking Computerized Tasks for Speaking Assessment. Language Testing. 35(2), 239–269. DOI: https://doi.org/10.1177/0265532217704009

[50] Amengual-Pizarro, M., García-Laborda, J., 2017. Analysing Test-Takers' Views on a Computer-Based Speaking Test. Profile: Issues in Teachers' Professional Development. 19(S1), 23–38. DOI: https://doi.org/10.15446/profile.v19n_sup1.68447

[51] Cao, L., 2020. Comparison of Automatic and Expert Teachers' Rating of Computerized English Listening-Speaking Test. English Language Teaching. 13(1), 18–30. DOI: https://doi.org/10.5539/elt.v13n1p18

[52] Masuda, H., Mori, M., Kanzawa, K., et al., 2016. Secure Data Management in an English Speaking Test Implemented in General-Purpose PC Classrooms. Proceedings of the 2016 ACM SIGUCCS Annual Conference; 6–9 November 2016; Denver Colorado USA. Association for Computing Machinery: New York, NY, USA. pp. 135–138.

[53] Munkh-ochir, G., Lee, C.-i., 2015. A Study on Error Types Represented in Computer-Based Speaking and Computer-Based Writing: Centered Around Korean Learners. Multimedia-Assisted Language Learning. 18(3), 112–141. DOI: https://doi.org/10.15702/mall.2015.18.3.122

[54] Xu, L., Zhao, X., Zheng, C., et al., 2017. Speaking-Related Anxiety in Computer-Assisted Language Testing Settings. In: Hayashi, Y. (ed.). Workshop Proceedings of the 25th International Conference on Computers in Education. Asia-Pacific Society for Computers in Education: Christchurch, New Zealand.

[55] Ockey, G.J., Timpe-Laughlin, V., Davis, L., et al., 2019. Exploring the Potential of a Video-Mediated Interactive Speaking Assessment. ETS Research Report Series. 2019(1), 1–29. DOI: https://doi.org/10.1002/ets2.12240

[56] Kondo, A., 2021. The Effects of Individual Differences in Speaking Skills of Japanese EFL Learners: Aptitude (Phonological Working Memory) and Attitude (L2 Motivation). Studies in Language Sciences. 19, 1–18. DOI: https://doi.org/10.34609/sls.19.0_1

[57] Xu, J., Jones, E., Laxton, V., et al., 2021. Assessing L2 English Speaking Using Automated Scoring Technology: Examining Automarker Reliability. Assessment in Education: Principles, Policy & Practice. 28(4), 411–436. DOI: https://doi.org/10.1080/0969594X.2021.1979467

[58] Wu, T.-I., Lo, T.-H., Chao, F.-A., et al., 2022. A Preliminary Study on Automated Speaking Assessment of English as a Second Language (ESL) Students. Proceedings of the 34th Conference on Computational Linguistics and Speech Processing; 21–22 November 2022; Taipei, Taiwan. pp.174–183.

Downloads

How to Cite

Hu, H., Gong, Q., & Mohd Said, N. E. (2025). Exploring a Decade of Research: A Systematic Review of Computer-Based English Speaking Tests. Forum for Linguistic Studies, 7(4), 788–803. https://doi.org/10.30564/fls.v7i4.8978

Issue

Vol. 7 , Iss. 4 (April 2025): In Progress

Article Type

Review

License

Copyright © 2025 Hengzhi Hu, Qiuyu Gong, Nur Ehsan Mohd Said

Creative Commons License

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