Assessing the Impact of the Haima English Intelligent Enhancement Platform on Pronunciation Improvement: A Study of Stress Problems
Journal: Region - Educational Research and Reviews DOI: 10.32629/rerr.v7i2.3463
Abstract
This study investigates the effectiveness of HaiMa English, an AI-assisted words online learning platform, in improving pronunciation among learners with stress at different proficiency levels. By analyzing pre- and post-intervention audio recordings of commonly mispronounced words produced by participates, the results show significant pronunciation improvements across all proficiency levels, with greater progress observed in students with lower stress levels. Frequent interaction with native pronunciation audio and timely instructor corrections contributed to more substantial improvements. The findings highlight the platform’s effectiveness in reducing pronunciation errors, particularly when stress is managed. The study underscores the need for personalized pronunciation support and the integration of stress-reducing strategies in intelligent learning tools.
Keywords
AI-assisted learning, pronunciation improvement, stress in language learning, language proficiency
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[3] Derwing, T. M., Munro, M. J. Second language accent and pronunciation teaching: A research‐based approach. Tesol Quarterly, 2005, 39(3), 379-397.
[4] Ebbinghaus, H. Memory. Рипол Классик, 1964.
[5] Hahn, L. D. Primary stress and intelligibility: Research to motivate the teaching of suprasegmentals. Tesol Quarterly, 2004, 38(2), 201-223.
[6] Housen, A., Kuiken, F. Complexity, accuracy, and fluency in second language acquisition. Applied linguistics, 2009, 30(4), 461-473.
[7] Jones, T. Pronunciation with other areas of language. The Routledge handbook of contemporary English pronunciation, 2017, 370-384.
[8] Kang, O., Kermad, A. Assessment in second language pronunciation. In The Routledge handbook of contemporary English pronunciation, Routledge. 2017, 511-526.
[9] Karjo, C. H. Accounting for L2 learners’ errors in word stress placement. Indonesian Journal of Applied Linguistics, 2016, 5(2), 199-208.
[10] Levis, J. M. Intelligibility, oral communication, and the teaching of pronunciation. Cambridge University Press, 2018.
[11] Liakin, D., Cardoso, W., Liakina, N. Mobilizing instruction in a second-language context: Learners’ perceptions of two speech technologies. Languages, 2017, 2(3), 11.
[12] Paakki, H. Difficulties in speaking English and perceptions of accents: A comparative study of Finnish and Japanese adult learners of English Itä-Suomen yliopisto, 2013.
[13] Pawlak, M., Mystkowska-Wiertelak, A., Bielak, J. Exploring advanced learners’ beliefs about pronunciation instruction and their relationship with attainment. Teaching and researching the pronunciation of English: Studies in honour of Włodzimierz Sobkowiak, 2015, 3-22.
[14] Pokrivcakova, S. Preparing teachers for the application of AI-powered technologies in foreign language education. Journal of Language and Cultural Education, 2019, 7(3), 135-153.
[15] Qiao, H., Zhao, A. Artificial intelligence-based language learning: illuminating the impact on speaking skills and self-regulation in Chinese EFL context. Frontiers in Psychology, 2023, 14, 1255594.
[16] Setter, J., Jenkins, J. State-of-the-art review article. Language Teaching, 2005, 38(1), 1-17.
[17] Swan, M., Smith, B. Learner English: A teacher's guide to interference and other problems (Vol. 1). Cambridge University Press, 2001.
[18] Yang, M., Cooc, N., Sheng, L. An investigation of cross-linguistic transfer between Chinese and English: A meta-analysis. Asian-Pacific Journal of Second and Foreign Language Education, 2017, 2, 1-21.
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