Strengths and Limitations of SmallTalk2Me App in English Language Proficiency Evaluation
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References
Bajraktarevic, N., & Jang, J. (2019). Incorporating contextual aspects of language use in language assessment. TESOL Quarterly, 53(2), 496-503.
Brown, A. (2017). Personalized learning and artificial intelligence. Journal of Educational Technology, 45(2), 78–92.
Brown, A., & Hudson, R. (2021). Exploring the efficacy of AI-driven apps in assessing speaking proficiency. Educational Technology Research, 43(2), 145-163
Carless, D. (2009). Revisiting the quantitative-qualitative divide: Exploring the potential of mixed methods for language assessment research. Language Testing, 26(3), 327–350.
Chapelle, C. A., Enright, M. K., & Jamieson, J. M. (2008). Building a validity argument for the test of English as a foreign language. New York: Routledge.
Chen, L. (2019). Addressing bias in artificial intelligence: the importance of diverse training data. Journal of AI Ethics, 3(1), 45-58
Dhara, Suvojit. Chatterjee, Sheshadari. Chaudhuri, Ranjan. Goswami, Adrijit. Kanti Ghosh, Soumya. (2022). Artificial intelligence in assessment of students' performance. 1–19. https://www.researchgate.net/publication/361861919_Artificial_Intelligence_in_Assessment_of_Students'_Performance
Fajri, M., & Indah, R. N. (2022). Students’ speaking problems in online learning: a systematic research review. Tell: Teaching of English Language and Literature Journal, 10(2), 99–111. https://doi.org/10.30651/tell.v10i2.13559
González-Calatayud, Victor. Prendes-Espinosa, Paz. Roig-Vila, R. (2021). Artificial intelligence for student assessment: a systematic review. https://www.mdpi.com/2076-3417/11/12/5467
Huhta, M., Vogt, K., Johnson, E., & Tulkki, H. (2013). Needs analysis for language course design: a holistic approach to ESP. Cambridge, UK: Cambridge University Press.
Jiang, Y., & Xiao, Y. (2022). App-based assessments might only partially account for cultural differences in communication styles. Language Testing, 39(1), 3-23. https://doi.org/10.1177/02655322211056312
Jones, S. (2016). Contextual understanding challenges in AI-based English language proficiency evaluation. International Journal of Applied Linguistics, 25(2), 89–104.
Kost, C. R., Ferguson, J. L., & Zlatev, J. J. (2019). The efficiency of automated evaluation in large-scale language assessments. Language Testing, 36(2), 209–231. https://doi.org/10.1177/0265532218789815
Lee, J. (2018). Limitations of AI in assessing higher-order skills in English language proficiency. Journal of Language Testing, 39(1), 56–72.
Lee, H., Warschauer, M., & Lee, J. H. (2019). The effects of corpus use on second language vocabulary learning: A multilevel meta-analysis. Applied Linguistics, 40(6), 1027-1052. https://doi.org/10.1093/applin/amz032
Lin, Peng, & Chen. (2019). Enhancing language assessment: the role of ai-integrated apps in evaluating speaking skills. Modern Language Education Journal, 28(1), 72-89
Li, Yang, & Wang. (2022). Assessing speaking ability through AI applications: a comprehensive review. Journal of Language Assessment, 15(3), 187–205.
Luoma, S. (2004). Assessing speaking. Cambridge University Press.
Lizasoain C, Andrea. Ortiz de Zárate F, Amalia. (2014). Alternative evaluation of a traditional oral skill assessment tool in an English teaching program. https://www.researchgate.net/publication/263660757
McNamara, T. F., & Roever, C. (2006). Language testing: The social dimension. Mouton de Gruyter.
Munirah, R. Refnaldi. (2020). An evaluation of assessment designed by English language education student teachers during teaching practice. https://ejournal.unp.ac.id/index.php/jelt
Nurdin, Hi. R., Zaim, M., & Refnaldi, R. (2019). Developing instruments for evaluating the implementation of authentic assessment for speaking skills at junior high school. Advances in Social Science, Education, and Humanities
Research, 276 (Icoelt, 2018), 106–111. https://doi.org/10.2991/icoelt-18.2019.17
Rintan, R., & Refnaldi, R. (2020). An evaluation of assessment designed by English language education student teachers during teaching practice. Journal of English Language Teaching and Linguistics, 5(2), 201-215. https://doi.org/10.24036/jelt.v9i1.108299
Seo, K., Tang, J., Roll, I., Fels, S., & Yoon, D. (2021). The impact of artificial intelligence on learners–instructor interaction in online learning. International Journal of Educational Technology in Higher Education, 18(1), 1–23. https://doi.org/10.1186/s41239-021-00292-9
Smith, T. (2015). Enhanced objectivity in an English language proficiency evaluation. Journal of Language Assessment, 28(3), 123–138.
Smith, A., & Jones, B. (2022). Challenges in AI-based language assessment tools for learners with non-standard accents or speech patterns. Language Testing, 39(3), 321–340. https://doi.org/10.1177/02655322211056312
Thompson, O., & Terkourafi. (2019). Beyond grammar and vocabulary: unveiling the potential of AI apps in assessing speaking competence. Applied Linguistics Review, 56(4), 301-318
Vogel, S., & Kasper, G. (2021). Challenges of assessing real-life communication skills in digital language assessment tools. Language Testing, 38(1), 3-23. https://doi.org/10.1177/0265532220967488
Weigle, S. C. (2014). Exploring multiple profiles of learner compositions. Journal of Second Language Writing.
Xu, J., & Recker, M. (2020). The importance of human interaction in AI-driven language assessment tools. Journal of Educational Technology, 45(3), 321-335.
Zhang, D., Cheng, L., & Wang, X. (2020). The application of AI chatbot-based evaluations in English language teaching. Journal of Educational Technology Development and Exchange, 13(1), 1-14. https://doi.org/10.11648/j.edu.20200501.11
Zhang, & Cheng. (2022). Challenges and opportunities of AI-driven speaking assessment applications in educational settings. Journal of Educational Technology and Applied Linguistics, 39(3), 208–225.
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