Leveraging Edbot.AI as a Diagnostic Assessment Tool to Enhance the Students’ English Achievement
DOI:
https://doi.org/10.31539/9vr4j332Abstract
In response to the growing need for more informative and learner-centered assessment, this study explores the use of Edbot.ai as an AI-based diagnostic assessment tool in junior high English learning. The study aims to examine the effect of Edbot.ai on students’ English achievement and to investigate students’ perceptions of its implementation. To achieve these aims, the study employed a sequential explanatory mixed-methods design using a quasi-experimental approach. To get the data, the study used English test and questionnaire. The findings reveal that the use of Edbot.ai contributed positively to students’ English achievement. Students also perceived Edbot.ai as supportive, engaging, and helpful in understanding their learning progress through timely feedback. Overall, the study indicates that AI-based diagnostic assessment can effectively support English learning outcomes. Future research is recommended to investigate the long-term impact of Edbot.ai to deepen understanding of its instructional potential.
Keywords: Diagnostic Assessment, Edbot.ai, English Achievement, Students’ Perception
References
Adeoye, M. A., Prastikawati, E. F., & Curle, S. (2025). Examining factors influencing language acquisition success in Indonesian multilingual classrooms. Journal of Languages and Language Teaching, 13(4), 1743–1757.
Adeoye, M. A., Prastikawati, E. F., & Riwayatiningsih, R. (2025). Beyond traditional testing: Exploring the efficacy of adaptive assessments in shaping future learners. Journal of Nonformal Education, 11(1), 153–169.
Aditama, M. G., Sugiharto, P. A., Istiqomah, L., & Hisyam, F. N. (2023). Integrating multiple intelligence tests into diagnostic assessment in ELT. International Social Sciences and Humanities, 2(2), 358–363.
Al Braiki, B., Harous, S., Zaki, N., & Alnajjar, F. (2020). Artificial intelligence in education and assessment methods. Bulletin of Electrical Engineering and Informatics, 9(5), 1998–2007. https://doi.org/10.11591/eei.v9i5.2470
Amin, M. Y. M. (2023). AI and ChatGPT in language teaching: Enhancing EFL classroom support and transforming assessment techniques. International Journal of Higher Education Pedagogies, 4(4), 1–15.
Barata, A., Yuliana, Y. G. S., & Regina, R. (2025). Artificial intelligence chatbot application for improving teachers’ spoken grammar. Edukasi: Jurnal Pendidikan, 23(1), 163–178.
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Chea, P., & Xiao, Y. (2024). Artificial intelligence in higher education: The power and risks of AI-assisted tools on academic English reading skills. Journal of General Education and Humanities, 3(3), 287–306.
Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510
Chen, Y. (2025). Transforming English language education with AI-driven deep learning models for scalable, adaptive, and inclusive assessment. International Journal of Information and Communication Technology, 26(12), 15–31.
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.
Dorgham, R. (2025). Using artificial intelligence tools for developing EFL students’ listening skills and reducing their listening anxiety. Educational and Psychological Studies, 40(140, Part 1), 513–577.
Fang, Y., Roscoe, R. D., & McNamara, D. S. (2023). Artificial intelligence-based assessment in education. In Handbook of artificial intelligence in education (pp. 485–504). Edward Elgar Publishing.
Farhady, H., & Selcuk, M. (2022). Classroom-based diagnostic assessment practices of EFL instructors. Iranian Journal of Language Teaching Research, 10(2), 77–94.
Farisyah, U., Sulaimon, J. T., & Sodiq, J. (2025). Dynamic assessment strategies for enhancing reading comprehension and student motivation. Educalingua, 3(1), 1–12.
González-Calatayud, V., Prendes-Espinosa, P., & Roig-Vila, R. (2021). Artificial intelligence for student assessment: A systematic review. Applied Sciences, 11(12), 5467. https://doi.org/10.3390/app11125467
Haenen, J., Vink, S., Sjoer, E., & Admiraal, W. (2025). Motivating students with optimal challenge in an open learning environment. Social Sciences & Humanities Open, 11, 101577. https://doi.org/10.1016/j.ssaho.2025.101577
Jimola, F. E., & Ofodu, G. O. (2019). ESL teachers and diagnostic assessment: Perceptions and practices. ELOPE: English Language Overseas Perspectives and Enquiries, 16(2), 33–48.
Kazemi, N., & Tavassoli, K. (2020). The comparative effect of dynamic vs. diagnostic assessment on EFL learners’ speaking ability. Research in English Language Pedagogy, 8(2), 223–240.
Khan, I., Ahmad, A. R., Jabeur, N., & Mahdi, M. N. (2021). An artificial intelligence approach to monitor student performance and devise preventive measures. Smart Learning Environments, 8(1), 17. https://doi.org/10.1186/s40561-021-00161-y
Koraishi, O. (2023). Teaching English in the age of AI: Embracing ChatGPT to optimize EFL materials and assessment. Language Education and Technology, 3(1), 1–10.
Lee, D., Kim, H. H., & Sung, S. H. (2023). Development research on an AI English learning support system to facilitate learner-generated-context-based learning. Educational Technology Research and Development, 71(2), 629–666. https://doi.org/10.1007/s11423-022-10172-2
Luo, J., Zheng, C., Yin, J., & Teo, H. H. (2025). Design and assessment of AI-based learning tools in higher education: A systematic review. International Journal of Educational Technology in Higher Education, 22(1), 42.
Maulidyah, D. S. (2025). Exploring teachers’ perceptions of AI-powered classroom-based assessment tools in ESP class. Indonesian Journal of Foreign Language Studies, 2(1), 28–36.
Mohammadi, M. (2024). Language teachers’ assessment literacy in AI-aided adaptive learning environments. Journal of Research in Applied Linguistics, 15(2), 73–88.
Nuraini, F. I., Sodiq, J., & Prastikawati, E. F. (2025). Edmodo as technology-based formative assessment: How it enhances reading comprehension. International Journal of Research in Education, 5(1), 81–92.
Pallant, J. (2007). SPSS survival manual: A step-by-step guide to data analysis using SPSS (3rd ed.). McGraw-Hill Education.
Prastikawati, E. F., & Adeoye, M. A. (2024). Enhancing learning: Peer assessment’s influence on English as a foreign language education in Indonesia. Mimbar Ilmu, 29(2), 246–253.
Rahayu, W., Prastikawati, E. F., Wiyaka, W., & Lestari, M. Y. W. (2022). Fostering students’ reading comprehension through dynamic assessment. Language Circle: Journal of Language and Literature, 17(1), 205–214.
Razali, N. M., & Wah, Y. B. (2011). Power comparisons of Shapiro–Wilk, Kolmogorov–Smirnov, Lilliefors, and Anderson–Darling tests. Journal of Statistical Modeling and Analytics, 2(1), 21–33.
Setiyowati, R., & Ardaniah, V. (2025). A systematic review of AI-based and teacher-based writing assessment. In Proceedings of the English Language and Literature International Conference (ELLiC) (Vol. 8, pp. 380–394).
Swiecki, Z., Khosravi, H., Chen, G., Martinez-Maldonado, R., Lodge, J. M., Milligan, S., & Gašević, D. (2022). Assessment in the age of artificial intelligence. Computers and Education: Artificial Intelligence, 3, 100075. https://doi.org/10.1016/j.caeai.2022.100075
Taj, A., Khan, S., Siddiqui, H. A., Abbas, Q., & Nawaz, A. (2025). Artificial intelligence in addressing vocabulary learning challenges: Strategies for English language learners. The Critical Review of Social Sciences Studies, 3(1), 3321–3342.
Tosuncuoglu, I. (2018). Importance of assessment in ELT. Journal of Education and Training Studies, 6(9), 163–167. https://doi.org/10.11114/jets.v6i9.3443
Wiyaka, W., Silitonga, L. M., Sunardi, S., & Pramudi, Y. T. C. (2025). Leveraging diagnostic assessment aligned to differentiated learning: Voices of English language teachers. KnE Social Sciences.
Yang, S., & Berdine, G. (2021). Normality tests. The Southwest Respiratory and Critical Care Chronicles, 9(37), 87–90.
Yang, Y. (2025). AI-supported L2 vocabulary acquisition: A systematic review from 2015 to 2023. Education and Information Technologies. Advance online publication.
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