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Leveraging Edbot.AI as a Diagnostic Assessment Tool to Enhance the Students’ English Achievement Shafa Nabila, Alya; Prastikawati, Entika Fani; Lestari, Maria Yosephin Widarti
Linguistic, English Education and Art (LEEA) Journal Vol 9 No 2 (2026): Linguistic, English Education and Art (LEEA) Journal
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/9vr4j332

Abstract

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