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The Use Of Artificial Intelligence In The Learning Of Malay Proverbs Among Secondary School Students In The District Of Semporna

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  • Kaeimah binti Nulbahari

    (Faculty Pendidikan, University Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia)

  • Zamri Mahamod

    (Faculty Pendidikan, University Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia)

Abstract

This study aims to evaluate the effectiveness of Artificial Intelligence (AI) in the learning of Malay proverbs among secondary school students in Semporna District, Sabah. The use of AI in education is perceived to strengthen students’ comprehension through immediate feedback, adaptive content, and self-directed learning. This study employed a quasi-experimental design involving two groups of Form Five students: the Experimental group (learning with AI applications) and the Control group (traditional teaching). A total of 60 students with moderate academic achievement were selected as the study sample. The research instruments consisted of pre- and post-tests designed to measure students’ understanding and achievement in Malay proverbs. Data were analyzed using SPSS version 27 through independent and paired sample t-tests. The findings revealed significant differences in mean scores between the Experimental and Control groups, as well as notable improvements between pre-test and post-test scores within the Experimental group. These results indicate that AI-based learning has a positive impact on students’ achievement in learning Malay proverbs. This study is expected to provide valuable implications for Malay language teachers in utilizing AI technology as an alternative, interactive, and effective approach to teaching proverbs.

Suggested Citation

  • Kaeimah binti Nulbahari & Zamri Mahamod, 2025. "The Use Of Artificial Intelligence In The Learning Of Malay Proverbs Among Secondary School Students In The District Of Semporna," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(9), pages 3191-3198, September.
  • Handle: RePEc:bcp:journl:v:9:y:2025:issue-9:p:3191-3198
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