Etika Sebagai Teras Literasi AI: Analisis Literasi, Efikasi Kendiri Dan Kompetensi Ai Pelajar Matrikulasi
DOI:
https://doi.org/10.37134/ejoss.vol12.sp2.7.2026Keywords:
SJT, Literasi AI, Etika AI, Efikasi Kendiri AI, MatrikulasiAbstract
Perkembangan AI telah memacu pendidikan menuntut penguasaan literasi AI sebagai kemahiran utama abad ke-21. Dalam konteks Program Matrikulasi Malaysia, pelajar perlu bersedia menghadapi pembelajaran berasaskan AI sebagai asas menuju ke peringkat universiti dan dunia kerja digital. Penggunaan AI dalam pendidikan telah mencetuskan isu kebergantungan berlebihan yang mencabar integriti akademik dan keupayaan berfikir secara kritis. Fenomena ini memerlukan penguasaan literasi AI. Namun kajian mengenai tahap literasi AI pelajar matrikulasi masih terhad. Kekurangan ini menimbulkan kebimbangan terhadap potensi penyalahgunaan AI serta cabaran dalam penggunaan beretika. Kajian ini bertujuan mengukur tahap literasi AI pelajar matrikulasi dan menganalisis hubungan etika AI dengan efikasi kendiri AI dan kompetensi AI. Kajian tinjauan berbentuk deskriptif digunakan melibatkan 355 pelajar dari sebuah kolej matrikulasi menggunakan instrumen MAILS. Dapatan kajian menunjukkan pelajar mempunyai literasi AI yang tinggi, begitu juga etika AI, kompetensi dan efikasi kendiri AI. Analisis Spearman menunjukkan etika AI berkorelasi kuat dengan efikasi kendiri AI dan kompetensi AI, menandakan bahawa peningkatan kesedaran etika seiring dengan peningkatan keyakinan dan kecekapan penggunaan AI. Kajian terhad kepada sebuah kolej matrikulasi dan menggunakan soal selidik skala Likert lima mata bagi mengukur etika, yang berisiko bias keinginan sosial. Kajian ini menyarankan agar sampel diperluaskan merentas beberapa kolej dan memperkukuh pengukuran etika menggunakan instrumen psikometrik yang mantap seperti Situational Judgment Test (SJT). Akhir sekali, bentuk pentaksiran di kolej matrikulasi wajar ditinjau semula bagi mengelakkan kebergantungan pelajar sepenuhnya terhadap AI, yang boleh menjejaskan perkembangan pemikiran aras tinggi. Penilaian hendaklah beralih daripada menilai produk akhir semata-mata kepada proses pembelajaran bermakna, beretika dan menekankan keaslian pemikiran pelajar dalam penggunaan AI
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References
Abuzaid, M. M., Elshami, W., & Fadden, S. M. (2022). Integration of artificial intelligence into nursing practice. Health and Technology, 12(6), 1109–1115.
Abuzaid, M. M., Elshami, W., & McFadden, S. M. (2022). Integration of artificial intelligence into nursing practice. Health and Technology, 12(6), 1109–1115. https://doi.org/10.1007/s12553-022-00697-0
Al-Abdullatif, A. M. (2025). Auditing AI Literacy Competency in K–12 Education: The Role of Awareness, Ethics, Evaluation, and Use in Human–Machine Cooperation. Systems, 13(6), 490. https://doi.org/10.3390/systems13060490
Al-Abdullatif, A. M. (2025). Auditing AI Literacy Competency in K–12 Education: The Role of Awareness, Ethics, Evaluation, and Use in Human–Machine Cooperation. Systems, 13(6), 490. https://doi.org/10.3390/systems13060490.
Alkharusi, H. (2022). A descriptive analysis and interpretation of data from Likert scales in educational and psychological research. Indian Journal of Psychology and Education, 12(2), 13–16.
Bozkurt, A., Karadeniz, A., Baneres, D., Guerrero-Roldan, A. E., & Rodríguez, M. E. (2021). Artificial Intelligence and Reflections from Educational Landscape: A Review of AI Studies in Half a Century. Sustainability, 13(2), 800. https://www.mdpi.com/20711050/13/2/800.
Carolus, A., Koch, M. J., Straka, S., Latoschik, M. E., & Wienrich, C. (2023). MAILS-Meta AI literacy scale: Development and testing of an AI literacy questionnaire based on well-founded competency models and psychological change-and meta-competencies. Computers in Human Behavior: Artificial Humans, 1(2), 100014.
Carolus, A., Koch, M. J., Straka, S., Latoschik, M. E., & Wienrich, C. (2023). MAILS-Meta AI literacy scale: Development and testing of an AI literacy questionnaire based on well-founded competency models and psychological change-and meta-competencies. Computers in Human Behavior: Artificial Humans, 1(2), 100014.
Çetindamar, D., Kitto, K., Wu, M., Zhang, Y., Abedin, B., & Knight, S. (2022). Explicating AI literacy of employees at digital workplaces. IEEE transactions on engineering management, 71, 810-823. https://doi.org/10.1109/TEM.2021.3138503.
Chan, C. K. Y. (2025). Students’ perceptions of “AI-giarism”: Investigating changes in understandings of academic misconduct. Education and Information Technologies, 30, 8087–8108. https://doi.org/10.1007/s10639-024-13151-7
Chan, C. K. Y. (2025). Students’ perceptions of “AI-giarism”: Investigating changes in understandings of academic misconduct. Education and Information Technologies, 30, 8087–8108.
Chiu, T. K. F. (2023). The impact of generative AI (GenAI) on practices, policies and research direction in education: A case of ChatGPT and Midjourney. Interactive Learning Environments. Advance online publication. https://doi.org/10.1080/10494820.2023.2253861
Conover, W. J. (1999). Practical nonparametric statistics (3rd ed.). John Wiley & Sons.
Field, A. (2018). Discovering statistics using IBM SPSS Statistics (5th ed.). SAGE Publications.
Finlay, J. (2020). An introduction to artificial intelligence. Crc Press.
George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference 11.0 update (4th ed.). Allyn & Bacon.
Haenlein, M., & Kaplan, A. (2019). A Brief History of Artificial Intelligence: On the Past, Present, and Future of Artificial Intelligence. California Management Review, 61(4), 5–14. doi:10.1177/0008125619864925.
Horowitz, M. C., & Kahn, L. (2021). What influences attitudes about artificial intelligence adoption: Evidence from U.S. local officials. PLOS ONE, 16(10), e0257732. https://doi.org/10.1371/journal.pone.0257732
Kaul, V., Enslin, S., & Gross, S. A. (2020). History of artificial intelligence in medicine. Gastrointestinal endoscopy, 92(4), 807–812.
Krejcie, R. V., & Morgan, D. W. 1970. Determining Sample Sizes For Research Activities. Educational and Psychological Measurement, 607-610.
Lee, D., & Kim, Y. (2022). Development of self-expression activity class program for elementary school students to cultivate AI literacy. Fourth Industrial Review, 2(1), 9-7. https://doi.org/10.20498/fir.2022.2.1.9.
Leite, H. (2025). Artificial intelligence in higher education: Research notes from a longitudinal study. Technological Forecasting & Social Change, 215, 124115. https://doi.org/10.1016/j.techfore.2025.124115
Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI conference on human factors in computing systems (pp. 1-16).
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041. https://doi.org/10.1016/j.caeai.2021.100041
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041. https://doi.org/10.1016/j.caeai.2021.100041.
Ng, D. T. K., Luo, W., Chan, H. M. Y., & Chu, S. K. W. (2022). Using digital story writing as a pedagogy to develop AI literacy among primary students. Computers and Education: Artificial Intelligence, 3, 100054. https://doi.org/10.1016/j.caeai.2022.100054
Ng, Z. Q. P., Ling, L. Y. J., Chew, H. S. J., & Lau, Y. (2022). The role of artificial intelligence in enhancing clinical nursing care: A scoping review. Journal of Nursing Management, 30(8), 3654–3674. doi:10.1111/jonm.13425.
Pailaha, A. D. (2023). The impact and issues of artificial intelligence in nursing science and healthcare settings. SAGE Open Nursing, 9, 23779608231196847.
Pallant, J. (2020). SPSS survival manual: A step by step guide to data analysis using IBM SPSS (7th ed.). McGraw-Hill Education.
Petricini T, Zipf S and Wu C (2025) RESEARCH-AI: Communicating academic honesty: teacher messages and student perceptions about generative AI. Front. Commun. 10:1544430.doi:10.3389/fcomm.2025.1544430.
Polanco-Levicán, K., & Salvo-Garrido, S. (2022). Understanding social media literacy: A systematic review of the concept and its competences. International journal of environmental research and public health, 19(14), 8807.
Ruksakulpiwat, S., Thorngthip, S., Niyomyart, A., Benjasirisan, C., Phianhasin, L., Aldossary, H., Ahmed, B. H., & Samai, T. (2024). A systematic review of the application of artificial intelligence in nursing care: where are we, and what’s next? Journal of Multidisciplinary Healthcare, 17(null), 1603–1616. doi:10.2147/JMDH. S459946.
Turós, M., Nagy, R., & Szűts, Z. (2025). What percentage of secondary school students do their homework with the help of artificial intelligence? A survey of attitudes towards artificial intelligence. Computers and Education: Artificial Intelligence, 8, 100394. https://doi.org/10.1016/j.caeai.2025.100394
Uppal, K., & Hajian, S. (2025). Students’ perceptions of ChatGPT in higher education: A study of academic enhancement, procrastination, and ethical concerns. European Journal of Educational Research, 14(1), 199–211. https://doi.org/10.12973/eu-jer.14.1.199.
Vettriselvan, R. (2025). Empowering Digital Education: The Future of Value-Based Learning in the Digital Era. In Empowering Value Co-Creation in the Digital Era (pp. 199-228). IGI Global Scientific Publishing.
Wang, B., Rau, P.-L. P., & Yuan, T. (2023). Measuring user competence in using artificial intelligence: validity and reliability of artificial intelligence literacy scale. Behaviour &InformationTechnology,42(9),1324–1337.doi:10.1080/0144929X.2022.2072768.
Zhang, L., Wang, Y., Li, X., & Yang, J. (2022). Developing an AI literacy curriculum for secondary education. Education and Information Technologies, 27, 15749–15770.
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