Relationship Between Artificial Intelligence (AI) in Supporting Differentiated Learning for Patient-Students in School in Hospital (SIH)

This study aims to identify the level of Artificial Intelligence (AI) usage in teaching at Schools in Hospitals (SiH), determine the level of effectiveness of differentiated learning, and analyze the relationship between both variables in the context of patient-students. The study employed a quantitative descriptive correlational design involving 48 SiH teachers selected through purposive sampling. Data were collected using a structured five-point Likert-scale questionnaire and analyzed using IBM SPSS Statistics. Descriptive analysis, the Shapiro–Wilk normality test, and Spearman’s correlation were conducted. The findings indicate that the level of AI usage (M = 2.91) and differentiated learning (M = 2.40) were at a moderate level. However, the correlation analysis revealed a significant and strong positive relationship between AI usage and differentiated learning (rₛ = 0.643, p < .05). The study concludes that AI has the potential to support a more flexible and adaptive implementation of differentiated learning in SiH. Future studies are recommended to examine the long-term effects of AI usage on the academic development and well-being of patient-students.

Artificial Intelligence, Differentiated Learning, School in Hospital

1. Bas, C., & Kiraz, A. (2025). The role of artificial intelligence in personalised STEM education. Journal of Educational Technology, 12(1), 45–60. [Google Scholar] [Crossref]

2. Creswell, J. W., & Creswell, J. D. (2021). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications. [Google Scholar] [Crossref]

3. Etikan, I., Musa, S. A., & Alkassim, R. S. (2020). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1–4. [Google Scholar] [Crossref]

4. Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2023). How to design and evaluate research in education (11th ed.). McGraw‑Hill Education. [Google Scholar] [Crossref]

5. Gligorea, A. (2023). Adaptive e‑learning systems powered by AI: A critical review. International Journal of Adaptive Learning, 9(2), 75–92. [Google Scholar] [Crossref]

6. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2022). Multivariate data analysis (8th ed.). Cengage Learning. [Google Scholar] [Crossref]

7. Hamdan Husein Batubara, et al. (2025). Teacher readiness and perception towards AI integration in classrooms. Malaysian Journal of Educational Innovation, 8(3), 112–130. [Google Scholar] [Crossref]

8. Haziq Saharuddin, M., et al. (2025). Optimising AI tools for personalised instructional design: A Malaysian context. Education and Information Technologies, 30(4), 2895–2910. [Google Scholar] [Crossref]

9. Joshi, A., Kale, S., Chandel, S., & Pal, D. K. (2020). Likert scale: Explored and explained. British Journal of Applied Science & Technology, 7(4), 396–403. [Google Scholar] [Crossref]

10. Küçükuncular, S., & Ertugan, S. (2025). Reducing teacher cognitive load through AI‑assisted lesson planning. Journal of Educational Computing Research, 62(1), 212–235. [Google Scholar] [Crossref]

11. Ministry of Education. (2021). Digital Education Transformation Plan 2021–2025. [Google Scholar] [Crossref]

12. Nor Lailatul Azilah, et al. (2025). Pembelajaran terbeza: Strategi untuk pendidikan inklusif di hospital sekolah. Jurnal Pendidikan Inklusif Malaysia, 6(1), 22–40. [Google Scholar] [Crossref]

13. Nurul Haida, & Zamri Mahamod. (2025). Fleksibiliti pedagogi dan kesejahteraan murid di SDH. Journal of Hospital School Education, 2(1), 15–30. [Google Scholar] [Crossref]

14. Nurul Haniza, et al. (2025). Era Pendidikan 5.0: AI dalam sistem pendidikan Malaysia. Asia Pacific Journal of Digital Education, 11(2), 98–115. [Google Scholar] [Crossref]

15. Pallant, J. (2020). SPSS survival manual: A step by step guide to data analysis using IBM SPSS (7th ed.). Open University Press. [Google Scholar] [Crossref]

16. Rajeswary, & Mohd Jasmy. (2025). Hubungan pengalaman mengajar dan keyakinan penggunaan AI dalam PdP. Malaysian Journal of Educational Research, 10(2), 57–76. [Google Scholar] [Crossref]

17. Regina Kana, et al. (2025). Use of smart tools to enhance understanding and motivation among learners with access barriers. International Journal of Educational Access, 7(3), 129–150. [Google Scholar] [Crossref]

18. Salkind, N. J. (2022). Exploring research (11th ed.). Pearson Education. [Google Scholar] [Crossref]

19. Taherdoost, H. (2022). Validity and reliability of questionnaires in research. International Journal of Academic Research, 4(2), 67–75. [Google Scholar] [Crossref]

20. UNESCO. (2023). Artificial Intelligence in Education: Challenges and Opportunities. UNESCO Publishing. [Google Scholar] [Crossref]

21. Wan Nur ‘Irfah Ilhami, & Mohd Isa Hamzah. (2024). Etika dan integriti akademik dalam penggunaan AI generatif. Journal of Ethics in Education Technology, 1(1), 10–27 [Google Scholar] [Crossref]

• Assessment of the Role of Artificial Intelligence in Repositioning TVET for Economic Development in Nigeria
• Teachers’ Use of Assure Model Instructional Design on Learners’ Problem Solving Efficacy in Secondary Schools in Bungoma County, Kenya
• “E-Booksan Ang Kaalaman”: Development, Validation, and Utilization of Electronic Book in Academic Performance of Grade 9 Students in Social Studies
• Analyzing EFL University Students’ Academic Speaking Skills Through Self-Recorded Video Presentation
• Major Findings of The Study on Total Quality Management in Teachers’ Education Institutions (TEIs) In Assam – An Evaluative Study