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The Effect of Artificial Intelligence (AI) on Students' Learning

Author

Listed:
  • Hairunnisa Ma’amor
  • Nur'ain Achim
  • Nor Lela Ahmad
  • Nabila Suraya Roszaman
  • Najwa Noor Kamarul Anuar
  • Nur Camelia Aqielah Khairul Azwa
  • Sahira Nabila Abd Rahman
  • Nur Ain Aqilah Hamjah

Abstract

Various studies have been conducted to identify factors that contribute to student engagement, personalized learning experience, and student academic performance. The evolution of technology offers various benefits including in the education sector. To date, the use of Artificial Intelligence (AI) in education has been seen to provide various benefits. This study aims to identify the relationship between the usage of AI with student engagement, personalized learning experience, and student academic performance. Data was collected from 110 undergraduate students from the Faculty of Business and Management, UiTM Puncak Alam Campus using a questionnaire. 106 data were analyzed using SPSS version 29. The findings show that AI usage for study purposes significantly influences student’s engagement and academic performance. On the other hand, the usage of AI and personalized learning experience show no significant influence. This study not only provides a deeper understanding of the context of AI usage for better student engagement and academic performance but also gives valuable insight for UiTM and faculty specifically to develop strategies and modules that enhance the implementation and usage of AI in their learning activities.

Suggested Citation

  • Hairunnisa Ma’amor & Nur'ain Achim & Nor Lela Ahmad & Nabila Suraya Roszaman & Najwa Noor Kamarul Anuar & Nur Camelia Aqielah Khairul Azwa & Sahira Nabila Abd Rahman & Nur Ain Aqilah Hamjah, 2024. "The Effect of Artificial Intelligence (AI) on Students' Learning," Information Management and Business Review, AMH International, vol. 16(3), pages 856-867.
    • Handle: RePEc:rnd:arimbr:v:16:y:2024:i:3:p:856-867
    DOI: 10.22610/imbr.v16i3S(I)a.4178
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    1. Rose Luckin, 2017. "Towards artificial intelligence-based assessment systems," Nature Human Behaviour, Nature, vol. 1(3), pages 1-3, March.
    2. Kate Crawford & Ryan Calo, 2016. "There is a blind spot in AI research," Nature, Nature, vol. 538(7625), pages 311-313, October.
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