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Investigating AI-based academic support acceptance and its impact on students’ performance in Malaysian and Pakistani higher education institutions

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Abstract

The rapid advancement of artificial intelligence (AI) technologies has led to a transformation in higher education worldwide. AI tools provide academic support to students anywhere and anytime to enhance their knowledge and skills. Those facing difficulties have been relying on traditional support and guidance. However, this support has experienced difficulties, including availability and accessibility. This study examines the potential of AI-powered tools to address these challenges, aiming to make academic support more accessible, efficient, and effective. This study focuses on understanding the determinants of AI tools' acceptance and use for academic support among students, influencing student satisfaction and academic performance in Pakistan and Malaysia. The research on AI tool acceptance and use in the higher education Institutions (HEI) context is still new and less explored in Pakistani and Malaysian higher education institutions. A theoretical model based on the Unified Theory of Acceptance and Use of Technology (UTAUT) and other factors was employed to identify factors that affect AI tool adoption in higher education. The survey research design was employed, and the total sample size was 305 respondents, with 203 students from Quaid-e-Awam University of Science and Technology (QUEST), Pakistan, and 102 students from Universiti Teknologi Malaysia (UTM). A “Partial least squares structural equation modeling (PLS-SEM) Analysis” was employed to assess the research model and hypotheses using SmartPls 4.0. In Pakistan and Malaysia, students are more concerned about using AI tools to improve their academic performance. The findings indicated that performance and effort expectancy, information accuracy of AI tools, pedagogical fit to meet the student’s expectations, and student interaction with tools were important factors in predicting the acceptance and use of AI tools among students of both countries in higher education, and the rising use of these AI tools has improved students’ satisfaction levels and significantly impacted students learning outcomes in both countries. Additionally, student engagement and personal innovativeness have not significantly affected the use of AI tools among students in both countries. This study provides a comprehensive analysis of AI tool adoption in the unique contexts of Pakistan and Malaysia, contributing to the broader discourse on technology integration in higher education.

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Acknowledgements

We thank the Research Management Centre (RMC) at Universiti Teknologi Malaysia (UTM) for allowing us to conduct this research (Q.J130000.21A2.07E10).

Funding

This work was funded by the Researchers Supporting Project Number (RSPD2024R564) at King Saud University, Riyadh, Saudi Arabia.

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Authors and Affiliations

  1. Faculty of Social Sciences and Humanities, School of Education, University Teknologi Malaysia, Johor Bahru, Malaysia

    Nisar Ahmed Dahri, Noraffandy Yahaya & Waleed Mugahed Al-Rahmi

  2. Computer Science Department, Community College, King Saud University, 11437, Riyadh, Saudi Arabia

    Waleed Mugahed Al-Rahmi & Fahad Alblehai

  3. Department of Computer Science, Quaid-e Awam University of Engineering, Science, and Technology, Nawabshah, Pakistan

    Muhammad Saleem Vighio

  4. Institute of Business Administration, Shah Abdul Latif University, Khairpur, Pakistan

    Rahim Bux Soomro

  5. Department of Philosophy, Ural Federal University named after the First President of Russia B. N. Yeltsin, 620002, Ekaterinburg, Russia

    Anna Shutaleva

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  1. Nisar Ahmed Dahri
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  2. Noraffandy Yahaya
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  3. Waleed Mugahed Al-Rahmi
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Correspondence to Nisar Ahmed Dahri or Noraffandy Yahaya.

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Dahri, N.A., Yahaya, N., Al-Rahmi, W.M. et al. Investigating AI-based academic support acceptance and its impact on students’ performance in Malaysian and Pakistani higher education institutions. Educ Inf Technol (2024). https://doi.org/10.1007/s10639-024-12599-x

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