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

教育技术 高等教育 学业成绩 心理学 数学教育 医学教育 知识管理 教育学 计算机科学 经济增长 经济 医学
作者
Nisar Ahmed Dahri,Noraffandy Yahaya,Waleed Mugahed Al-Rahmi,Muhammad Saleem Vighio,Fahad Alblehai,Rahim Bux Soomro,Anna Shutaleva
出处
期刊:Education and Information Technologies [Springer Science+Business Media]
卷期号:29 (14): 18695-18744 被引量:82
标识
DOI:10.1007/s10639-024-12599-x
摘要

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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