Demographic factors shaping artificial intelligence (AI) perspectives: Exploring their impact on University students' academic performance - Ting Tin Tin; Koh Yi Chor; Wong Jing Hui; Wong Yan Cheng; Chaw Jun Kit; Wan Nor Al-Ashekin Wan Husin; Ali Aitizaz; Lee Kuok Tiung; Sunday A. Afolalu; Umar Farooq Khattak (Scopus, 2024)
Undergraduate students in Malaysia have shown increasing usage of AI in their studies, notably ChatGPT, prompting a need to examine its effects on their academic outcomes. This research studies the impact of demographic factors of students’ understanding of AI knowledge and their attitudes towards AI and their overall academic performance. The study scrutinizes the role of ages, gender, and program study on student’s AI knowledge and attitude towards AI, aiming to comprehend their implication on academic performance. Data was gathered from a varied group of undergraduates via questionnaires, a sample size of 107 students and analyzed using statistical software such as SPSS and the Pearson correlation method. The PROCESS macro examines the mediation effect of AI knowledge and on the relationship between demographic elements and attitudes towards AI, while the path analysis method using AMOS software is employed to study sequential relationships among these variables. The study confirms a positive correlation between age and both AI knowledge and attitude towards AI. However, no significant correlations were observed between gender or program study and AI knowledge and attitudes towards AI. This research provides valuable insight into the impact of demographic elements on AI knowledge and attitude towards AI, and academic performance, potentially influencing student;s future academic and career trajectories in the AI era.