Readiness to Implement Artificial Intelligence (AI)-Based Learning: A Case Study among Teachers at the Faculty of Technical and Vocational, UPSI

Abstract

This study explores the readiness of pre-service teachers to implement Artificial Intelligence (AI)-based learning within the Faculty of Technical and Vocational Education at Sultan Idris Education University (UPSI). Despite the increasing integration of AI into Malaysia’s national education curriculum by 2027, many pre-service teachers demonstrate limited knowledge, technical skills, and positive attitudes toward AI adoption in educational settings. Employing a quantitative research design, data were collected through a structured questionnaire distributed to 184 purposively selected respondents. The study aimed to examine the relationships between knowledge, skills, and attitudes, and their influence on pre-service teachers’ readiness to apply AI in teaching and learning. Findings revealed significant positive correlations between readiness and knowledge (r = 0.822), skills (r = 0.795), and attitudes (r = 0.792), with all results statistically significant at p < 0.001. These results underscore the importance of equipping future educators with foundational AI competencies. The study recommends structured training programs and early exposure to AI technologies to enhance the digital teaching capabilities of future educators.