Factors Influencing Artificial Intelligence Adoption as Learning Support Media: an Extended Technology Acceptance Model Study in Bangka Belitung Islands
Keywords:
Artificial Intelligence, Extended Technology Acceptance Model, AI Anxiety, Academic Performance, Multi-Institutional AnalysisAbstract
The integration of artificial intelligence (AI) in higher education has accelerated globally, yet understanding of adoption factors remains fragmented, particularly in geographically isolated regions. This study extends the Technology Acceptance Model (TAM) by incorporating facilitating conditions, AI anxiety, and academic performance outcomes to analyze AI adoption patterns across multiple institutions in Bangka Belitung Islands, Indonesia. A cross-sectional quantitative design was employed with 523 students from five higher education institutions. Data were analyzed using SEM-PLS through SmartPLS 4.0, revealing that perceived ease of use demonstrated the strongest influence on actual AI system use (β=0.394, p<0.001), followed by perceived usefulness (β=0.327, p<0.001) and facilitating conditions (β=0.218, p<0.01). AI anxiety showed a significant negative effect on actual system use (β=-0.156, p<0.05), while actual system use strongly predicted academic performance (β=0.782, p<0.001). The extended model explained 68.4% variance in actual AI system use and 61.2% variance in academic performance. Multigroup analysis revealed significant differences between public and private institutions (p<0.05), with private institutions showing stronger technology acceptance patterns. These findings suggest that successful AI implementation requires holistic strategies addressing user experience design, institutional support infrastructure, and anxiety reduction programs tailored to institutional contexts in archipelagic regions.
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