Exploring the factors of students' intention to participate in AI software development

Purpose: Although many universities have begun to provide artificial intelligence (AI)-related courses for students, the influence of the course on students' intention to participate in the development of AI-related products/services needs to be verified. In order to explore the factors that influence students' participation in AI services and system development, this study uses self-efficacy, AI literacy, and the theory of planned behaviour (TPB) to investigate students' intention to engage in AI software development. Design/methodology/approach: The questionnaire was distributed online to collect university students' responses in central Taiwan. The research model and eleven hypotheses are tested using 151 responses. The testing process adopted SmartPLS 3.3 and SPSS 26 software. Findings: AI programming self-efficacy, AI literacy, and course satisfaction directly affected the intention to participate in AI software development. Moreover, course playfulness significantly affected course satisfaction and AI literacy. However, course usefulness positively affected course satisfaction but did not significantly affect AI literacy and AI programming self-efficacy. Originality/value: The model improves our comprehension of the influence of AI literacy and AI programming self-efficacy on the intention. Moreover, the effects of AI course usefulness and playfulness on literacy and self-efficacy were verified. The findings and insights can help design the AI-related course and encourage university students to participate in AI software development. The study concludes with suggestions for course design for AI course instructors or related educators.