AI-Automation Tooling in Computer Engineering Education: Mixed-Methods TAM/UTAUT Evidence for a General Acceptance Attitude
A study on undergraduate computer engineering students in Thailand found a generally positive attitude towards AI automation tooling, specifically the open-source platform n8n. The research utilized a mixed-methods approach, combining a Likert scale survey with qualitative feedback to assess constructs like performance expectancy, effort expectancy, and behavioral intention. While quantitative results indicated strong acceptance, qualitative analysis revealed a small group skeptical about output reliability, suggesting targeted instructional strategies to build trust and self-efficacy. AI
IMPACT Suggests AI automation tools can be effectively integrated into computer engineering curricula, with specific instructional levers identified for educators.