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.
RANK_REASON The cluster contains an academic paper detailing a study on the acceptance of AI tools in computer engineering education. [lever_c_demoted from research: ic=1 ai=1.0]
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