Towards the development of complex thinking in university students: Mixed methods with ideathon and artificial intelligence

Abstract

This article examines the capacity of an artificial intelligence (AI) platform to assess university students' mastery of complex thinking. Central questions addressed include the identification of essential technical elements that contribute to the platform's effectiveness, and how the AI platform can boost student motivation and cultivate complex thinking. The research employed a mixed-methods approach, anchored by an Ideathon centered on the Sharing Economy. Qualitative insights were drawn from semi-structured interviews with nine university students. The results indicate that the platform effectively evaluates complex thinking proficiency, differentiating between systemic, scientific, and innovative thinking. Notably, the AI-driven personalization of the platform was found to significantly enhance student motivation. This study highlights the capabilities of AI platforms in competency assessment and suggests that future research should investigate how such data can inform strategies to develop complex reasoning among diverse university student populations.

Keywords

• Human-computer interface
• Cultural and social implications
• Teaching/learning strategies
• Distributed learning environments
• Data science applications in educa-tion