AI-Based Platform Design for Complex Thinking Assessment: A Case Study of an Ideathon Using the Transition Design Approach

Abstract

AbstractEmerging Artificial Intelligence-enhanced technology platforms in education warrant attention to exploring new learning strategies and dynamics. Keeping up with the accelerating momentum to bring classic traditional learning activities to Artificial Intelligence-supported platforms may unbalance the interest in developing the participants' higher-order thinking. This article presents case study research of an Artificial Intelligence-based technological platform to measure complex thinking traits of higher education participants in an Ideathon learning scenario. The didactical strategy was grounded in the Transition Design approach, with Sharing Economy as the challenge. An overview of the process for developing Artificial Intelligence-supported activities, the challenges and risks identified in the development, and a classification model and enhancements for future implementation in a subsequent pilot are presented. The findings set a guideline for balancing Artificial Intelligence-powered educational activities and the development of the participants' complex thinking.Keywords: Artificial intelligencecomplex thinkingtechnological platformIdeathontransition designclassification modelhigher educationeducational innovation AcknowledgmentThe authors acknowledge the technical support of Writing Lab, Institute for the Future of Education, Tecnologico de Monterrey, Mexico, in producing this work.Disclosure statementThe authors report no competing or conflicts of interest.Informed consentStudents participating in the Ideathon gave informed consent through Google Forms.Data availability statementData is available upon request.Additional informationFundingThe authors acknowledge the financial support from Tecnologico de Monterrey through the "Challenge-Based Research Funding Program 2022". Project ID # I001 – IFE001 – C1-T1 – E. "OpenResearchLab: innovation with artificial intelligence and robotics to scale domain levels of reasoning for complexity" (ID Novus N21-207), funded by the Institute for the Future of Education (IFE), Tecnologico de Monterrey and Instituto Politecnico Nacional Projects SIP20220557 and SIP-20231910.