Integration of cognitive conflict in generative learning model to enhancing students’ creative thinking skills

Abstract

In the complexity of the Fourth Industrial Revolution era, the importance of creative thinking is increasingly emphasized in the context of learning computing and algorithms. These skills are instrumental in inspiring innovative solutions, addressing complex challenges, and fostering the development of advanced technologies that characterize the transformative landscape of Industrial Revolution 4.0. This study aims to determine the effectiveness of the generative learning model based on cognitive conflict in improving the creative thinking skills (CTS) and learning outcomes of students in the computational physics and algorithms & programming courses. This research used mixed methods consisting of pretest-posttest control group design and snowballing technique. The research instruments consist of cognitive tests, psychomotor tests, affective tests, CTS tests, observation questionnaires, and interviews. The research sample consisted of 138 students taking computational physics and algorithms & programming courses. Quantitative data were analyzed using multivariate analysis of variance and qualitative data were analyzed using narrative analysis. The findings indicate that this model effectively improves students’ CTS and learning outcomes. Furthermore, the cognitive conflict aspect encourages students to be creative in analyzing and solving problems. This model has the potential to be used to optimize students’ potential in facing the demands of the fourth industrial revolution.