Designing miniatures for a science and technology contest: The role of metacognitive performance in error-based learning

Abstract The process of error detection, explanation, and correction is essential in project making. Such structured error-based learning is thought to occur via active exploration of metacognitive processes. To understand how error-based learning can strengthen metacognitive performance, this study focused on hands-on project making in a STEAM contest. According to trait activation theory, participants practice metacognitive skills to continue improving their project functions, this study explored how participants’ motivation in a hands-on project affected the three types of metacognitive performance: monitoring of cognition, knowledge of cognition, and regulation of cognition. This study utilized purposive sampling and delivered a questionnaire to participants in a STEAM contest called PowerTech. Confirmatory factor analysis and structural equation modeling were performed to verify the research model. The results indicated that the intrinsic motivation to attend the contest was positively related to the three types of metacognitive performance, and negatively related to anxiety about losing the contest. The implication of this study is that when involved in a hands-on project, metacognitive ability can be enhanced through the practice of detection, explanation, and correction while working on a project.