Effects of troubleshooting robotics learning on students’ engagement, computational thinking, and programming skills

Abstract

Learning engagement is an important indicator of active learning outcomes. Computational thinking is a basic competency required in the 21st century. Troubleshooting learning is helpful to enhance students’ computational thinking and engagement, as its targeted error analysis addresses traditional learning’s limitation of insufficient guidance on error-prone points. However, the role of troubleshooting in students’ engagement and computational thinking in robotics programming learning is to be explored. To fill in this gap, the current study explored the effects of troubleshooting robotics programming learning on students’ engagement, computational thinking, and programming skills. A quasi-experimental study was conducted to explore the effects of troubleshooting learning on students’ robotics programming learning by comparing students’ learning results in two courses instructed by the same instructor (one instructed with a problem-based method, the other instructed with a troubleshooting method). The participants were seventy-nine students from a university in China. Questionnaires, tests, and work analyses were used to measure students’ engagement, computational thinking, and programming skills. The results indicated that troubleshooting learning is more effective in enhancing students’ engagement (i.e., behavioral, cognitive, and emotional engagement), computational thinking (i.e., cooperativity, critical thinking, and creativity) and programming learning (i.e., data representation). The findings provide insight into troubleshooting-supported robotics programming learning. Different types of troubleshooting tasks with progressive difficulty are effective in enhancing students’ learning. Troubleshooting could be used in the early stages of programming learning to help students master the error prone areas of programming.