A Systematic Literature Review in Robotics Experiential Learning With Computational and Adversarial Thinking

Abstract

The rise of the Industrial Revolution 4.0 and the increasing reliance on the digital economy drive the need for a new set of skills, especially in robotics learning, that includes computational thinking (CT) and adversarial thinking (AT) for the young generation. The need for CT-related skills includes various fields, such as robotics, engineering, computer science, mathematics, music, arts, and humanities. Therefore, adopting robotic learning with CT and AT can enhance learning skills over the conventional learning model. This paper presents a systematic literature review on CT and AT practices in robotics learning to improve educational methods. This study conducts a systematic literature review from four databases: ACM, Scopus, IEEE Xplore, and ScienceDirect. Sixty-five studies in robotics learning to increase CT and AT skills were analyzed by applying the inclusion and exclusion criteria. The study's findings show that CT and AT are significant in training students to engage in robotics learning activities. These considerations will lead to strengthening their skill and critical thinking. The study also suggests that integrating these skills can prepare teachers for critical thinking and boost student learning. The findings suggest that CT and AT can directly adopt digital adversarial learning skills to improve overall robotics learning activities. For future studies, the difference in learning ages related to robotics activities with CT and AT applications can be studied to deeply comprehend the effectiveness of CT and AT applications.