An Empirical Study of the Computational Thinking Learning Game, “Online Robot City”

Abstract

Having strong computational thinking (CT) skills is key for students studying computer science (CS) and STEM-related fields. However, relying too heavily on programming languages can hinder students' understanding and application of CT concepts. Therefore, to effectively promote the learning of CT, this study conducted a quasi-experimental design to integrate two different questioning strategies into the Online Robot City game for teaching purposes. The study aimed to explore the impact of using the 5W1H strategy and the context-based concept mapping strategy for information gathering and problem decomposition on students' achievement in CT and on their learning behavior patterns. The results are expected to respond to the importance of different learning approaches, in particular the context-based thinking method like the context-based concept mapping strategy proposed in this study, which may make relatively more contributions to CT learning achievement and self-efficacy.