Assessing implicit computational thinking in game-based learning: A logical puzzle game study

To date, extensive work has been devoted to incorporating computational thinking in K-12 education. Recognizing students' computational thinking stages in game-based learning environments is essential to capture unproductive learning and provide appropriate scaffolding. However, few reliable and valid computational thinking measures have been developed, especially in games, where computational knowledge acquisition and computational skill construction are implicit. This study introduced an innovative approach to explore students' implicit computational thinking through various explicit factors in game-based learning, with a specific focus on Zoombinis, a logical puzzle-based game designed to enhance students' computational thinking skills. Our results showed that factors such as duration, accuracy, number of actions and puzzle difficulty were significantly related to students' computational thinking stages, while gender and grade level were not. Besides, findings indicated gameplay performance has the potential to reveal students' computational thinking stages and skills. Effective performance (shorter duration, fewer actions and higher accuracy) indicated practical problem-solving strategies and systematic computational thinking stages (eg, Algorithm Design). This work helps simplify the process of implicit computational thinking assessment in games by observing the explicit factors and gameplay performance. These insights will serve to enhance the application of gamification in K-12 computational thinking education, offering a more efficient method to understanding and fostering students' computational thinking skills.