Log-Based Analysis of Creativity in the Context of Computational Thinking

Computational thinking (CT) and creativity have been recognized as crucial skills for adapting to the current digital era. However, despite being extensively studied over the last few decades, research on their associations has only emerged recently. We report on a study that examined how creativity is manifested in the context of CT, specifically while solving computational problems in an online game-based learning environment for early programming. We took a learning analytics log-based approach to evaluate measures of CT and creativity. We developed a Python algorithm to automatically analyze the logged solutions across four creativity measures. This allowed for an objective, quantitative, multidimensional analysis of 52,438 submissions of N = 111 primary and secondary school students over 85 tasks. We examined the relationships between measures of creativity, game level, and CT, utilized exploratory analysis to investigate how measures of creativity differ across age groups, and explored how these measures characterize students. Our findings suggest that creativity does not decrease throughout the game despite the increased difficulty and its mechanics that penalize creative solutions. We also point out how various dimensions of creativity play different roles in learning. These findings suggest that educators should foster intrinsic motivation and encourage students to explore multiple solution paths to enhance both CT and creativity skills. Researchers should keep investigating mechanisms to assess and enhance creativity in learning environments and explore the influence of personal and contextual factors.