Our exploratory study focuses on the cognitive processes and strategies underlying computational thinking. Our main objective is to examine problem-solving strategies and cognitive load during a block-based programming task in greater detail. In doing so, we aim to explore potential connections to other cognitive abilities such as working memory capacity or fluid intelligence.

To achieve this goal, we employ eye-tracking technology to analyze the thought processes of our learners. Our research aims to uncover how learners tackle block-based programming tasks, whether there are different strategies involved, and what influences the success of the learners.

Furthermore, we take an additional step and broaden the perspective of our study. We combine eye-tracking data from cognitive tests specifically oriented towards fluid intelligence, working memory capacity, and computational thinking. This approach could contribute to a more precise understanding of the relationship between programming knowledge and computational thinking.