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The results of qualitative and quantitative investigations conducted with individuals who learned algorithms in school are presented in this article. In these investigations, eye-tracking technology was used to follow the process of solving algorithmic problems. The algorithmic problems were presented in two comparable variants: in a pseudocode and flowchart. The eye-tracking data resulted in both qualitative (films registering the gaze paths) and quantitative measures, which allowed the detection and interpretation of the differences in the task-solving strategies between those who found the correct answer and those that did not. The results confirmed a hypothesis that use of the formal notation characteristic of a programming language for presenting algorithms is often a practical difficulty in the process of solving even simple tasks. This study opens a new direction of research; they show that eye-tracking technology can be used to optimise the educational process of learning programming.
Andrzejewska et al. (Thu,) studied this question.