The research results we present in this paper reveal that properly calibrated e-learning tools have potential to effectively promote the algorithmic thinking of both science-oriented and humanities-oriented students. After students had watched an illustration (by a folk dance choreography) and an animation of the studied sorting algorithm (bubble sort), they were invited to predict and perform [ (1) to reconstruct on the same input; (2) to orchestrate on a random sequence stored in a white array; (3) to orchestrate on a black-box sequence] the entire step sequence of the algorithm (using the interactive visual learning environment we developed). The results of the experiment show that while science-oriented students' performance proved superior to those of their humanities-oriented colleagues, the differences were observed to diminish as both groups advanced with their e-learning tasks. Although drawing general conclusions would be premature, we can conclude that there are no unbridgeable differences in the way these two groups relate to e-learning processes that aim to promote algorithmic thinking. Our findings also emphasize the key importance of some motivational principles in facilitating algorithmic thinking: the principle of moderate and progressive challenge, the principle of gradual shift from concrete to abstract and the principle of genuine active involvement.

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We proposed to investigate whether properly calibrated e-learning environments can efficiently promote computational thinking of both sciences- and humanities-oriented people. We invited two groups of students (sciences- vs. humanities-oriented members) to participate in a six-stage learning session: to watch a folk-dance illustration (s1) and an animation (s2) of the bubble-sort algorithm; to reconstruct the algorithm on the same input (s3); to orchestrate the algorithm on a random input stored in a white(s4)/black(s5) array (visible/invisible sequence) and to watch a parallel simulation of several sorting algorithms as they work side-by-side on different color-scale bars (s6). To assess the current motivation of students we created nine specific questionnaires (Q1–9). The experiment we conducted included the following task sequence: Q1–2, s1, Q3, s2, Q4, s3, Q5, s4, Q6, s5, Q7, s6, Q8–9. We focused on assessing the motivational contributions of the generated (situational factors) emotions, challenge and active involvement during the e-learning experience. Research results revealed that there are no unbridgeable differences in the way these two groups relate to e-learning processes that aim to promote computational thinking. Although sciences-oriented students’ motivational-scores were consistently superior to their humanities-oriented colleagues, there was strong correlation between them; furthermore, differences diminished as both groups advanced with their learning tasks.

In this paper, we are going to introduce a new multi-sensory method and software, which improve the teaching-learning process of the recursive procedures and functions. The presented method can also be categorized as a blending or hybrid teaching-learning strategy that applies to technologically enhanced pedagogy. (The software was initially designed to be utilized especially in the teaching phase of the educational process, but it can also be efficiently used as an e-learning tool.) ß