Abstract

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.

Highlights

  • Has any technology been as ubiquitous in human history as computer science is today

  • There are many motivation questionnaires used in educational psychology we have proposed the development of a specific questionnaire-sequence for this study

  • While the questionnaire proposed by Rheinberg et al (2001) is built around factors like probability of success, anxiety, interest, and challenge, we have focused on assessing the motivational contributions of the generated positive/negative emotions, challenge and active involvement during the e-learning experience

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Summary

Introduction

Has any technology been as ubiquitous in human history as computer science is today. Z. Katai computing (Grover and Pea 2013).The creation of a genuine educational program which ensures a proper initiation in computational thinking (CT) is a major endeavor. As in most countries there is already a severe computational literacy gap among the different segments of society, this educational program must be all inclusive and must address all irrespective of age, gender, race, culture, orientation or disability. In this study we have focused on one specific facet of diversity: sciences- vs humanities-oriented people. After Snow (1959) had introduced the term of “two cultures”, the concept of sciences/humanities-oriented learner arose and it was suggested that these two categories of people are characterized by different cognitive styles, often described as the individual difference in the way people acquire and process information (Witkin et al 1977; Achter et al 1999; Billington et al 2007). Since motivation plays a crucial role in learning and constitutes a key element in all the approaches to active learning (Valle et al 2011), the impact of diversity on learners’ motivation is a critically important aspect of the addressed educational issue

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