Search

Computational thinking (CT) is being consolidated as a key set of problem-solving skills that must be developed by the students to excel in our software-driven society. However, in psychological terms, CT is still a poorly defined construct, given that its nomological network has not been established yet. In a previous paper, we started to address this issue studying the correlations between CT and some fundamental cognitive variables, such as primary mental abilities and problem-solving ability. The current work deepens in the same direction as it aims to extend the nomological network of CT with non-cognitive factors, through the study of the correlations between CT, self-efficacy and the several dimensions from the ‘Big Five’ model of human personality: Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. To do so, the Computational Thinking Test (CTt) and some additional self-efficacy items are administered on a sample of 1251 Spanish students from 5th to 10th grade ( N = 1251), and the Big Five Questionnaire-Children version (BFQ-C) is also taken by a subsample from the above ( n = 99). Results show statistically significant correlations between CT and self-efficacy perception relative to CT performance ( r s = 0.41), in which gender differences in favor of males are found ( d = 0.42). Moreover, results show statistically significant correlations between CT and: Openness to Experience ( r = 0.41), Extraversion ( r = 0.30), and Conscientiousness ( r = 0.27). These findings are consistent with the existing literature except for the unexpected correlation between CT and the Extraversion factor of personality, which is consequently discussed in detail. Overall, our findings corroborate the existence of a non-cognitive side of CT that should be taken into account by educational policies and interventions aimed at fostering CT. As a final contribution, the extended nomological network of CT integrating cognitive and non-cognitive variables is depicted. [ABSTRACT FROM AUTHOR]

Computational thinking (CT) is being located at the focus of educational innovation, as a set of problem-solving skills that must be acquired by the new generations of students to thrive in a digital world full of objects driven by software. However, there is still no consensus on a CT definition or how to measure it. In response, we attempt to address both issues from a psychometric approach. On the one hand, a Computational Thinking Test (CTt) is administered on a sample of 1,251 Spanish students from 5th to 10th grade, so its descriptive statistics and reliability are reported in this paper. On the second hand, the criterion validity of the CTt is studied with respect to other standardized psychological tests: the Primary Mental Abilities (PMA) battery, and the RP30 problem-solving test. Thus, it is intended to provide a new instrument for CT measurement and additionally give evidence of the nature of CT through its associations with key related psychological constructs. Results show statistically significant correlations at least moderately intense between CT and: spatial ability ( r = 0.44), reasoning ability ( r = 0.44), and problem-solving ability ( r = 0.67). These results are consistent with recent theoretical proposals linking CT to some components of the Cattel-Horn-Carroll (CHC) model of intelligence, and corroborate the conceptualization of CT as a problem-solving ability. [ABSTRACT FROM AUTHOR]

Several authors and studies highlight the benefits of the integration of Computer Science into K-12 education. Applications such as Scratch have been demonstrated to be effective in educational environments. The aim of this study is to assess the use of a Visual Programming Language using Scratch in classroom practice, analyzing the outcomes and attitudes of 107 primary school students from 5th to 6th grade in five different schools in Spain. The intervention takes place in two academic years analyzing the practice of integrating coding and visual blocks programming in sciences and arts. The “Computational concepts and computational practices” dimension details a quasi-experimental approach, which showed significant improvement regarding learning programming concepts, logic, and computational practices with an active approach. The “Learning processes and coding in primary education” dimension analyzes the practice of the experimental group through questionnaires and structured observation. In this pedagogical design, students interact and create their own content related to curricular areas with several advantages, such as motivation, fun, commitment, and enthusiasm, showing improvements related to computational thinking and computational practices. Understanding of computational concepts through an active approach, Project Based Learning, usefulness, motivation, and commitment underline the importance and effectiveness of implementing a Visual Programming Language from active methodologies in primary education. Due to the aforementioned benefits and positive results obtained in this research, it is recommended to implement a Visual Programming Language in educational settings in 5th and 6th grade in primary education through a cross-curricular implementation. [ABSTRACT FROM AUTHOR]

There is increasing effort to integrate Computational Thinking (CT) curricula across all education levels. Therefore, research on CT assessment has lately progressed towards developing and validating reliable CT assessment tools, which are crucial for evaluating students' potential learning progress and thus the effectiveness of suggested curricular programs. Several CT assessment tools were developed for elementary, high-school, and university students over the last years. Moreover, associations between CT scores and other cognitive abilities were unraveled. However, studies on the topic in primary school level are scarce. Like the general concept of intelligence, CT remains broadly defined as the ability to combine algorithmic operations to form complex solutions in order to solve problems effectively, utilizing concepts of computer science with or without the use of computers. In this study, we aimed at specifying a cognitive definition of CT, focusing on the under-investigated population of primary school children. Since validated assessment tools for this age group were not available, we adapted a validated CT test, which was initially designed for middle school students. In our study participated 192 third and fourth graders. The analyses revealed promising results on the reliability of the adapted CT assessment for primary school students. Moreover, findings indicated CT's positive associations with i. complex numerical abilities, ii. verbal reasoning abilities, and iii. non-verbal visuospatial abilities. Our results indicate similarities but also differences in associations of CT with other cognitive abilities in primary school children compared to other age groups. In summary: i. numerical abilities seem to associate with CT at the primary school level, whereas this seems not the case later on in education, ii. verbal abilities seem to associate with CT both along primary and secondary education levels, and iii. non-verbal reasoning abilities seem to associate with CT from primary education level to the university level and beyond. These differences imply that several basic cognitive abilities support CT abilities and CT development differentially across ages. • The cognitive development of computational thinking is differential across age. • Computational thinking builds on a convolute of several other cognitive abilities. • Computational thinking is associated with verbal reasoning abilities. • Computational thinking is associated with non-verbal visuospatial abilities. • Computational thinking is correlated to numerical abilities in primary school. [ABSTRACT FROM AUTHOR]