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Computational Thinking (CT) is crucial for the advancement of the STEM field, where there continues to be a lack of female representation. Teaching and learning (T/L) of CT should incorporate didactic strategies that aim to eliminate gender biases and integrate girls/women into this context. In response to the question, "What didactic strategies have been implemented in the T/L of CT in primary and secondary education?". A systematic review was conducted following a PRISMA protocol specifically designed for this review. The study analysed Didactic Strategies (DS) and examined whether they incorporated the so‐called "minimum actions" (MA) proposed in this article as a strategy to integrate females into CT. The findings revealed a limited number of studies that implemented these actions. In conclusion, there is an urgent need to continue developing DS that incorporate these MA to effectively integrate girls and women into CT, allowing them to play a central role in its advancement and development. [ABSTRACT FROM AUTHOR]

Introduction: With the increasing amount of research around Computational Thinking (CT) and endeavors introducing CT into curricula worldwide, assessing CT at all levels of formal education is of utmost importance to ensure that CT-related learning objectives are met. This has contributed to a progressive increase in the number of validated and reliable CT assessments for K-12, including primary school. Researchers and practitioners are thus required to choose among multiple instruments, often overlapping in their age validity. Methods: In this study, we compare the psychometric properties of two of these instruments: the Beginners' CT test (BCTt), developed for grades 1-6, and the competent CT test (cCTt), validated for grades 3-4. Classical Test Theory and ItemResponse Theory (IRT) were employed on data acquired from 575 students in grades 3-4 to compare the properties of the two instruments and refine the limits of their validity. Results: The findings (i) establish the detailed psychometric properties of the BCTt in grades 3-4 for the first time, and (ii) through a comparison with students from the same country, indicate that the cCTt should be preferred for grades 3-4 as the cCTt is able to discriminate between students of low and medium ability. Conversely, while the BCTt, which is easier, shows a ceiling effect, it is better suited to discriminate between students in the low ability range. For these grades, the BCTt can thus be employed as a screening mechanism to identify low ability students. Discussion: In addition to providing recomendations for use of these instruments, the findings highlight the importance of comparing the psychometric properties of existing assessments, so that researchers and practitioners, including teachers and policy makers involved in digital education curricular reforms, may take informed decisions when selecting assessments. [ABSTRACT FROM AUTHOR]

The use of Artificial Intelligence (AI) offers new and thriving opportunities, but introduces also new risks and ethical issues that should be dealt with. We argue that the introduction of AI contents at schools through practical, hands-on, projects is the way to go to educate conscientious and critical citizens of the future, to awaken vocations among youth people, as well as to foster students' computational thinking skills. However, most existing programming platforms for education lack some of the required educational features to develop a complete understanding of AI. In this paper we present LearningML, a new platform aimed at learning supervised Machine Learning (ML), one of the most successful AI techniques that is in the basis of almost every current AI application. This work describes the main functionalities of the tool and discusses some decisions taken during its design. For its conception, we have taken into account lessons learned from the research literature on introducing AI in school and from the analysis of other educational tools built with the aim to allow learners to use ML. We offer as well some promising results obtained after a preliminary testing pilot workshop. Finally, the next steps in the development of LearningML are presented, focused on the face and instructional validation of the tool.

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]