![Computational thinking is an independent skill, since only 51% of its variance is reducible to known psychological variables [7, 8].](https://www.researchgate.net/profile/Jesus-Moreno-Leon/publication/325352993/figure/fig1/AS:636692188897284@1528810655748/Computational-thinking-is-an-independent-skill-since-only-51-of-its-variance-is_Q320.jpg)
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On computational thinking as a universal skill: A review of the latest research on this ability
Abstract and Figures
In recent years we are witnessing movements around the world to bring computer programming to schools. Lots of these initiatives, however, have been conceived to address the shortage of professionals in the technology sector, an approach that is encouraged by the software industry. On the contrary, this article argues that the focus should swift towards computational thinking, an ability that goes far beyond computer science or technology, fostering fundamental skills for the citizens of the twenty-first century. In this paper we summarize the findings of recent investigations that study computational thinking from different perspectives, explaining what this new skill is made of, presenting outcomes of school interventions showing relationships between the development of this ability and improvements in different subjects and soft skills, presenting technologies to foster its development, and reviewing tools that support educators in the assessment of this skill.
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... The biggest problem with these definitions of CT is the fact that the proposed CT concepts derive from general scientific practices and do not relate specifically to computer science. This suggests an imperialistic flavor [43], [46] . In fact, the UNESCO curricular guidelines [27] state that "programming is a rapid, specific and suitable way for students to gain experience of solving problems" and that "[t] eachers should stress the methodological aspects of problem solving: programming is just a means to an end, rather than a goal in itself." ...
In order to assess the extent to which text-mining techniques can be used to gain insights into a particular topic area, we apply hierarchical word clustering and the Term Frequency-Inverse Document Frequency (TF-IDF) measure to articles on computer programming published since the 1970s, when research articles on teaching programming are now more readily available in PDF files. Study 1 compares two sets of papers published before and after the introduction of the concept of Computational Thinking in 2006 to highlight the changes seen in these research sets. Articles mentioned in frequently cited review papers were selected as the target articles to ensure the quality of the sample. Study 2 extends the sample pool to include a range of papers published after the 1970s, allowing us to examine the stability of the conceptual structures identified in Study 1. In both studies, the obtained word clusters or concepts align with known research trends in the programming-education literature. The significance and potential of text-mining techniques are also discussed.
... This finding, directly and indirectly, is in line with the results of some previous studies (e.g. Kafai, 2016;Lewalter & Neubauer, 2020;Moreno-León et al., 2018;So et al., 2020). Researchers believe that by programming exercises, some factors related to digital informal learning, such as identifying an unclear problem (Wing, 2011), and evaluating its function (Ota et al., 2016) CT skills improve (Moon et al., 2020). ...
... Similarly, Grover and Pea (2018) proposed CT practices, including problem decomposition, creating computational artifacts, testing, debugging, iterative refinement (incremental development), and collaboration and creativity (now regarded as a cross-cutting twenty-first century skill). Moreno-León et al. (2018) concluded that the focus should shift from general programming to CT. However, these aforementioned studies are limited, as they only discussed the components of CT, associated outcomes, and tools used to foster CT skills. ...
Unplugged activities as a low-cost solution to foster computational thinking (CT) skills seem to be a trend in recent years. However, current evidence of the effectiveness of unplugged activities in promoting students’ CT skills has been inconsistent. To understand the potential of unplugged activities on computational thinking skills, a systematic review and meta-analysis were conducted. Our review of 49 studies examined the influence of unplugged activities to improve students’ CT skills in K–12 education between 2006 and 2022. The literature review showed that studies on CT skills were mainly (81.64%) conducted in computer science and STEM education, with board and card games being the most common unplugged activities for fostering CT skills in K–12 education. CT diagnostic tools (36.37%) were frequently used as assessment tools. A follow-up meta-analysis of 13 studies with 16 effect sizes showed a generally large overall effect size (Hedges’s g = 1.028, 95% CI [0.641, 1.415], p < 0.001) for the use of unplugged activities in promoting students’ CT skills. The analysis of several moderator variables (i.e., grade level, class size, intervention duration, and learning tools) and their possible effects on CT skills indicated that unplugged activities are a promising instructional strategy for enhancing students’ CT skills. Taken together, the results highlight the affordances of unplugged pedagogy for promoting CT skills in K–12 education. Recommendations for policies, practice, and research are provided accordingly.
... A training process for computational thinking skills can occur in several ways. The instructions can be computer guided in digital environments, but it is also possible to learn CT in a more classical learning setting without digital technologies [32]. Even though digital technologies are not necessary, various studies have already demonstrated that, nevertheless, technologies offer suitable opportunities to learn CT effectively and in a personalized way [25]- [27]. ...
Addressing and solving challenges by designing innovative artifacts is one of the main objectives of design science research (DSR). However, to achieve this goal, learning the theory of DSR and its methodology alone is not enough. We argue that computational thinking (CT) is an important skill set for design science researchers, since it helps to understand and structure problems from a computational point of view, which is an important basis for developing effective and innovative information system artifacts. CT consists of four core components: (1) dividing the problem, (2) abstraction, (3) pattern recognition, and (4) algorithmic thinking. Therefore, it is a skill set that can support DSR researchers in a broad way. However, so far, CT is rarely taught and trained and mainly not part of DSR courses. To close this gap and to train CT comprehensively, we develop a course based on low code programming, in other words, programming with little to no code. Our training can be embedded in DSR courses in a modular way. Thus, during a DSR course, students and researchers can develop and improve various prototypes with little effort and transfer the acquired competence to new design projects. As a central contribution of our study, we show how the training of CT can be applied in a modular way in DSR courses.KeywordsTransferable SkillsComputational ThinkingDesign Science Research
... The systematic review of computational thinking development through programming in Scratch was presented by Zhang and Nouri [75]. Also, authors [76,77,78,79,80] show the review in the computer thinking area. ...
This study presents review of 7580 papers in 13 academic journals, published from January 2015 to January 2020. After a detailed analysis of all papers, 46 papers were further selected showing research on a student population aged between 6 and 15 years old. In order for the paper to be included in the research, the condition was that the paper deals with teaching at least one of the following content areas: programming languages, game design, computer thinking (CT), algorithmic thinking and robotics programming. This study shows the representation of the listed content area in reviewed papers for the specified time period as well as a detailed analysis of the selected papers. Available data about study, participants and education level, country (first author), learning domain, teaching tools, research questions, hypothesis, pre/post-test results, interviews, control groups, course duration, research design, previous experience, project or grant and re-search purpose in detected papers were analysed. In addition, impact of studying some of the listed content areas on student learning performance, motivation, attitude and perception were investigated.
This article presents a systematic literature review (SLR) on the effects of serious games, or more specifically educational games that aim to teach Computational Thinking (CT) skills to primary school students. Sixty one studies from various data sources were evaluated based on the CT skills and programming concepts addressed, the evaluation instruments used, the target audience, the learning outcomes and their results. The findings of the studies on the efficiency or impact of educational games on the acquisition of the proposed topics were positive, indicating that educational programming games can help primary school students develop CT skills or understand fundamental programming concepts. Additionally, the results suggest a general positive attitude towards the use of an educational game for learning purposes, while students perceive games as a great motivator for engaging in CT activities. Finally, the research discusses research gaps and shortages, as well as methodological limitations and recommendations for future work in the relevant domain.
As the emerging field of equity in STEM education continues to grow, debates are also growing surrounding how to best serve populations with historically restricted access and successful outcomes within the STEM fields. In this article, a group of doctoral students who took a course titled Equity in STEM Education discussed their takeaways regarding the literature introduced in the course. The topics covered in this article center around Gutiérrez’s (2007) equity framework of power, identity, access, and achievement. Through the lens of the equity framework, the dimension of power will be used to present discourse on the sociopolitical turn in STEM education. Identity will be used to explore debates on race, poverty, gender, and sexuality within STEM equity and education. Access will be used to examine discussions on students’ ability to achieve STEM equity in rural settings and within specific domains such as computer science. Finally, achievement will be used to explore arguments on both sides of the achievement gap research. To conclude, we urge researchers, educators, and policymakers to listen and act upon the work of contemporary scholars in order to achieve an equitable STEM education system.
Computational thinking (CT) is an essential skill required for every individual in the digital era to become creative problem solvers. The purpose of this research is to investigate the relationships between computational thinking skills, the Big Five personality factors, and learning motivation using structural equation modeling (SEM). The research administered the computational thinking scale, NEO FFI scale, and Motivated Strategies for Learning Questionnaire to a sample of 92 students pursuing degrees in Computer Science and Engineering. Based on the result analysis, it was determined that both personality and learning motivation had positive and significant impacts on computation thinking skills. Personality had a major contribution to the prediction of CT, with consciousness being the most influential predictor. The findings of this study suggest that educators and academics should focus on the significance of the psychological side of CT for the improvement of students’ CT skills.
Recent studies suggest that computational thinking, composed of the skills of abstraction, decomposition, algorithmization, debugging, and problem-solving, is the fundamental skill for scientific, technological, and economic development for the twenty-first century. However, this diagnosis that is unveiled in rich countries remains nebulous for poor countries. The problem is that education in computational thinking is fundamental for countries to insert themselves in the international arena in an advantageous way and thus achieve the welfare goals for the population of each country. The objective of this research was to make a bibliographic review that shows the state of the art in the teaching of computer programming and computational thinking in the 5 continents. In the review, the advances in the countries of Europe, North America, Oceania, and Asia were observed, whereas in Latin America and Africa, the advances are still basic in some countries and non-existent in others. This review is based on Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA). The main search terms were “Computational thinking” and “Teaching computer programming.” The search was performed in the ACM, Conference on Computational Thinking Education (Hong-Kong), Google Scholar, WOS, and SCOPUS databases, from October until December 2020, whose publication year was from 2016 onward. One of the main results found is that the teaching of computational thinking in England was implemented in schools in 2014; in Germany, it has been implemented since 2016 at a transversal level in universities; in South Korea, China, and Taiwan, it has been implemented since 2016. However, in Latin America and Africa governments, the subject is still not considered.
Computational thinking is nowadays being widely adopted and investigated. Educators and researchers are using two main approaches to teach these skills in schools: with computer programming exercises, and with unplugged activities that do not require the use of digital devices or any kind of specific hardware. While the former is the mainstream approach, the latter is especially important for schools that do not have proper technology resources, Internet connections or even electrical power. However, there is a lack of investigations that prove the effectiveness of the unplugged activities in the development of computational thinking skills, particularly for primary schools. This paper, which summarizes a quasi-experiment carried out in two primary schools in Spain, tries to shed some light on this regard. The results show that students in the experimental groups, who took part in the unplugged activities, enhanced their computational thinking skills significantly more than their peers in the control groups who did not participate during the classes, proving that the unplugged approach may be effective for the development of this ability.
Computational thinking (CT) is emerging as a key set of problem-solving skills that must be developed by the new generations of digital learners. However, there is still a lack of consensus on a formal CT definition, on how CT should be integrated in educational settings, and specially on how CT can be properly assessed. The latter is an extremely relevant and urgent topic because without reliable and valid assessment tools, CT might lose its potential of making its way into educational curricula. In response, this paper is aimed at presenting the convergent validity of one of the major recent attempts to assess CT from a summative-aptitudinal perspective: the Computational Thinking Test (CTt). The convergent validity of the CTt is studied in middle school Spanish samples with respect to other two CT assessment tools, which are coming from different perspectives: the Bebras Tasks, built from a skill-transfer approach; and Dr. Scratch, an automated tool designed from a formative-iterative approach. Our results show statistically significant, positive and moderately intense, correlations between the CTt and a selected set of Bebras Tasks (r=0.52); and between the CTt and Dr. Scratch (predictive value r=0.44; concurrent value r=0.53). These results support the statement that CTt is partially convergent with Bebras Tasks and with Dr. Scratch. Finally, we discuss if these three tools are complementary and may be combined in middle school.
Programming and computational thinking skills are promoted in schools worldwide. However, there is still a lack of tools that assist learners and educators in the assessment of these skills. We have implemented an assessment tool, called Dr. Scratch, that analyzes Scratch projects with the aim to assess the level of development of several aspects of computational thinking. One of the issues to address in order to show its validity is to compare the (automatic) evaluations provided by the tool with the (manual) evaluations by (human) experts. In this paper we compare the assessments provided by Dr. Scratch with over 450 evaluations of Scratch projects given by 16 experts in computer science education. Our results show strong correlations between automatic and manual evaluations. As there is an ample debate among educators on the use of this type of tools, we discuss the implications and limitations, and provide recommendations for further research.
In the last years, socialization of the software development process has been proven to be an emergent practice, becoming social development platforms (such as GitHub or GitLab) very popular among software developers. However, little is still known about how social factors inuence software development. In particular, in this paper we focus on how socialization affects the learning of programming skills, as developing software can be considered, in part, a continuous learning process. Aiming to shed some light in this regard, we analyze the social interactions of almost 70,000 users and the sophistication of over 1.5 million software products authored by them in the Scratch platform, the most popular social coding site for learning to program. The results indicate that there is a relationship between the social conducts of users and the improvement of their programming abilities, showing that more social actions performed by users is positively associated with more sophistication in their programs. Furthermore, the results also provide evidence that the relationship of social factors with the development of software programming skills tends to grow with time.
Purpose
The purpose of this article is to review and discuss the varied ways computer programming is introduced to schools and families as a new form of learning. The paper examines the rhetoric around coding within academic journals and popular media articles over the past three decades. This article argues that despite the best intentions of media researchers and enthusiasts, if the rhetoric around computer science (CS) in all K-12 schools is to become a reality, there first needs to be a greater focus on monitoring such rhetoric and better understanding exactly how programming is presented to the wider public.
Design/methodology/approach
This paper represents an analysis of 67 peer-reviewed books and journal articles as well as news articles and editorials related to students’ learning (or needing to learn) computer programming on the K-12 level. In terms of criteria for inclusion, in addition to publication date and article readership, there were three considerations: the article needed to focus on CS on the K-12 grade levels; the article needed to focus on introductory computer programming initiatives, rather than more advanced courses/topics); the article needed to specifically focus on school-based learning environments.
Findings
Findings point to three distinct ways in which introductory coding initiatives have been portrayed (and been perceived): new literacy, “grounded” math and technical skill. Ultimately, the paper does not propose a single defining metaphor. Rather it argues that the metaphors one selects matter considerably in determining programming’s future in entering (or not entering) schools, and that educators need to make a conscientious effort to consider multiple metaphors without choosing just one.
Research limitations/implications
In terms of research limitations, the article does not purport to be an exhaustive analysis of all the metaphors that have been used to introduce CS to K-12 schools over the past 30 years. Rather it only identifies the leading metaphors from the literature, and in doing so, makes an important first step in examining the role of metaphor in the presentation of CS as a “new” course of study.
Practical implications
The article is intended for educators, researchers and administrators to gain a better understanding of what CS is (and could be) for K-12 schooling.
Social implications
The article is intended for educators, researchers and administrators to likewise understand how they, themselves, can present CS to students and families as a potential course of study.
Originality/value
There is currently considerable discussion about teaching CS in all US high schools, middle schools and even elementary schools. There is however little examination of past attempts to bring CS into K-12 schools and what these attempts may inform current advocacy.
[Full text freely available at http://www.informingscience.org/Publications/3521]
The introduction of computer programming in K-12 has become mainstream in the last years, as countries around the world are making coding part of their curriculum. Nevertheless, there is a lack of empirical studies that investigate how learning to program at an early age affects other school subjects. In this regard, this paper compares three quasi-experimental research designs conducted in three different schools (n=129 students from 2nd and 6th grade), in order to assess the impact of introducing programming with Scratch at different stages and in several subjects. While both 6th grade experimental groups working with coding activities showed a statistically significant improvement in terms of academic performance, this was not the case in the 2nd grade classroom. Notable disparity was also found regarding the subject in which the programming activities were included, as in social studies the effect size was double that in mathematics.
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 (rs = 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.
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. Available at: http://www.sciencedirect.com/science/article/pii/S0747563216306185