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Over the last decade, there has been an explosion of national interest in computer science (CS) education. In response to this, several organizations and initiatives have emerged in recent years to expand the CS pipeline. However, within these broad and laudable efforts, one important area has been largely overlooked—the instruction of CS to multilingual students, including the large and growing number of students designated as English learners in K-12 schools. These are one of the most underserved and understudied groups in CS education. In this article, we draw on existing research, as well as our own and others’ theoretical and empirical work to date, to put forth both a framework and curriculum for teaching CS to multilingual students.

Background: Computational thinking is derived from arguments that the underlying practices in computer science augment problem‐solving. Most studies investigated computational thinking development as a function of learners' factors, instructional strategies and learning environment. However, the influence of the wider community such as educational policies on computational thinking remains unclear. Objectives: This study examines the impact of basic and technology‐related educational policies on the development of computational thinking. Methods: Using supervised machine learning, the computational thinking achievements of 31,823 eighth graders across nine countries were analysed. Seven rule‐based and tree‐based classification models were generated and triangulated to determine how educational policies predicted students' computational thinking. Results and conclusions: Predictions show that students have a higher propensity to develop computational thinking skills when schools exercise full autonomy in governance and explicitly embed computational thinking in their curriculum. Plans to support students, teachers and schools with technology or introduce 1:1 computing have no discernible predicted influence on students' computational thinking achievement. Implications: Although predictions deduced from these attributes are not generalizable, traces of how educational policies affect computational thinking exist to articulate more fronts for future research on the influence of educational policies on computational thinking. Lay description: What is already known about this topicComputational thinking (CT) is a problem‐solving skill.Inquiries on CT focus on learners' factors such as age, gender and attitudes.Also, the choice of instructional strategies and learning environment influence CT development. What this paper addsArticulated how the wider community structures influence the development of CT.Educational policies affect the development of computational thinking. Implications for practicesStudents have a higher predicted propensity to develop CT when schools exercise full autonomy in governance and embed CT in the curriculum explicitly.Plans to support students, teachers and schools with technology or plans to introduce 1:1 computing have no discernible influence on students' CT. [ABSTRACT FROM AUTHOR]

Background: Computational thinking (CT) has emerged as a critical component of 21st‐century skills, and increasing effort was seen in exploring the development of CT skills in K–12 students. Despite cumulative research on exploring students' CT acquisition and its influencing factors, learners' development of the skill over time and the underlying mechanism that contributes to individual differences remain unclear. Objective: To bridge this gap, the present study aimed to explore the individual differences in CT acquisition among primary school students and how these differences were shaped over time. Specifically, variations in the development of CT across demographics, including gender and learning experience, were explored. Method: Three waves of data were collected from a sample of 322 primary school students (aged 7–12) across 18 months, with a 9‐month interval between adjacent waves. A time‐lagged model was leveraged for data analysis, and control variables were included in the model to strengthen statistical robustness. Results and Conclusion: The results indicate that male students and those who were more experienced in coding tended to have more positive attitudes toward coding. Additionally, coding interest was found to mediate the relationship between demographics and CT, demonstrating that male students and more experienced learners tended to be more interested in coding, which, in turn, contributed to the development of CT skills in later stages. Conclusion: The study provides valuable insights into the mechanisms underlying individual differences in CT development over time. The findings highlight the importance of nurturing coding interest among female students and promoting coding exposure for novice learners. Lay Description: What is already known about this topic: Individual differences in students' CT performance were broadly reported.Demographics were identified as important factors contributing to individual differences in CT acquisition.How these differences were shaped over time remains unclear. What this paper adds: The study investigated the underlying mechanisms of individual differences in long‐term CT development.Demographic differences in primary school students' CT development over time were explored.Results illustrate that females tended to have lower coding attitudes. Prior coding experience positively predicted coding attitudes.Coding interest mediated the relationship between demographics and CT, demonstrating that male students and more experienced learners tended to be more interested in coding, which, in turn, contributed to the development of CT skills in later stages. The implications of study findings for practitioners: The findings indicate the essential role interest and motivation played in supporting students' sustainable development in CT skills.The findings suggest the need for more attention to girls' motivation and learning interest in CT and coding instructions.The findings highlight the importance of introducing coding at early educational stages and promoting coding exposure for novice learners. [ABSTRACT FROM AUTHOR]

Computational thinking (CT) is a multidimensional term that encompasses a wide variety of problem-solving skills related to the field of computer science. Unfortunately, standardized, valid, and reliable methods to assess CT skills in preschool children are lacking, compromising the reliability of the results reported in CT interventions. To surpass this limitation, we validated in a sample of 700 preschool students (5–6 years old) the Beginners Computational Thinking test Short-Form (BCTt-SF), an unplugged 12-item instrument that measures three of the most common computational concepts assessed in preschool research: sequences, loops, and conditionals. The theoretical model underpinning the BCTt-SF was supported by dimensionality assessment, which suggested that preschool students can be distinguished in terms of four specific abilities (i.e., sequences, simple loops, nested loops, and conditionals) and that all of these abilities were related by a general factor. We modeled this hierarchical structure with a bi-factor model that presented excellent psychometric properties, from good statistical fit indices to adequate reliability of the general ability. To take full advantage of this model, we created an online application in the Shiny platform (https://computationalthinkingtests.shinyapps.io/SF-BCTt/) for the seamless scoring of examinees by any teacher or researcher who uses the BCTt-SF to assess CT skills in preschool children. Finally, we demonstrated how the BCTt-SF can be used to test the impact of educational interventions for improving CT skills in preschoolers. [ABSTRACT FROM AUTHOR]

In the digital age in which we live, one of the primary goals of education is to nurture individuals who are capable of thinking creatively, solving problems, and being innovative and productive. Computational thinking is an analytical process that requires defining problems and at the same time solving these problems by proceeding in creative ways. Based on this possible pattern of relationship between computational thinking and creativity, the aim of this study was to determine how two different versions of the computational thinking approach (plugged and unplugged) affect 6th-grade students' creative problem-solving skills (CPSS). Thus, two different teaching modules were designed on the circulatory system with a focus on plugged and unplugged computational thinking. A quasi-experimental design was used. Experiment group 1 utilized the plugged teaching module, experiment group 2 worked with the unplugged teaching module, and the control group in the Turkish middle school science curriculum's inquiry-based science activities. All three groups participated in 16 h of lessons over a 4-week period. We utilized the Creative Problem Solving Skills Inventory (CPSSI) for data collection. The results demonstrated that both the plugged and unplugged teaching modules were more successful at enhancing the CPSS than the inquiry-based science activities. Furthermore the unplugged teaching module was significantly more successful in developing CPSS compared to inquiry-based science activities. Hence, this empirical study demonstrated that both plugged and unplugged computational thinking approaches can enhance CPSS, but also reveals the greater effectiveness of unplugged approaches in fostering middle school students' CPSS. [ABSTRACT FROM AUTHOR]

Computational thinking (CT), an essential competency for comprehending and addressing intricate issues in the digital world, has been incorporated into curriculum planning as a goal for programming education. This study introduced flow design into programming curricula to investigate its impact on undergraduates 'CT skills during pair work. Two types of flow design approaches, construct-by-self flow design (CBS-FD) and construct-on-scaffold flow design (COS-FD), were proposed to determine which approach better enhances students' CT skills. Seventy-six first-year undergraduates participated, including thirty in the CBS group and thirty-six in the COS group. Evaluations made from the results and processes of programming tasks were employed to describe computational performance and computational practices, respectively. Data gathered from CT skill surveys were thoroughly analyzed to gain a deeper understanding of computational perspectives. Our findings highlighted that COS-FD significantly improved participants' computational performance compared with CBS-FD. The COS groups fostered an engaging, sharing atmosphere, while CBS groups spent more energy on negotiating the manipulation of flow design. Moreover, both COS-FD and CBS-FD proved beneficial in enhancing participants' computational perspectives, with the COS groups better improving their algorithm thinking. The study presents valuable perspectives on the design and implementation of collaborative programming activities within curriculum education. [ABSTRACT FROM AUTHOR]

Computational thinking (CT) competency is essential for K-12 students in the digital societies. Understanding the relationship between students' CT and relevant factors contributes to implementing and improving CT education. Most previous studies investigated the effect of demographic or attitudinal factors on CT performance; whereas few research explored the impact of mindset on CT, and how mindset potentially mediates the relationship between the affective and performance facets of CT. This study adapted a CT assessment instrument and validated it using item response theory (IRT) analysis and structural equation modeling (SEM) among N = 961 middle school students in eastern China. Further, two SEMs were fitted and compared to investigate the impact of programming self-efficacy (PSE) and growth mindset (GM) on CT performance. Results revealed that both programming self-efficacy and growth mindset positively predicted CT. Moreover, growth mindset positively mediated the relationship between PSE and CT. Findings suggest that mindset interventions beyond programming are also facilitative for improving CT. [ABSTRACT FROM AUTHOR]

In the contemporary era, Computational Thinking has emerged as a crucial skill for individuals to possess in order to thrive in the 21st century. In this context, there is a need to develop a methodology for cultivating these skills within a science and mathematics content education framework, particularly among pre-service teachers. This study aimed to investigate the impact of Educational Robotics on the development of Computational Thinking skills, with a particular focus on the role of gender, through a scientific and mathematical content teaching approach. A pre-experimental design with a quantitative approach was employed, and it was implemented with a total of 116 pre-service teachers, 38 males and 78 females. The results demonstrated a notable enhancement between the pre-test (8.11) and post-test (9.63) scores, emphasising specific concepts such as simple functions, while, and compound conditional. With respect to gender, statistically significant differences were identified prior to the intervention, but not following its implementation. The high level of Computational Thinking exhibited by both genders was comparable (53.85% in females and 55.26% in males) following the intervention. This indicates that the intervention is a promising approach for enhancing Computational Thinking proficiency, independent of gender and initial proficiency levels. The implementation of Educational Robotics in the teaching of science and mathematics enables the enhancement of Computational Thinking abilities among pre-service teachers, while reducing the observed gender disparity in this area of skill development. [ABSTRACT FROM AUTHOR]

The game-based learning approach to developing students' computational thinking (CT) current has received attention from researchers. However, the compatibility between games and instruction is often insufficient to accommodate the entertaining and educational nature of the curriculum entirely, and the benefits of game-based learning could be compromised. Therefore, this study proposed a role-playing-based micro-game strategy for developing students' CT in a Python programming course, and designed a quasi-experiment to verify the effectiveness of the role-playing-based micro-game strategy. A total of 133 eighth-grade students from schools in eastern China were randomly divided into experimental and control groups. The experimental group used a role-playing-based micro-game strategy, and the control group used a traditional instructional strategy. The results showed that the experimental group scored significantly higher than the control group on the CT test, especially in the dimensions of computational concepts and computational practices. The learning engagement of the experimental group was significantly higher than that of the control group, and the learning motivation of the experimental group was significantly improved before and after the experiment. In addition, qualitative analysis of the interview data indicated that micro-game strategy on role-playing could promote classroom learning and meet the needs of the course knowledge system. [ABSTRACT FROM AUTHOR]

As the impact of digital technologies pervades on our lives at all levels, it is important for students to develop their digital literacy. Computational thinking (CT) education is one pathway helping young students to thrive in the digital world. CT is a critical reasoning process whereby people formulate and solve problems using computers. CT education relies not only on schools and teachers, but also on parents. We reviewed 34 studies of the influence of parents on their children's CT education. We explore the following four aspects in CT education: (1) the contexts, (2) the effects regarding participation (affective, behavioral, and cognitive) outcomes in CT education, (3) the research designs, and (4) the mechanisms through which parents' participation influences children's CT education. Two theoretical frameworks, the tripartite model and parental involvement theory, were used to synthesize the 34 articles to analyze parents' affective, behavioral, and cognitive participation outcomes as well as the mechanisms of parental influence on CT education. We propose a conceptual framework of parental involvement in CT education. We further provide recommendations for supporting parents' involvement in children's CT education by suggesting appropriate parental mindsets and strategies to maximize the effectiveness of children's CT education. [ABSTRACT FROM AUTHOR]

The purpose of this study is to derive a correlation between the technological thinking disposition and the computational thinking ability of gifted students in Korea. The correlation between each element was analyzed by looking at the sub-elements of computational thinking according to the components of technological thinking disposition. The experiment was conducted from September 2019 to February 2021 with 217 students of I Gifted School in Incheon, South Korea. The collected data were analyzed with Pearson's correlation coefficient using the statistical program R using Google COLAB. A summary of the study results is as follows. First, regarding the correlation between technological thinking ability, among the 6 components of technological thinking disposition, technological creativity and expression disposition and technological manipulation disposition show the highest correlation at 0.851. This shows that students who have an excellent ability to implement algorithms with new ideas or express them in various other attempts when implementing programs for gifted students also tend to enjoy program coding or have a tendency to like coding. Second, concerning the correlation between the technological thinking disposition and the sub-factors of computational thinking, some elements showed negative correlations and some had almost no correlation index. Students with high technological curiosity, however, tended to show a 0.287 in the parallelism factor compared to other factors. This showed a generally high trend. It can be said that students who want to know the functions, uses, forms, and characteristics of functions while implementing programs tend to have a better ability to divide large tasks into smaller tasks and process them simultaneously compared with other sub-elements of computational thinking. Third, regarding the correlation between computational thinking skills, the correlation between data analysis and pattern recognition was the highest at 0.637. This indicates that students who have an excellent ability to analyze a given coding problem also can find rules in data, showing that students at gifted schools in Korea tend to enjoy problem-solving. [ABSTRACT FROM AUTHOR]

The present article explores the impact of educational robotics on fostering computational thinking and problem-solving skills in elementary school students through a problem-based learning approach. This study involved the creation of a framework which includes a robot and two eBooks designed for students and teachers. The eBooks serve as a guide to the construction and programming of a small Arduino-based robot. Through integration with gamification elements, the model features a narrative with three characters to boost a student's engagement and motivation. Through iteration of heuristic evaluations and practical tests, we refined the initial theoretical framework. An empirical study was conducted in two phases involving 350 students. The first empirical test involved a small group of 21 students, similar to end users, from five European schools. With a 100% completion rate for the tasks, 73.47% of these tasks were solved optimally. Later, we conducted a larger validation study which involved 329 students in a Portuguese school. This second phase of the study was conducted during the 2022–2023 and 2023–2024 school years with three study groups. The results led to a 91.13% success rate in problem-solving activities, and 56.99% of those students achieved optimal solutions. Advanced statistical techniques, including ANOVA, were applied to account for group differences and ensure the robustness of the findings. This study demonstrates that the proposed model which integrates educational robotics with problem-based learning effectively promotes computational thinking and problem-solving skills, which are essential for the 21st century. These findings support the inclusion of robotics into primary school curricula and provide a validated framework for educators. [ABSTRACT FROM AUTHOR]

Computational thinking (CT) is an essential mathematical skill for problem-solving and students’ future lives. It is integrated into the educational curricula of several countries, including Portugal. Therefore, pre-service teachers (PST) must possess didactic knowledge to effectively develop CT in students. The aim of this study encompassed three main objectives: translating and adapting the computational thinking scale into Portuguese (study 1), validating the scale (study 2), and assessing the perceived levels of CT competencies among PST in Portuguese university students while examining differences between undergraduate and master’s level PST (study 3). The sample consisted of study 1 with 43 participants and study 2 and study 3 with 382 participants. In study 1, temporal stability was assessed indicating strong stability. The internal consistency showed good homogeneity of the items. The exploratory factor analysis revealed consistency with the structure of the original scale. In conclusion, the Portuguese version of the CT scale demonstrates adequate psychometric properties, proving valid and reliable for assessing CT in university students. Additionally, significant differences were observed between undergraduate and master’s degree students, underscoring the importance of tailored training programs to meet the specific needs of undergraduate students. [ABSTRACT FROM AUTHOR]

This study aims to identify the nature and the extent of recent research studies on computational thinking in the Arab educational systems. The analyzed studies were gathered from English and Arabic educational sources. The selected publications were peer-reviewed journal articles over the past ten years that dealt with computational thinking in education in the Arab world. The selected studies were analyzed based on language, publication date, educational setting, educational discipline, site, primary purpose, research method, sample, and adopted definition of computational thinking. Twenty-eight research articles were selected for the investigation. The analysis revealed that the majority of the examined research studies were published in the Arabic language after the year 2020 in K-12 educational settings. The majority of the examined studies were conducted in programming and computer science in a few Arab countries. In addition, the majority of the examined studies focused on how to develop students’ computational thinking levels using various interventions. The majority of the studies employed a limited number of participants and used different forms of experimental research designs. The studies adopted different forms of the definition of computational thinking. Based on the findings, recommendations for future studies were presented. [ABSTRACT FROM AUTHOR]

Few studies of computational thinking (CT) integration in elementary curricula have yet focused on supporting early elementary educators with implementing and assessing their young students' application of these practices to content area work. This paper summarizes a collaborative research project that engaged researchers, K-second grade teachers, and professional development (PD) providers in implementing a hybrid PD model to answer the following research questions: (1) What kind of PD and guidance do teachers need to identify and support emergent computational thinking development in young students' language and work process? (2) What kind of PD and guidance do teachers need to identify emergent computational thinking development in young students' work products? This project employed a mixed-methods research design that included pre- and post-surveys and interviews with teachers to measure and understand how growth in teachers' confidence, knowledge, and self-efficacy with CT prepared them to identify and support these concepts with young learners. Additionally, analysis was able to identify the key formative assessment strategies these teachers employed to generate insight into students' understanding and application of CT during problem-solving. [ABSTRACT FROM AUTHOR]

Recent studies highlight the potential of modern board games (MBGs) to foster computational thinking (CT) skills in students. This research explored the impact of integrating MBGs into a primary education classroom through an embedded concurrent mixed-methods approach, with a pre-experimental design in its quantitative aspect and content analysis in its qualitative dimension, with 20 fourth-grade students from a school in Portugal. The students participated in 10 game sessions, each lasting 50 min, and their CT skills were assessed using Bebras tasks in both the pre-test and post-test phases. Statistical analysis, including the Shapiro–Wilk test for normality and paired sample t-tests, revealed significant improvements in key CT areas, particularly abstraction, algorithmic thinking, and decomposition. Descriptive statistics were also calculated, and content analysis using Nvivo software was conducted on field notes, corroborating the quantitative data. The results suggest that MBGs can serve as a valuable educational tool for developing CT skills in young learners. This study not only highlights the effectiveness of MBGs but also emphasises the need for further research using more robust experimental designs to enhance CT development in educational settings. [ABSTRACT FROM AUTHOR]

This article contributes new knowledge on collaboration within and between Change Laboratory sessions and how it offers the potential to support the zone of proximal development and the expansive learning of participants. The Change Laboratory is a formative intervention method that helps participants transform their practices. This qualitative study examines how six educators participating in a Change Laboratory intervention dealt with problems that arise when implementing digital artifacts in teaching mathematics. We collected data through participant observation between sessions and video recordings during sessions. We conducted the data analysis abductively, using the seven expansive learning actions as an analytical framework. The findings highlight how collaboration between the researcher and the participants, both during and between Change Laboratory sessions, helped support the participants' zone of proximal development and expansive learning. This close collaboration enabled the educators to collectively reflect on and transform their teaching practices, specifically by incorporating digital artifacts into their educational routines. The study provides important insights into how digital artifacts can be successfully implemented in practice using Change Laboratories, emphasizing the importance of supporting educators in their zone of proximal development. Using a theoretical perspective grounded in cultural-historical activity theory, the study contributes to understanding how change occurs in the educational field. [ABSTRACT FROM AUTHOR]

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In this conceptual study, we explore the incorporation of computational thinking (CT) within integrated Science, Technology, Engineering, and Mathematics (STEM) education, aiming to enhance the Technological Pedagogical Content Knowledge (TPACK) framework for teacher professional development. Despite the fundamental role of mathematics in K‐16 and engineering education, its theoretical and practical dimensions in a transdisciplinary STEM context and its interlinks with CT remain underexplored. This gap extends to the professional development of teachers in research‐oriented STEM environments, which presents significant challenges. The study aims to address these issues by repositioning cognitive‐adaptive competencies such as CT and design thinking (DT) as a crucial enabler for STEM teacher professional competency, advocating for a move beyond normative approaches. We comprehensively analyze the integration efforts of CT in STEM, which often rely on declarative definitions without substantive practical implications. The study poses questions on (1) how CT can be effectively integrated into STEM, (2) the characteristics of the normative‐adaptive model for teacher education, and (3) the development of a conceptual educational framework focused on mathematical modeling, simulation design, and student engagement in research. Drawing on innovative educational practices, we scrutinize the integration of CT and DT through examples from mathematics, emphasizing the importance of developing computational models and algorithms. Ultimately, we propose a competency‐centered normative‐adaptive‐context aware model of STEM integration (NACAMS)‐TPACK model that enhances the classical TPACK framework by interlinking computational, design, and general pedagogical competencies. This study is particularly relevant for educators, policymakers, and researchers involved in K‐16 STEM and engineering education. [ABSTRACT FROM AUTHOR]

Computer vision education is increasingly important in modern technology curricula; yet, it often lacks a systematic approach integrating both theoretical concepts and practical applications. This study proposes a staged framework for computer vision education designed to progressively build learners' competencies across four levels. This study proposes a four-staged framework for computer vision education, progressively introducing concepts from basic image recognition to advanced video analysis. Validity assessments were conducted twice with 25 experts in the field of AI education and curricula. The results indicated high validity of the staged framework. Additionally, a pilot program, applying computer vision to acid–base titration activities, was implemented with 40 upper secondary school students to evaluate the effectiveness of the staged framework. The pilot program showed significant improvements in students' understanding and interest in both computer vision and scientific inquiry. This research contributes to the AI educational field by offering a structured, adaptable approach to computer vision education, integrating AI, data science, and computational thinking. It provides educators with a structured guide for implementing progressive, hands-on learning experiences in computer vision, while also highlighting areas for future research and improvement in educational methodologies. [ABSTRACT FROM AUTHOR]

Life in the twenty-first century requires education to integrate knowledge, attitudes, skills, and mastery of information and communication technology (ICT). An example of the skills needed in the twenty-first century is computational thinking. This study aims to develop computational thinking-skill tasks on numbers and arithmetic based on the Riau Malay culture. A research and development (R&D) method was employed with a 4-D model, which consists of four stages, namely definition, design, development, and dissemination. Furthermore, the tasks developed were validated by two mathematics education experts and tested to 33 fifth-grade students from a public school in Pekanbaru, Indonesia. The Rasch model was used to analyse the data, and the result showed that 23 valid tasks were obtained from 24 items. This implies that the tasks of assessing the computational thinking skills in the context of Riau Malay culture satisfy the valid and reliable criteria and are useful for further study. [ABSTRACT FROM AUTHOR]

Novice nurses often report a disconnect between textbook knowledge and realworld practice which damages their confidence in providing clinical care to patients. Nursing students indeed encounter numerous challenges in clinical environments such as inadequate resources and a gap between learning theory and clinical practice. To close the academic-practice gap and to ensure nursing students are equipped with sufficient clinical skills to perform tasks in their future career, virtual simulation can be used for students to experience clinical cases. In addition to the virtual simulation environment itself, appropriate pedagogies are also needed for them to explore simulated clinical tasks and apply what they have learned. Problem-based learning (PBL) is one pedagogy well-suited to this purpose. To increase the effectiveness of PBL in fostering student nurses' self-efficacy and problem-solving skills, this study proposes integrating computational thinking (CT) into PBL in concert with the virtual dissection table, as CT is viewed as a problem-solving skill. Informed by CT, nursing students organize and synthesize the acquired knowledge, applying it to solve clinical problems and provide nursing care in clinical practice more effectively with the skills developed. The results reveal no significant differences in learning achievement, but both problem solving skills and confidence increase for students empowered by CT concepts. [ABSTRACT FROM AUTHOR]

There has been a global consensus to develop computational thinking (CT) in primary education, but the biggest obstacle to promoting CT is teachers' lack of sufficient CT. This study explored the effects of micro: bit educational robotics (MER) programming activities on primary teachers' CT and programming attitudes (PA) while considering the teachers' gender effects. We implemented a single-group pre-test and post-test experiment with 56 primary teachers in China. We also measured teachers' CT and PA levels before and after the MER activities intervention. The results showed that MER activities significantly enhanced teachers' CT and PA and had different effects on each dimension of their CT and PA. The analysis of variance by gender showed that male teachers had significantly higher overall CT and PA scores than female teachers. However, female teachers performed better on collaborative skills in CT, indicating that female teachers also have the potential to develop CT. In addition, we found the mediating effects of PA, which means that MER activities affect CT through PA. Furthermore, PA predicted CT positively, suggesting that PA could be a key factor in enhancing CT. This study clarified the mechanism of gender and PA influence on CT during the MER activities intervention, which provides references for future researchers to conduct teacher training. [ABSTRACT FROM AUTHOR]

This study explores the influence of schools' general characteristics, and their information and communication technology (ICT) capabilities on students' computational thinking. The computational thinking achievements of 31,823 students who participated in a large-scale comparative study in 1412 schools and across nine countries/regions were analyzed using supervised machine learning. Five classification rules were triangulated to determine how 22 schools' general characteristics and their ICT capabilities predicted students' computational thinking achievements. Data analysis showed no predictive relationship between schools' ICT capabilities and computational thinking. However, some classification rules predicted higher computational thinking achievement for students from affluent schools. The discussion amplifies the need for proper incorporation of ICT in schools with recommendations for more research on the nuanced relationship between schools' characteristics and computational thinking development. [ABSTRACT FROM AUTHOR]

Computational thinking (CT), as one of the key skills in the twenty-first century, has been integrated into educational programming as an important learning goal. This study aims to explore CT processes involved in pair programming with the support of visual flow design. Thirty freshmen participated, working in pairs to solve two programming problems. Their discourses were recorded, transcribed, and coded based on a CT framework encompassing cognitive, practical, and social perspectives. Both quantitative and qualitative methods were applied to analyze the data. In particular, Epistemic Network Analysis (ENA) was applied to explore the patterns of their CT processes. The findings revealed that social perspectives emerged the most frequently in all pairs' discourses. The high-level groups (HLGs) focused more on practical and social perspectives whereas the low-level groups (LLGs) emphasized more on cognitive perspectives. The ENA networks revealed that social perspectives mostly centered around cognitive perspectives for all pairs with CT process patterns in HLGs crossing the three perspectives more frequently. In addition, HLGs exhibited a more complicated and developmental trend in solving the two problems, while LLGs displayed a relatively similar CT pattern. The current study provides insights into the design and implementation of collaborative learning activities in educational programming. [ABSTRACT FROM AUTHOR]

Computational Thinking, a capacity based on the principles of computing, has been highlighted in the specialized literature as an essential skill for the 21st century, bringing significant benefits to the problem-solving process. In this way, norms for the integration of Computational Thinking in education have emerged in the educational curricula of several countries. For this integration to be successful, it is essential that the training given to pre-service teachers enables them to develop well-planned and structured interventions to promote the development of Computational Thinking. This article presents a systematic review of the literature that aims to investigate how the development of Computational Thinking has been integrated into teacher training. Eleven articles that corresponded to the selected research criteria were found, and the characteristics of their studies are analysed and presented in this article. The article concludes that it is necessary to invest in pre-service teacher training, highlighting the need for long-term and more comprehensive training covering not only the theoretical component but also the practical component, as well as reflection on practice. [ABSTRACT FROM AUTHOR]

The present study illustrates digital storytelling (DS) as an open-ended learning environment, which is one of the ways of preparing pre-service teachers (PST) to practice computational thinking (CT) in their future teaching. An 8-week teacher training program was organized and presented. The study aims to investigate the program's impact on the PST's CT skills, CT-integrated DS design skills, and their perspectives. A study group of fifty-two second-year PSTs took part in the Instructional Technologies course. An embedded mixed-method design was used. The CT scale was used as a pre-test and post-test to examine the development of the PST's CT skills for quantitative data collection. The qualitative data comprise the CT-integrated DS projects developed by the PST during the training and the reflection reports they wrote at the end of the training. The paired samples t-test was used in the analysis of quantitative data. The DS projects were evaluated using the rubrics with the story/storyboard, DS, and CT skills dimensions. Reflection reports were analyzed using thematic analysis. The findings revealed a significant improvement in the PST's CT skills after the training program. The qualitative findings show the PST's perspectives on CT definitions, the perceived benefits of CT and DS, and the use of DS to promote CT. The qualitative findings also present evidence for the CT-integrated DS design skills of the PST. Therefore, the study presents early findings showing that CT components could be integrated with DS and used in teacher education effectively without any pressure to use programming tools. The study also shows how DS is gradually integrated with the CT components as a suggestion for future studies. [ABSTRACT FROM AUTHOR]

This study investigated the impact of problematization-oriented scaffolding and structuring-oriented scaffolding, incorporated within instructional videos, on students' computational thinking and their performance in programming education. We recruited 86 participants from three senior classes at a high school. Each of the three classes was assigned to one of the experimental conditions: the problematization-oriented scaffolding group, the structuring-oriented scaffolding group, and the control group, which received no scaffolding. Pre- and post-tests were conducted to assess students' computational thinking and programming performance during a three-week period. We observed significant improvements in the computational thinking skills of the problematization-oriented scaffolding group, particularly in the algorithmic thinking and cooperativity subdimensions, when compared to the control group. Structuring-oriented scaffoldings in videos also helped enhance students' computational thinking, especially in the algorithmic thinking subdimension. In contrast, students in the control group primarily improved their problem-solving skills, although the difference across the three groups was not significant. Furthermore, this study revealed that the use of learning scaffolds, whether problematization-oriented or structured, significantly contributes to students' learning achievements in comparison to the control group. These findings emphasize the importance of selecting the appropriate scaffolding approach to enhance specific dimensions of computational thinking. [ABSTRACT FROM AUTHOR]

Computational thinking (CT) is valued as a thinking process that is required to adapt to the development of curriculum in primary education. In the context of modern information technology, English as a language subject emphasizes the necessity for changes in both learning and teaching modes. However, there is a lack of up-to-date synthesis research and a comprehensive overview surrounding CT integrated into English language curriculum learning and teaching in primary education. To address this research gap, this study conducted a systematic literature review on CT in the primary English curriculum, based on papers published from 2011 to 2021. The purpose of this review is to systematically examine and present empirical evidence on how CT can be integrated into the teaching and learning of the primary English language curriculum in educational contexts. The review was conducted based on the PRISMA 2020 statement and presents a synthesis of 32 articles. The CT-TPACK model was adopted as a lens and framework to analyze these articles. The results indicate that the relationship among CT, content knowledge of English language curriculum, pedagogy and learning knowledge, technology and resources is highlighted. Research on the integration of CT into English courses using unplugged activities is still insufficient. The research about how teachers and students use CT to support content knowledge of the English language curriculum in various educational contexts is still in its infancy. [ABSTRACT FROM AUTHOR]

Although computational thinking (CT) is becoming increasingly prevalent in K-12 education, many teachers find it challenging to integrate it with their classroom learning. In this systematic review, we have reviewed empirical evidence on teachers' computational-thinking-focused professional development (PD). The findings depict the landscape of what has been done in terms of how PDs have been designed, how CT has been conceptualized, how learning outcomes have been assessed, and how teachers have been supported in integrating CT into their teaching practices. We have further summarized the lessons learned from the PDs and discussed the gaps as the field moves forward. These findings shed light on supporting teachers as the first step to creating an effective model for CT learning and development in K-12 education. [ABSTRACT FROM AUTHOR]

Background: The pedagogy of computational thinking has gained extensive traction across numerous nations globally, with a particular emphasis on nurturing computational thinking in the formative years of early childhood. Nevertheless, the efficacy of diverse instructional approaches in the domain of programming education, with regards to fostering the advancement of computational thinking abilities in young children, remains a subject of ongoing debate. Objectives: The primary aim of this research is to evaluate the efficacy of programming education in fostering computational thinking skills in young children. The central focus revolves around a meticulous exploration of the influence exerted by diverse modalities of programming education on the cultivation of computational thinking abilities in early learners. Methods: A total of 32 empirical studies were incorporated into the analysis. Out of these, 77 effect sizes were deemed to meet the predefined inclusion criteria for the present study. The statistical analysis was executed utilizing Stata version 17.0 software. Results and Conclusions: The acquisition of programming skills can enhance the advancement of computational thinking in young children (Hedges's g = 0.49, 95% confidence interval [0.40, 0.58]), thereby yielding a moderate effect. When considering the triad of programming education modalities, it becomes evident that graphical programming surpasses both tangible programming and unplugged programming in terms of its efficacy in fostering the growth of computational thinking in young learners. Implications: The foregoing contributes significantly to the systematic cultivation and augmentation of computational thinking skills in young children. It establishes a foundational framework for early childhood educators and instructional tool designers to effectively and purposefully impart programming knowledge to children. Lay Description: What is already known about this topic?: Computational thinking represents a fundamental skill that should be universally acquired, with the cultivation of this cognitive capacity during early childhood deemed an indispensable prerequisite for one's future endeavours.The influence of programming education on the development of computational thinking in young children is a multifaceted outcome, arising from an intricate interplay of various factors.The practical implementation of computational thinking within preschool education remains at an exploratory stage, beset by numerous challenges. What this paper adds?: Programming education moderately fosters the advancement of computational thinking in young children.Different types of programming education have varying effects on the computational thinking of young children.Graphical programming emerges as a superior modality for fostering computational thinking in young children. Implications for practice and/or policy: The strategic utilization of programming education modalities tailored to the unique learning styles and developmental characteristics of children emerges as a strategically advantageous approach for nurturing the advancement of their computational thinking abilities.Programming education for preschoolers is inherently intertwined with the indispensable support and expert guidance provided by educators and other professionals. [ABSTRACT FROM AUTHOR]

The construction industry is a hazardous environment with a high prevalence of work-related musculoskeletal disorders, compromising workers' physical and emotional well-being. Construction practitioners can leverage sensor-based safety assessment systems to track and identify workers' awkward postures, preventing potential injuries. Educational sensor data practices with block programming can enable higher-order learning of the required computational skills for sensor data analytics. However, limited research exists on the factors influencing the acquisition of these skills in training graduating construction students. Through a sensor-based risk assessment intervention, this study explores how individual characteristics (demographics) influence students' learning. Assessments included perceived self-efficacy of data analytics skills, analytical performance scores, and user acceptance of the educational platform. The results suggest: (a) women show higher self-efficacy gains, while Hispanic/Latino students and those without construction or programming experience report lesser gains, (b) students reach similar performance levels, but those with construction experience excel in reflection reports, and (c) students without construction experience perceive higher utility and lower risks, while Hispanic/Latino students show greater future intent to use the pedagogical tool. The findings contribute to Aptitude-Treatment Interaction Theory by highlighting how individual differences can impact the efficacy of pedagogical interventions in acquiring technical skills in construction education. [ABSTRACT FROM AUTHOR]

Statistics teaching at the high school level needs modernizing to include digital sources of data that students interact with every day. Algorithmic modeling approaches are recommended, as they can support the teaching of data science and computational thinking. Research is needed about the design of tasks that support high school statistics teachers to learn new statistical and computational approaches such as digital image analysis and classification models. Using our design framework, the construction of a task is described that introduces classification modeling using grayscale digital images. The task was implemented within a teaching experiment involving six high school statistics teachers. Our findings from this exploratory study indicated that the task design seemed to support statistical and computational thinking practices related to classification modeling and digital image data. [ABSTRACT FROM AUTHOR]

While research has shown that students' epistemic beliefs can be a strong predictor of their academic performance, cognitive abilities, or self-efficacy, studies of this topic in computer education are rare. The purpose of this study was twofold. First, it aimed to validate a newly developed questionnaire for measuring students' epistemic beliefs about computer programming at middle school level. Second, the study aimed to understand how students' epistemic beliefs predict their computational thinking disposition and computer programming self-efficacy. A total of 406 middle school students completed a survey consisting of three research instruments: the Computer Programming Epistemic Belief Inventory (CPEBI), the Computational Thinking Scale (CTS), and the Computer Programming Self-Efficacy Scale (CPSES). The results indicated that the epistemic belief of "uncertainty" was a significant and positive predictor of the "abstraction" and "generalization" dimensions of computational thinking dispositions. In addition, the belief of "complexity" was an antecedent to three dimensions of computational thinking, namely, "algorithmic thinking," "evaluation," and "generalization." Only the "evaluation" dimension of CT disposition had significant and positive relationships with "programming self-efficacy." The roles of "uncertainty" and "complexity" of computer programming epistemic beliefs are discussed. Implications and suggestions for future computer programming education, especially for young students, are provided. [ABSTRACT FROM AUTHOR]

Three years after Japan integrated programming into all elementary school subjects, questions remain on how policy is being put into practice in arts education. This article examines the current state of programming – activities addressing a local version of computational thinking – in music, with a focus on Japan's pending challenges. First, an analysis of 23 activity reports sheds light on the main features of implementation efforts conducted by elementary school teachers from all over the country. Notably, compliance with official guidelines seems to have been prioritized over subject-specific contents, and, in some cases, the mere use of digital technologies in the classroom appears to be more relevant than programming and music-making goals. Following that, two key stakeholders – Japanese professionals engaged in planning and implementing programming in music in elementary schools – provide insights on its present state and future prospects through an open questionnaire. Their often-contrasting answers include perspectives on learning goals, teachers' skills and assessment, as well as their expectations and concerns. A number of unresolved issues and tensions persist regarding how subject contents and programming should be balanced. Given this situation, final remarks address how music-centered, postdigital views of programming may inform future initiatives in the intersection of computing science and music education. [ABSTRACT FROM AUTHOR]

Previous research has not adequately explored students' behavioral processes when addressing computational thinking (CT) problems of varying difficulty, limiting insights into students' detailed CT development characteristics. This study seeks to fill this gap by employing gamified CT items across multiple difficulty levels to calculate comprehensive behavioral sequence quality indicators. And then, through latent profile analysis, we identified four distinct latent classes of behavioral process. We then examined the in-game performance differences among these classes, uncovering each class's unique attributes. Class 1 students consistently demonstrated high-quality, efficient behavioral sequences regardless of item difficulty. In contrast, class 2 students applied significant cognitive effort and trial-and-error strategies, achieving acceptable scores despite low behavioral sequence quality. Class 3 students excelled in simpler items but faltered with more complex ones. Class 4 students displayed low motivation for challenging items, often guessing answers quickly. Additionally, we investigated the predictive value of students' performance in gamified items and their behavioral process classes for their external CT test scores. The study finally elaborated on the theoretical implications for researchers and the practical suggestions for teachers in CT cultivation. [ABSTRACT FROM AUTHOR]