Computational thinking in collaborative programming discourse: an epistemic network analysis

To date, extensive work has been devoted to incorporating computational thinking in K‐12 education. Recognizing students' computational thinking stages in game‐based learning environments is essential to capture unproductive learning and provide appropriate scaffolding. However, few reliable and valid computational thinking measures have been developed, especially in games, where computational knowledge acquisition and computational skill construction are implicit. This study introduced an innovative approach to explore students' implicit computational thinking through various explicit factors in game‐based learning, with a specific focus on Zoombinis , a logical puzzle‐based game designed to enhance students' computational thinking skills. Our results showed that factors such as duration, accuracy, number of actions and puzzle difficulty were significantly related to students' computational thinking stages, while gender and grade level were not. Besides, findings indicated gameplay performance has the potential to reveal students' computational thinking stages and skills. Effective performance (shorter duration, fewer actions and higher accuracy) indicated practical problem‐solving strategies and systematic computational thinking stages (eg, Algorithm Design ). This work helps simplify the process of implicit computational thinking assessment in games by observing the explicit factors and gameplay performance. These insights will serve to enhance the application of gamification in K‐12 computational thinking education, offering a more efficient method to understanding and fostering students' computational thinking skills. Practitioner notes What is already known about this topic Game‐based learning is a pedagogical framework for developing computational thinking in K‐12 education. Computational thinking assessment in games faces difficulties because students' knowledge acquisition and skill construction are implicit. Qualitative methods have widely been used to measure students' computational thinking skills in game‐based learning environments. What this paper adds Categorize students' computational thinking experiences into distinct stages and analyse recurrent patterns employed at each stage through sequential analysis. This approach serves as inspiration for advancing the assessment of stage‐based implicit learning with machine learning methods. Gameplay performance and puzzle difficulty significantly relate to students' computational thinking skills. Researchers and instructors can assess students' implicit computational thinking by observing their real‐time gameplay actions. High‐performing students can develop practical problem‐solving strategies and exhibit systematic computational thinking stages, while low‐performing students may need appropriate interventions to enhance their computational thinking practices. Implications for practice and/or policy Introduce a practical method with the potential for generalization across various game‐based learning to better understand learning processes by analysing significant correlations between certain gameplay variables and implicit learning stages. Allow unproductive learning detection and timely intervention by modelling the reflection of gameplay variables in students' implicit learning processes, helping improve knowledge mastery and skill construction in games. Further investigations on the causal relationship between gameplay performance and implicit learning skills, with careful consideration of more performance factors, are expected.

Pair programming (PP) can help improve students’ computational thinking (CT), but the trajectory of CT skills and the differences between high-scoring and low-scoring students in PP are unknown and need further exploration. In this study, a total of 32 fifth graders worked on Scratch tasks in 16 pairs. The group discourse of three learning topics (comprising 9 projects) was collected. After the audio files were transcribed, 1,303 conversations were obtained. They were analyzed via Epistemic Network Analysis (ENA) Webkit, which can reveal the trajectory of students’ CT development via analyzing codes of discourse related to CT in PP. Three Scratch learning topics were assessed based on the Dr. Scratch platform to acquire the level of students’ CT and to determine the low- and high-scoring groups. Results indicated that CT concepts and CT practices were always closely related in PP and CT practices, and CT perspectives could be gradually and closely related after a long period of CT training. A significant difference between the two groups’ CT structures was found. The high-scoring group had more fragments of CT practice and connecting of CT perspectives, while the low-scoring group showed more fragments of CT concepts and expressing of CT perspectives. This research provides insights into cultivating primary school students’ CT using Scratch in the context of PP. The findings can provide suggestions for instructors to design instructional interventions to facilitate students’ CT skills via PP learning. Instructors can improve CT skills by guiding students to constantly ask questions, and specifying the role swap between driver and navigator in PP. Besides, instructors could give more consideration to the development of CT perspectives, and especially the ability to question.

Does text-based programming improve K-12 students’ CT skills? Evidence from a meta-analysis and synthesis of qualitative data in educational contexts

Educational robotics or unplugged coding activities in kindergartens?: Comparison of the effects on pre-school children's computational thinking and executive function skills

Programming has received extensive attention for the embodiment of computational thinking (CT) skills. However, the lack of in‐depth research on the characteristics of college students' CT skills in text‐based programming learning has resulted in the unknown distribution characteristics and evolution patterns of their CT skills, which cannot effectively constitute an effective tracking analysis of their CT skills, thus affecting the cultivation of creative thinking and problem‐solving skills for them. Therefore, the purpose of the paper is to explore the characteristics of college students' CT skills through text‐based programming work and discover the overall characteristics, individual differences and evolutionary patterns of their CT skills on the relation between text‐based programming and CT skills through data analysis. It was found that there are roughly five categories of CT difference and four major categories with nine subcategories of CT evolution among college students. The results showed that the Control and Data skills were the students' dominant skills. In contrast, Algorithm skills were relatively weak. Only about 1/3 of the students had the phenomenon of continuous skill improvement, and programming learning did not have a significant impact on the improvement of CT skills for some students. Finally, we propose several suggestions for CT skills development strategies in response to the students' characteristics in CT skills. The study can not only fill the gaps of the current study but also identify the evolutionary characteristics of students' CT skills, which can effectively intervene in college students' programming learning and help improve their CT skills.

Objective: This study aims to examine the influence of computational thinking skills, critical thinking skills, and collaborative thinking skills on the learning outcomes of robotics competencies of Electrical Engineering Education Students. Method: The sample in this study was 150 respondents, all of whom were students of the Electrical Engineering Education Study Program at Universitas Negeri Surabaya. The research data were obtained from filling out the questionnaire and analyzed quantitatively using the SEM PLS analysis technique with the help of the SmartPLS program. Results: This study shows that (1) Critical thinking skills have a positive effect on the educational robotics-based learning system, (2) computational thinking skills have a positive effect on the educational robotics-based learning system, (3) collaborative skills have a positive effect on the educational robotics-based learning system, (4) critical thinking skills have a positive effect on learning outcomes, (5) Computational Thinking Skills have a positive effect on learning outcomes, (6) Collaboration Skills have a positive effect on learning outcomes, (7) educational robotics-based learning systems have a positive effect on learning outcomes. Novelty: Educational robotics-based learning systems can be an ideal platform for developing computational, critical, and collaborative thinking skills among students. The use of robots as interactive and direct learning media through experiments and problem solving. This can help better understand technical concepts and increase confidence in facing complex challenges in the increasingly connected and rapidly changing real world.

The aim of this study is to examine the relationship between primary school teachers' 21st century skills self-efficacy levels and their computational thinking skills and STEM implementations self-efficacy levels. The sample of the study consists of 440 primary school teachers. While determining the sample of the research, convenience sampling technique, one of the purposeful sampling methods, was used. In order to collect data within the scope of the research, "Personal Information Form", "STEM Implementations Teacher Self-Efficacy Scale", "Computational Thinking Skill Scale" and "21st Century Skills Self-Efficacy Perception Scale" were applied. SPSS 22 package program was used to analyze the data obtained in the study. Since the data of the research showed normal distribution, Pearson correlation and multiple regression were analyzed. According to the results of Pearson correlation analysis conducted in this study, it was determined that there was a weak positive relationship between STEM implementations self-efficacy variable and 21st century skills self-efficacy computational thinking skills variables. In addition, it was determined that the relationship between the 21st century skills self-efficacy variable and the computational thinking skills variable was positive and moderate. According to the results of multiple regression, it was determined that primary school teachers' computational thinking and 21st century skills self-efficacy levels significantly predicted STEM implementations teacher self-efficacy level. As a result, it was determined that 21st century skills self-efficacy and computational thinking skills affect STEM implementation self-efficacy levels.

Effect of different mind mapping approaches on primary school students’ computational thinking skills during visual programming learning

The cultivation of computational thinking (CT) skills is a key issue in talent cultivation today. This study reported a meta-analysis of 22 empirical studies to determine the effectiveness of using educational games to improve students’ CT skills and the influence of various factors in instructional design on acquiring CT skills. The results showed that: (a) educational games can promote the improvement of students’ CT skills (Hedges’ g = 0.766, p = 0.000); (b) the overall effect is at the upper-middle level (95%CI [0.580, 0.951]); (c) The positive connection between educational games and CT skills is affected by sample size, grades level, game usage mode, and game tools. Controlling the class size to less than 50 students and the reasonable choice of game tools and usage modes are more conducive to promoting students’ CT skills. In sum, we suggested that the educational game teaching process should be rationally planned, and technology should be fully utilized to develop students’ CT skills. The above findings are of great significance to promote the improvement of students’ CT skills through educational games in the future.

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.

Two studies were conducted to examine the use of grounded embodied pedagogy, construction of Imaginary Worlds (Study 1), and context of instructional materials (Study 2) for developing learners' Computational Thinking (CT) Skills and Concept knowledge during the construction of digital artifacts using Scratch, a block-based programming language. Utilizing a conceptual framework for grounded embodied pedagogy called Instructional Embodiment, learners physically enacted (Direct Embodiment) and mentally simulated (Imagined Embodiment) the actions and events as presented within pre-defined Scripts. Instructional Embodiment utilizes action, perception, and environment to create a dynamic, interactive teaching & learning scenario that builds upon previous research in embodied teaching and learning. The two studies described herein examined the effects of Instructional Embodiment, Imaginary World Construction, and Context on the development of specific Computational Thinking Concepts and Skills. In particular, certain CT Concepts, such as Conditionals, Variables, Thread Synchronization, Collision Detection, & Events, and CT Skills, such as abstraction and pattern recognition, were identified and measured within the learners' individual digital artifacts. Presence and/or frequency of these Concepts and Skills were used to determine the extent of Computational Thinking development. In Study 1, fifty-six sixth- and seventh-grade students participated in a fifteen-session curricular program during the academic school day. This study examined the type of instruction and continuity of Imaginary World Construction on the development of certain CT Skills and Concepts used in a visual novel created in Scratch. Main effects were found for learners who physically embodied the pre-defined instructional materials: embodying the pre-defined Scripts led to the learners using significantly more ‘speech’ Blocks in their projects and more Absolute Positioning Blocks for ‘motion’ than those who did not physically embody the same Scripts. Significant main effects were also found for continuity of Imaginary World Construction: learners who were instructed to continue the premise of the first digital artifact (Instructional Artifact) implemented significantly more computational structures in their second digital artifact (Unique Artifact) than those who were instructed to create a Unique Artifact with a premise of their own design. In Study 2, seventy-eight sixth- and seventh-grade students participated in a seventeen-session curricular program during the academic school day. This study examined the type of instruction and context of instructional materials on the development of CT Skills and Concepts during the construction of a video game using Scratch. Similar to Study 1, findings suggest that physically embodying the actions presented within the pre-defined instructional materials leads to greater implementation of many of these same structures during individual artifact construction. The study also showed that as the pre-defined Scripts become more complex (e.g. single-threaded to multi-threaded), the effect of physical embodiment on the development of CT Skills and complex CT Concept structures becomes less pronounced. Findings from this study also suggest that Context has a significant effect on identifying & implementing the CT Skill pattern recognition: learning CT Concepts from an Unfamiliar Context had a significant positive effect on the implementation of both Broadcast/Receive couplings and Conditional Logic & Operator patterns. In sum, the findings suggest that the type of instruction, the continuity of the Imaginary World being constructed, and the context of the instructional materials all play a significant role in the learners' ability to develop certain Computational Thinking Skills and Concept knowledge. The findings also suggest that a physically embodied approach to teaching abstract concepts that is grounded in an unfamiliar context is the most effective way to integrate a grounded embodied approach to pedagogy within a formal instructional setting.

Improving 7th-graders’ computational thinking skills through unplugged programming activities: A study on the influence of multiple factors

Computational Thinking (CT) and digital literacy are skills students must possess to adapt and survive amidst the current technological advancements. One way to enhance students’ CT and digital literacy skills is through innovative learning models that align with the material being taught. Biotechnology is one of the subjects that students need to master in Phase E of the Merdeka Curriculum. This study aims to determine the effectiveness of the CPS-STEM learning model on students’ CT and digital literacy skills in biotechnology material. This research was conducted from April to May in the 2023/2024 academic year at three high schools in the Kayen, with a total population of 891 students. The sample used in this study was calculated using the Slovin formula, its 8 classes consisting of 2 control groups (72 students) and 2 experimental groups (217 students). This study is a quasi-experimental design with a pre-test and post-test group design. The STEM approach is integrated with CPS syntax outlined in the teaching module and assisted with student worksheets. CT skills were measured using post-test instruments, while digital literacy skills were measured using questionnaire. Data analysis was conducted to determine the effectiveness of the CPS-STEM learning model on CT skills, calculated using the N Gain test, while digital literacy skills were measured using a Likert scale. The results showed that the CPS-STEM was effective to improve CT skills in the medium category (0.40), whereas the direct instructional learning model was not effective in enhancing CT skills. This study also showed that the CPS-STEM learning model was effective in enhancing digital literacy skills with a percentage increase of 15.25%

The growing interest of educational researchers in computational thinking (CT) has led to an expanding literature on assessments of CT skills and attitudes. However, few studies have examined whether CT attitudes influence CT skills. The present study examines the relationship between CT attitudes and CT skills for preservice teachers (PSTs). The Callysto CT test (CCTt) for Teachers was administered to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n\,\,=$ </tex-math></inline-formula> 105 PSTs to measure their CT attitudes and skills. Structural equation modeling was used to examine the relationship of participants' CT and problem-solving skills with their attitudes toward CT, technology, coding, and data. Findings revealed that CT attitudes predicted CT skills and provided the first step in exploring the validity and reliability of the CCTt instrument.

Students with strong Computational Thinking (CT) skills possess a unique ability to analyze problems, devise efficient solutions, and navigate the intricacies of a rapidly evolving digital landscape. Given the conceptual overlapping between CT skills and engineering design competencies, engineering design processes provide students with a context for applying and developing CT skills. However, how to promote students to develop CT skills through pedagogical design in engineering education needs further research, especially in the formal higher education context. To address this gap, we constructed a model and designed a course that supports students in applying CT (i.e., decomposition, pattern recognition, abstraction, algorithm design, and troubleshooting/debugging) skills during multiple engineering design iterations. We collected 13 group design reports from 62 undergraduate students regarding their efforts in designing and solving mazes over three design iterations by applying CT skills. Using mixed methods, we examined what and how CT skills were demonstrated in the group reports, and what changes groups made between design iterations and why. We found that the participants demonstrated five CT skills with differing frequencies and needed more support in troubleshooting. When making changes between design iterations, groups mainly considered enabling users to apply CT skills, avoiding hard coding, adjusting the complexity of the mazes, considering design constraints to meet engineering design requirements, and enhancing user experience. The findings underscore the pressing need to equip students with the ability to navigate and resolve intricacies, particularly in troubleshooting, and groups' abilities to consider various elements when making engineering design decisions.