Teaching Of Computational Thinking Research Articles

Engagement predicts computational thinking skills in unplugged activity: Analysis of gender differences

Engagement is critical to computational thinking and programming education. However, as multi-dimensional variables, when analyzing how different aspects of engagement in computational thinking tasks influence skills development, it becomes crucial to discern precisely which engagement components intersect with the progression of computational thinking skills. This discernment is pivotal because engagement can vary based on the task nature, the context, and the individual's preferences. Therefore, the purpose of this study is to explore the gender differences in engagement and computational thinking skills and the predictive relationships among these sub-dimensions for boys and girls in an unplugged environment. In this study, a quasi-experiment for 90 sixth-grade students from a north Chinese primary school was performed. By partial least squares–structural equation modeling, students’ models of computational thinking skills and engagement were analyzed, and comparisons of boys and girls were made by analysis of covariance statistics. Results indicated that compared with boys, girls reported higher computational thinking performance and more engagement in unplugged contexts. Furthermore, girls’ computational thinking skills were only predicted by their cognitive engagement, whereas boys’ computational thinking skills were predicted by their behavioral, emotional, and cognitive engagement. Teachers can adopt these findings to design computational thinking teaching interventions that combine the advantages of unplugged activity and focus on the engagement of boys and girls.

Computational Thinking Research in Mathematics Learning in the Last Decade: A Bibliometric Review

This study aims to map the landscape of the importance of previous research on computational thinking (CT) in mathematics learning over the last decade. This research is a literature review research, there are 113 publications collected from the Scopus database which are then analyzed using the bibliometric analysis method assisted by the Vosviewer application. The data taken from the Scopus database was refined so that it became 113 publications. The results of the study show that publications are spread across various continents, including America, Asia, Africa, and Europe. The United States and the United Kingdom are the most influential countries and have high cooperation with other countries in this field. The main conclusion from this study is that computational thinking has an important role in learning mathematics and STEM. The integration of computational thinking in the mathematics curriculum can improve students' understanding of mathematics and help them face the challenges of the digital age. In addition, the development of effective training methods for mathematics teachers as well as the assessment of good computational thinking learning tools and platforms can help improve the effectiveness of computational thinking teaching in mathematics contexts. These innovations will help better understand how computational thinking can be effectively integrated in mathematics learning and prepare students for a future filled with digital technologies.

An Evaluation of the Effect of Activity-Based Computational Thinking Education on Teachers: A Case Study

This study aimed to conduct an in-depth evaluation of the activity-based computational thinking teaching practices performed to improve computational thinking and teaching skills of the basic education teachers. Based on the aim of the study, the case study design, one of the qualitative research methods, was selected. As a result of the collaborative work of five experts, a 20-hour education program built on two core competencies, four sub-competencies and eight thinking skills was implemented. The participants were 40 teachers, 20 of whom were classroom teachers and 20 of whom were pre-school teachers. Data were collected from three different sources using five data collection tools in order to conduct an in-depth analysis of the practices. Quantitative and qualitative data collection tools were used in a combined fashion in the research. The data were analyzed through content analysis and non-parametric analyses. Our findings revealed that thanks to the teaching practices performed, classroom teachers had significantly higher problem solving, diverse thinking, algorithmic thinking, and computational thinking total scores, while preschool teachers achieved significantly higher total scores in algorithmic thinking skills and computational thinking. It was observed that the participants defined computational thinking on the basis of 18 different thinking skills. The explanations of the participants about the functions of computational thinking skills were grouped under seven categories. When the principles that should be considered in the teaching of computational thinking skills were examined, it was seen that the need for utilizing scaffolds was stated the most.

Review on the teaching of programming and computational thinking in the world

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.

Developing College students’ computational thinking multidimensional test based on Life Story situations

At present, research on computational thinking in universities is gaining interest, and more attention is being paid to the cultivation and teaching of computational thinking. However, there is a lack of computational thinking assessment tools for college students, which makes it difficult to understand the current status and development of their computational thinking. In this study, computational thinking is regarded as the ability to solve practical problems. By analyzing the relevant literature, we identified five dimensions of computational thinking – decomposition, generalization, abstraction, algorithm and evaluation – and described their operational definitions. Referring to the Bebras and the problem situations in Google computational thinking education, we set up a life-based situation that college students are familiar with. Based on the life story situation, we developed a multidimensional assessment for college students’ computational thinking. This assessment tool contains 14 items, all of which are multiple-choice questions, and the structure and quality of the tool are verified by multidimensional item response theory. The results show that the assessment tool has good internal validity and can discriminate different disciplines of college students. The college students’ computational thinking test developed in this study can be used as an effective tool to assess college students’ computational thinking.

The effects of scaffolded programming scripts on pre-service teachers’ computational thinking: Developing algorithmic thinking through programming robots

Workers in the areas of science, technology, engineering and mathematics play a significant role in the sustained growth and stability of the global economy, and, thus constitute a critical component in helping all countries worldwide to prosper. In this context, computational thinking constitutes an important skill to have as it enables workers to develop creative solutions to complex problems. Nonetheless, across all economies worldwide, there is a need to have more workers who are able to think through problems, challenges, and solutions in computational terms. It is thus of utmost importance to integrate the teaching of computational thinking in K-12 education in order to reduce the skills gap between education and the workplace. A pertinent and crucial question that arises is whether teachers have the knowledge and skills to teach students how to think computationally. Existing research shows that teacher education departments do not currently have the knowledge to promote computational thinking in their programs. The present study focuses on two aspects of computational thinking, such as, algorithmic thinking and debugging skills with the use of scaffolded programming scripts in an educational technology undergraduate course. The results show statistically significant learning gains in pre-service teachers’ algorithmic thinking and debugging skills in the context of robotic programming activities with LEGO WeDo. Limitations and future research directions are discussed.

Improving early childhood pre-service teachers’ computational thinking teaching self-efficacy beliefs in a STEM course

ABSTRACT Background In order for computational thinking (CT) to be successfully implemented in educational environments, teachers’ CT teaching self-efficacy beliefs should be developed. The existing research on this topic is generally focused on training in-service teachers on CT to develop their self-efficacy. Conversely, the current study aims to contribute to the development of early childhood pre-service teachers’ CT teaching self-efficacy beliefs through CT-integrated STEM education. Purpose In the current study, the effect of CT-integrated STEM education on CT teaching self-efficacy beliefs of early childhood pre-service teachers was explored. Sample The study group was composed of 68 second-year early childhood pre-service teachers. All were attending a state university in the city of İstanbul during the 2020–2021 academic year. Design and Methods The study employed a quasi-experimental design, i.e. the control group was given only STEM education, while the experimental group was given CT-integrated STEM education. The data collection tool used in the current study was ‘the scale of self-efficacy beliefs towards teaching computational thinking’. For analysis, an independent samples t-test and a paired samples t-test were used. Results The findings have revealed that there is a significant difference in the post-test scores on the ‘scale of self-efficacy beliefs towards CT teaching’ in favor of the experimental group. The effect size calculated for the difference between the mean pre-test and post-test scores of the experimental group students was found to be large. These results show that CT-integrated STEM education contributed to the development of the pre-service teachers’ CT teaching self-efficacy beliefs. Conclusion The current study contributes to the literature by showing that CT-integrated STEM education fosters pre-service teachers’ professional development and their self-efficacy beliefs about CT teaching.

Unplugged computational thinking at K-6 education: evidence from a multiple-case study in Spain

ABSTRACT This paper examines the implementation of unplugged tasks across different school settings developing computational thinking skills and concepts at upper primary school children in Spain without programming and without using electronic devices. The study is based on qualitative case study design. Across the three case studies/schools – Waldorf-Steiner, conventional and innovative – several themes and key tasks were emerged for unplugged computational thinking development. The evidence stems from observation field notes and interview transcripts with 152 participants. We collected 94 lessons in total, and we analyzed the data based on a predefined coding scheme and thematic content analysis. We conclude that the detected unplugged tasks demonstrate a great potential to develop computational thinking skills and concepts, even though the teachers are not fully aware of their development. The study highlights the need for teacher professional development on computational thinking teaching and learning. Also, we stress the need for computational thinking skills, concepts, and tasks integration into curriculum explicitly. Given the paucity of research on unplugged methods and computational thinking development in primary education, this study is promising to uncover some prominent issues for further examination and future research agenda.

A Novel Three-Way Decision Model for Improving Computational Thinking Based on Grey Correlation Analysis

Computational thinking (CT) is an approach that applies the fundamental concepts of computer science to solve problems, design systems, and understand human behavior, which can help students develop lifetime learning and generate new topics. It has been the elements of competency expected of the next generation of talents. However, the current research on computational thinking evaluation is still at a relatively weak stage. The existing related evaluation research is still limited to traditional curriculum evaluation methods. Therefore, the training effect of computational thinking cannot be well quantified, and the characteristics of students cannot be further explored. In this work, we propose a three-way decision model for improving computation thinking. We first developed a system of evaluation metrics, including five specific primary indicators and several secondary indicators. Next, the weight of each indicator was determined by applying an expert similarity measure, consequently getting the best metric sequence. We employ a grey correlation analysis to calculate the distance of each test result from this optimal sequence. Then, we trisect the set of testers based on the distance to build three regions of high score sequences, medium score sequences, and low score sequences inspired by the three-way decision. We can then exploit these rules on target students in the relatively low regions to improve their computational thinking. An example analysis illustrates the effectiveness and applicability of the method. This article provides a solid theoretical basis for improving students’ computational thinking ability. Teaching administrators can conveniently formulate computational thinking teaching strategies, and timely warning and intervention for students with poor computational thinking ability can effectively improve students’ computational thinking ability. The corresponding training measures are given to students of different ability levels to achieve differentiated and personalized training.

Computational thinking for teachers: Development of a localised E-learning system

Malaysia has introduced computational thinking skills as part of a curriculum integration update to meet the global trends in 21st-century education, focusing on empowering digital literacy. Nevertheless, a preliminary investigation revealed an apparent lack of understanding of computational thinking skills in general among teachers. The study explores the feasibility of developing a localized E-learning system to train computational thinking skills among teachers. An E-learning system, termed as myCTGWBL, was developed on the basis of a newly proposed conceptual framework to present computational thinking teaching–learning repertoire to the teachers. The hypothesis is that myCTGWBL would develop teachers' computational thinking and its position in teaching–learning understanding. myCTGWBL relevance was tested through DeLone and McLean's information system and Urbach's collaboration quality construct. To determine the success factors, partial least squares structural equation modeling was used. A total of 369 teachers participated in a two-stage survey. Participants' understanding of computational thinking and perceptions were recorded at the pre- and post-intervention phases. Open-ended questions of the surveys were analyzed using a simple text analysis technique. The closed-ended questions surveys were analyzed using SPSS Statistics 22.0. A significant improvement in teachers' computational thinking teaching–learning repertoire in a relatively short period has been recorded. Teachers also demonstrated increased confidence in the future delivering computational thinking-based lessons. The E-learning conceptual framework has illustrated the predictive power between user intent, user satisfaction, and Computational thinking (CT) knowledge benefits. Results demonstrate that myCTGWBL could be used to guide future planning when establishing CT knowledge acquisition initiatives, particularly among teachers.

Educational Challenges for Computational Thinking in K–12 Education: A Systematic Literature Review of “Scratch” as an Innovative Programming Tool

The use of information and communications technologies (ICTs) has emerged as an educational response amidst the COVID-19 pandemic, providing students the technological tools that enable them to acquire or strengthen the necessary digital skills to develop computational knowledge. The purpose of this study was to analyze Scratch, a programming language used to foster the teaching of computational thinking, particularly in K–12 education. A systematic literature review (SLR) was conducted, identifying 30 articles on the topic of Scratch and computational thinking in the database ProQuest Central from January 2010 to May 2020. These articles were analyzed to identify the use of Scratch worldwide and the educational impact it has on computational thinking, specifically in K–12 education. The results highlight the following: (1) countries which incorporated Scratch into their teachers’ study plans (curricula); (2) the transformation of learning environments that Scratch promotes; and (3) the importance of incorporating tools like Scratch in the current curricula and, more importantly, developing the framework for innovative ICTs capable of transforming education.

Raranga te Kete Aronui—Weaving the Basket: Continuing With Open, Flexible, and Distance Learning

This issue of the Journal uses the metaphor of raranga te kete aronui (weaving the basket of the pursuit of knowledge) as it continues the conversation of developing areas of open, flexible, and distance learning (OFDL). It comes at a time when the COVID-19 pandemic has disrupted traditional face-to-face teaching in classrooms on a global scale, and the value of open, flexible, and distance learning has become starkly apparent. This issue has five articles which contribute to the ongoing knowledge presented in this issue. There are two articles based on educational theory: Higgins explores the theoretical history of OFDL, and the work of Nichols et al. is based on Mezirow’s 10 stages of transformative learning. Three research articles provide insight into a range of specific areas: Sime et al. use networked learning theory to investigate the design of a social exploration MOOC, Irons and Hartnett present exploratory research into the teaching of computational thinking in junior classrooms in New Zealand, and Nyugen describes the design and development of qualifications in early childhood education and care to meet a demand for New Zealand home-based early childhood educators to be qualified. These are all contributions to our weaving and filling of te kete aronui.

Research on Head-Mounted Virtual Reality and Computational Thinking Experiments to Improve the Learning Effect of AIoT Maker Course: Case of Earthquake Relief Scenes.

In this study, the head-mounted virtual reality (VR) technology is adpoted for computational thinking teaching in the AIoT Maker course teaching. The earthquake relief situation is designed in the VR in the course scenario, because in the context of situational thinking, pre-emptive training in the face of emergency disasters has been conducted through observation meetings or training courses. Through listening to lecturers or experienced personnel to share experiences, students often have a harder time thinking about real scenes and it is harder to think creatively how to design with the emergency disaster response. In view of this, this research will combine the development and evaluation of earthquake relief training courses for head-mounted VR and computational thinking experiments to explore the use of VR and computational thinking experiments to drive students to create ideas for real disaster relief scenarios. Through computational thinking, students think about different script situations and discuss in each scene to find a suitable maker design of the AIoT project. Finally, this study combined with its modular space program training to develop students’ programming skills. According to the experiment, this study is able to strength students’ practical learning motivation, and follow-up employ ability training for course learning.

Integrating Computational Thinking into Social Studies

Computational Thinking (CT) has recently been addressed as one of the key skills for the twenty-first century. Integrating CT into different subject areas of K-12 education is also now widely accepted to improve the quality of instruction. In that sense, it is important to enable educators and researchers to recognize how to integrate computational thinking into K-12 classrooms and to study how students learn to think computationally in social studies courses. Besides, providing good practice on CT helps to develop common ground for the teaching of computational thinking in social studies subject areas. Hence, the purpose of this paper is to provide a framework for social studies teachers with regard to how CT can be integrated into K-12 classrooms for social studies. Moreover, a practical implementation idea is also suggested based on this framework. This paper is expected to provide an insight to social studies teachers who want to integrate CT into their classroom in the future and support them in teaching context.

Pedagogy of Computational Thinking from the Psychology: a Problem-Solving Thinking

Computational thinking should be understood as problem-solving thinking, beyond its link to programming. Therefore, it is necessary to address this thought’s structure through its cognitive processes to obtain an operational definition that allows this thought’s pedagogy to be adequately addressed in the classroom, regardless its development source. In this article, five processes inherent to this thought are determined, identifying only those that are always used. These processes are operatively defined from a psychological and a pedagogical perspective. The processes are abstraction, generalization, evaluation, creation of algorithms and decomposition of the problem. The first four processes present an inherent relation to problem-solving that can be verified, while, the last one, decomposition, can be considered not fundamental in problem solving and, therefore, linked to computational thinking. The performed analysis and categorization prove that decomposition is the key and central process of computational thinking. Therefore, computational thinking teaching must always be approached from the decomposition of problems or tasks that allow the simplification of the rest of the processes involved. This should involve different resources such as programming, playing games, problem-solving, or the creation of projects.

Developing young children's computational thinking with educational robotics: An interaction effect between gender and scaffolding strategy

The study examined the effects of learning with the Bee-Bot on young boys' and girls' computational thinking within the context of two scaffolding techniques. The study reports statistically significant learning gains between the initial and final assessment of children's computational thinking skills. Also, according to the findings, while both boys and girls benefited from the scaffolding techniques, a statistically significant interaction effect was detected between gender and scaffolding strategy showing that boys benefited more from the individualistic, kinesthetic, spatially-oriented, and manipulative-based activity with the cards, while girls benefited more from the collaborative writing activity. In regards to the children's problem-solving strategies during debugging, the results showed that the majority of them used decomposition as a strategy to deal with the complexity of the task. These results are important, because they show that children at this very young age are able to cope with the complexity of a learning task by decomposing it into a number of subtasks that are easier for them to tackle. The research contributes to the body of knowledge about the teaching of computational thinking. In addition, the study has practical significance for curriculum developers, instructional leaders, and classroom teachers, as they can use the results of this study to design curricula and classroom activities with a focus on the broader set of computational thinking skills, and not only coding.