Aspects Of Computational Thinking Research Articles

Computational Thinking Assessment in Primary and Secondary Education: A Meta-synthesis of tools, Methods and Pedagogical Approaches

Despite the widespread adoption of computational thinking (CT) across educational levels, challenges persist in its assessment due to diverse definitions, frameworks, and its practical application in classroom settings. This meta-synthesis investigates the assessment of computational thinking (CT) in primary and secondary education, synthesizing evidence from 12 reviews across five international databases, focusing on tools, methods, and pedagogical practices employed in assessing CT, with the aim to outline practical approaches for evaluating CT components. The review delves into the primary focuses of these syntheses, the CT skills and components assessed, and the methods and tools utilized, identifying gaps in current practices. The findings highlight a prevalent focus on programming skills, with less emphasis on cognitive processes and collaborative aspects of CT. The synthesis also points to the need for developing assessment tools and methods that encompass the broader spectrum of CT skills, suggesting avenues for future research and practical application in educational settings.

Enhancing computational thinking in children through logical puzzles: A machine learning approach for early coding education

This recent growth in early education in coding evidences the rising need for the computing-thinking-skills development in children. Though most of the programming curricula are based upon syntax and other basic concepts of coding, computational thinking encompasses broader cognitive skills, such as problem-solving, abstraction, and logical reasoning. This research therefore intends to fill a gap in research and will investigate the ways pre-coding games employ logical puzzles as an enhancement in developing computational thinking skills in children aged 7-10 years and how these affect the acquisition of programming knowledge. In all, there will be two groups assigned: one will be exposed to logical-oriented puzzle training, Group A, and the other will be a control group, Group B, which receives only regular standard lessons in programming introduction. Pre- and post-measures of computational thinking and basic programming skills will be obtained from the participants. The machine learning algorithms, such as Random Forest for prediction in terms of improvement in subject performance in computational thinking and K-Means clustering to identify patterns in their development of skills, will be implemented in their pure or integrated forms to analyze data. Logistic Regression will be executed in order to model the odds of improved performance in programming given an intervention of exposure to puzzles. The research study will, therefore, apply these algorithms in comparing the performance of the two groups and reveal the aspects of computational thinking to which the greatest influence in a positive way through puzzle activities is exerted. It is expected that children exposed to logical puzzles may show significant improvements in both computational thinking and programming skills. These findings should be useful to educators in their effort to show how logical puzzles can be integrated into the curricula of early coding education to build foundational skills and thereby contribute to a refinement of best practices in STEM education.

The Effect of Computer-Supported Stem Applications on Secondary Students' Achievement and Computational Thinking Skills

In this study, the effect of STEM applications integrated with computer- supported materials on mathematics achievement in the subject of ratio-proportion and percentages was examined. In addition, it was aimed to reveal the effect of these applications on computational thinking skills. Furthermore, we aimed to reach the opinions of the experimental group students about the materials they used, STEM applications, and the application process. A mixed method was used with a sample consisting of 89 students in grade 7 of a secondary school. An achievement test, a scale of levels of computational thinking, and learning diaries were used as tools for data collection. The data were analyzed using t-test and content analysis. It was found that there was a significant difference between the experimental and control groups in terms of achievement in favor of the experimental groups. In terms of computational thinking, there was a significant difference in favor of the experimental groups, except for the creativity aspect of computational thinking skills. Based on the findings obtained with the computational thinking skills scale the study had a positive impact on most aspects of computational thinking. Accessed through the learning diaries students' views on learning with STEM applications were generally positive. In particular, the opinions on computer-supported materials pointed to a very satisfactory process. The findings suggest that the inclusion of STEM activities and the use of computer technology in education contribute to students' computational thinking skills and learning.

Modern board games and computational thinking: results of a systematic analysis process

ABSTRACT In recent years, modern board games (MBG) have attracted the attention of academics due to their innovative mechanics and mechanisms, which seem to facilitate the creation of spaces for the development of various aspects of computational thinking (CT). This article examines a number of MBG to identify those that contain CT-promoting mechanics. We focus on MBG whose mechanics can implicitly support the development of CT, considering these games as valuable pedagogical tools for use in the classroom. Specifically, they can be used by groups of students to introduce, discuss and practice CT concepts. The research identifies several games considered ideal for achieving the aims of the PhD study. This article essentially explores the mechanics of carefully selected MBG, reflecting on how they integrate, support or relate to the development of CT, and discusses their implementation in educational contexts. The results suggest a practical approach to the selection of CT-promoting MBG, offering valuable insight for teachers and education professionals interested in using board games in education. The results point to the potential of these games as effective resources for developing CT in primary school students, contributing to both academic research and practical applications in education.

Advancing Computational Thinking in Mathematics Education: a Systematic Review of Indonesian Research Landscape

Computational Thinking (CT) has emerged as a crucial and foundational skill in the 21st century, capturing the attention of researchers across various domains, including mathematics education in Indonesia. This research identifies and analyzes trends, themes, focuses, and research findings on CT through mathematics learning in Indonesia. This Systematic Literature Review (SLR) adheres to the PRISMA guidelines, encompassing three stages: search, selection, and data analysis. The search process on the Scopus database, utilizing queries aligned with the research objectives, yielded 31 articles related to CT and mathematics education authored by Indonesian researchers. Subsequent selection involved criteria such as research focus, study type, document availability, and intervention differences, resulting in 14 articles. Data analysis employed Bibliometrix and NVivo 14 Plus software. The findings reveal a significant increase in research on CT in mathematics education from Indonesian researchers over the past two years, with an annual growth rate of 5.74%. This publication landscape involves contributions from 39 authors affiliated with 16 higher education institutions in Indonesia. Researchers have delved into diverse themes, including the analysis of CT skill achievement, the development of CT-oriented instructional models and media, and the creation of assessment tools to measure CT skills. These findings underscore the broad relevance of CT in the realm of mathematics education. As a burgeoning field of study, numerous aspects of CT remain open for further research, development, and exploration, especially those related to mathematics. To enhance the impact and implementation of Computational Thinking (CT) within the context of Indonesian education, future research may consider investigating innovative pedagogical approaches, assessing the long-term impact of CT interventions, and exploring the potential integration of CT across various educational levels.

Computational Thinking in Diverse and Inclusive Preschool Settings – Cracking the Code

Abstract: Computational Thinking is a fundamental skill just as reading, writing and mathematics. It involves the development of higher-order thinking skills, such as problem-solving, and borrows from computer-science methods like the concepts of abstraction and decomposition. In the context of young populations, preferences, adoption, encouragement, and sensitization, are relevant to the development of Computational Thinking attitudes and skills. The present study was designed to explore how Computational Thinking can be integrated into a typical curriculum, considering the notions of inclusion and diversity. Thirty children (aged 4-6 years) from diverse ethnical backgrounds participated in a Hidden Treasure Hunt learning activity which was distinct by the absence of explicit instructions. Previous research show that while significant emphasis is often placed on the cognitive aspects of Computational Thinking, the affective and emotional dimensions are frequently overlooked. This study underscores the importance of not only imparting knowledge and building skills but also the role of attitudes and emotions in nurturing an environment for discovery and higher-order thinking abilities development in young children.

Visual modelling and emergent aspects of computational thinking: Example from a cross-disciplinary course

In 2006, Jeanette Wing announced—in a very short, three-page paper—a new discipline she labelled ‘Computational Thinking.’ This new field, CT, she said, is not the same as just programming, because it also includes the energies, constructs and ambitions behind programming—such as problem-solving, heuristic and algorithmic thinking, data manipulation, abstraction, reduction, transformation, generalization, data manipulation, and pattern finding. Wing asserts that CT is an important methodology for learning in general, and that CT’s benefits extend into ‘all parts of life.’ If this claim is true, then CT should be crucial not only for students of STEM subjects—who already use computational methods—but also for those studying disciplines traditionally associated with the humanities, qualitative social sciences and arts and letters. But where are the voices from these other fields? Where are the studies of observed learning when computational methods are applied within these other non-STEM subjects? And where do we find instances of new kinds of thinking emerging from this mix? I want to address these questions in a personal and idiographic way. I describe the history, activities and outcomes of a university-level course I invented, called Visual Modelling. The course required students to intermingle computational methods with drawing and design tools. Using words and images I explain some of the ideas and procedures that emerged over the fifteen years of co-teaching this cross-disciplinary course. Everyone participated in the ongoing back-and-forth translation between the different notational languages, everyone benefited, and this level

Examining STEM Students' Computational Thinking Skills through Interactive Practicum Utilizing Technology

This research study explores and compares the computational thinking skills demonstrated by STEM students during interactive practicums involving both virtual laboratories and physical laboratories. The objectives of the study are to assess the performance of computational thinking skills in each practicum setting and to determine any differences between the two environments. An experimental approach was adopted, and 106 first-year STEM students from a distinguished private university in Indonesia participated in the study. The students were divided into two groups, one using virtual labs and the other using physical labs. The study employed a portfolio instrument to assess various aspects of computational thinking, including problem reformulation, recursion, problem decomposition, abstraction, and systematic testing. The findings show that both groups of students achieved "good" scores for computational thinking skills. However, students in the virtual labs group demonstrated superior skills compared to the physical labs group. The aspects of problem reformulation and abstraction received the highest scores in both groups, while problem decomposition received the lowest scores. A MANOVA test confirmed statistically significant differences in computational thinking skills between the two practicum environments. The study suggests that the use of virtual labs can positively impact students' computational thinking abilities. The results have implications for educators and institutions seeking to enhance students' computational thinking skills and design effective STEM practicums.

An AI-enhanced pattern recognition approach to temporal and spatial analysis of children's embodied interactions

Multimodal video analysis is a complex and time-consuming process for a researcher; it entails capturing, watching, and re-watching video data to identify which segments best inform or address the questions that drive the research. Modern AI applications can alleviate the challenges that arise during the fine-grained analysis of learners' multimodal interactions captured through video. In this study, we present a supervised approach to training a deep neural network to analyze children's computational thinking (CT) captured through multimodal video data. The approach first uses a set of images extracted from video data to train the AI to map them to labels generated using a priori theory. Confusion matrices were used to establish the performance of the AI by comparing AI predictions to human analysis on a validation set of data. The findings suggested that the AI classified several aspects of children's CT in a way that was highly consistent with human analysis, demonstrating how the AI could serve as an additional team member during multimodal analysis. Implications for using AI to ease the challenges of multimodal analysis of video data are discussed.

Computational thinking as part of compulsory education: How is it represented in Swedish and Norwegian curricula?

In recent years, many countries have revised their school policy documents to incorporate digital competence, computational thinking and programming. This study examines and compares how and in what contexts Nordic curricula, Swedish and Norwegian in particular, embody aspects of computational thinking. Results show that only parts of the practices defined in the computational thinking framework used for analysis could be explicitly identified in the curriculum documents. The most salient computational thinking practice represented in both the Swedish and Norwegian curricula is programming, and programming is primarily recognized as a method and tool for learning other subject content and not as a knowledge domain in its own right. Implicitly both curricula leave leeway for teachers to implement a broader approach to computational thinking. However, this would need much time, teacher competence and effort, and what it requires seems to be under-communicated in the curricula, leaving schools and teachers with major challenges.

Characterizing Computational Thinking in the Context of Model-Planning Activities

Computational thinking (CT) is a critical skill needed for STEM professionals and educational interventions that emphasize CT are needed. In engineering, one potential pedagogical tool to build CT is modeling, an essential skill for engineering students where they apply their scientific knowledge to real-world problems involving planning, building, evaluating, and reflecting on created systems to simulate the real world. However, in-depth studies of how modeling is done in the class in relation to CT are limited. We used a case study methodology to evaluate a model-planning activity in a final-year undergraduate engineering classroom to elicit CT practices in students as they planned their modeling approach. Thematic analysis was used on student artifacts to triangulate and identify diverse ways that students used CT practices. We find that model-planning activities are useful for students to practice many aspects of CT, such as abstraction, algorithmic thinking, and generalization. We report implications for instructors wanting to implement model-planning activities into their classrooms.

Implementation of Computational Thinking and Ignatian Pedagogy in Geometry subject for Elementary School Pre-Service Teachers

This study aims to describe the implementation of Computational Thinking in the flipped classroom in the Geometry course based on Ignatian Pedagogy for prospective elementary school teachers at Sanata Dharma University. The research method used is descriptive. The research subjects were pre-service teacher Sanata Dharma University class 2017. The data collection techniques used were observation, interviews, and documentation. The data were analyzed by using qualitative analysis. This research concludes that the implementation by learning steps, namely (1) context, (2) experience, (3) action, (4) evaluation, (5) reflection. In this step, four aspects of Computational Thinking are developed, namely (1) decomposition, (2) pattern recognition, (3) abstraction, (4) algorithm. The results of the learning reflection show the response that students like the learning design.

Validating the effectiveness of game-based learning approach in the form of video game for assessing computational thinking

This research aims to validate the effectiveness of students’ understanding in four aspects of computational thinking with the game-based learning assessment. The four aspects of computational thinking involved in this research are decomposition, pattern recognition, abstraction, and algorithm. This research will use a mixed method design approach with a quasi-experiment using a pre-test and post-test nonequivalent group design. The quasi-experiment will validate the effectiveness of students’ understanding on the decomposition, pattern recognition, abstraction, and algorithm aspects of computational thinking with the game-based learning assessment. The qualitative data gathered will be analyzed using thematic analysis. It is expected that the students’ understanding in four aspects of computational thinking with the game-based learning assessment will vary in terms of the effectiveness.

Teachers’ Ontological Perspectives of Computational Thinking and Assessment: A Text Mining Approach

As a dynamic and multifaceted construct, computational thinking (CT) has proven to be challenging to conceptualize and assess, which impedes the development of a workable ontology framework. To address this issue, the current article describes a novel approach towards understanding the ontological aspects of CT by using text mining and graph-theoretic techniques to elucidate teachers’ perspectives collected in an online survey (N = 105). In particular, a hierarchical cluster analysis, a knowledge representation method, was applied to identify sub-groups in CT conceptualization and assessment amongst teachers. Five clusters in conceptualization and two clusters in assessment were identified; several relevant and distinct themes were also extracted. The results suggested that teachers attributed CT as a competence domain, relevant in the problem- solving context, as well as applicable and transferrable to various disciplines. The results also shed light on the importance of using multiple approaches to assess the diversity of CT. Overall, the findings collectively contributed to a comprehensive and multi-perspective representation of CT that refine both theory and practice. The methodology employed in this article has suggested a minor but significant step towards addressing the quintessential questions of “what is CT?” and “how is it evidenced?”.

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.

Inspiring or confusing – a study of Finnish 1–6 teachers’ relation to teaching programming

There is limited research on teaching and learning of programming in primary school and even less about aspects concerning teaching programming from teachers’ viewpoint. In this study, we explore how Finnish 1-6 primary school teachers (N=91), teaching at schools with Swedish as the language of instruction, relate to programming and teaching of programming, one year after the introduction of the new national curriculum that included programming. The teachers’ relation to programming is studied by analyzing their view on programming, perceived preparedness to teach programming and their attitudes towards teaching programming. The main results of the present study are that the responding teachers approach programming in school with mixed emotions, but the majority claim to have sufficient preparedness to teach programming, and many of them have a positive attitude towards the subject. The findings indicate that the most important factor for high perceived preparedness and positive attitude is sufficient domain knowledge. The teachers’ views on programming are very diverse, ranging from focusing only on the connection to elementary step-by-step thinking to more sophisticated reasoning connecting to central aspects of computational thinking and other educational outcomes. The findings suggest that there is a need for educational efforts to make the connection between mathematical content and programming more visible for primary school teachers.

Analysis of Student Computational Thinking in Solving Social Statistics Problems

This study aims to see students' computational thinking in solving social statistics questions and to find out why students experience their mistakes. This type of research uses a descriptive qualitative approach. The subjects used in this study were Governmental Science students taking the Social Statistics course. Data collection techniques were carried out by observation and tests. The instruments used in this study were the observation sheet and the test question sheet. The analysis is carried out by reducing the data first, then presenting the data, and ending by concluding the results of the computational thinking indicator. The results showed that all aspects of computational thinking have been carried out by students, starting from Decomposition, Pattern Recognition, Abstraction, and Algorithm design. Students get the highest percentage, namely algorithm design with 84% and the lowest on decomposition with 65.5%. The cause of errors, in general, is because students are not used to completing in a structured manner. Students are accustomed to solving problems by directly substituting values into the formula without first writing down what is known and looking for what is needed in the questions first.

Characterising computational thinking in mathematics education: a literature-informed Delphi study

ABSTRACT Recently, computational thinking (CT) has attracted much research attention, especially within primary and secondary education settings. However, incorporating in mathematics or other disciplines is not a straightforward process and introduces many challenges concerning the way disciplines are organised and taught in school. The aim of this paper is to identify what characterises CT in mathematics education and which CT aspects can be addressed within mathematics education. First, we present a systematic literature review that identifies characteristics of CT that have been explored in mathematics education research. Second, we present the results of a Delphi study conducted to capture the collective opinion of 25 mathematics and computer science experts regarding the opportunities for addressing CT in mathematics education. The results of the Delphi study, which corroborate the findings of the literature review, highlight three important aspects of CT to be addressed in mathematics education: problem solving, cognitive processes, and transposition.

Integrated activities in STEM environment: Methodology and implementation practice

AbstractIntroductionScience, Technology, Engineering, and Mathematics (STEM) and STEAM (with A for Arts) have evolved to symbolize the renewal of science education. STEAM education offers a number of benefits, such as improved problem analysis and solving skills, as well as the development of creative abilities. Many researchers reiterate the importance of STEAM‐related activities and programs, especially the integration of maker education. Despite much interest in STEAM, it is often challenging for many educators to incorporate integrated activities into their teaching practice. This paper deals with the value of STEAM integration in a methodological sense, with a focus on the maker's laboratory and physical computing, as well as the application of design thinking and computational thinking approaches.Motivation and ObjectivesThe goal of this study is to develop a comprehensive conceptual framework for integrated STEM curricula focusing on the following research questions: (a) how to improve daily activities of STEM education by combining the activities of different laboratories and using a design thinking approach? and (b) how to combine FabLab activities and physical computing related to teaching different aspects of computational thinking in the context of STEM?Research Methodology and MethodsAs a research methodology, we implement a mixed methods strategy to combine theoretical study and empirical research based on a synthesized literature survey and the process of iterative model development based on an observational case study. We conduct a detailed case study of two applications of integrated activities based on FabLab and physical computing integration, and illustrate how design thinking can guide teachers to open up for interdisciplinary, creative, and project‐based opportunities.Results and FindingsThe paper provides a conceptual framework for STEM integration activities and step‐by‐step guidelines on how design thinking methods could could interact in practice. The implications of the results may be useful for educators seeking recommendations for the integration process, which enable educators to design hands‐on activities and incorporate integrated aspect of students' STEAM learning into teaching practice. In conclusions, the authors suggest that as interdisciplinary crossroads, design thinking provides a natural bridge between subjects, and fits especially to integrate activities of the maker's labs and physical computing, focusing on the integration of computational thinking and computational making approaches within STEM education environment. The absence of a statistical evaluation, which is positioned as a further research step, may be mentioned as a limitation of the study.

The relationship between Executive Functions and Computational Thinking

We argue that understanding the cognitive foundations of computational thinking will assist educators to improve children’s learning in computing. We explain the conceptual relationship between executive functions and aspects of computational thinking. We present exploratory empirical data from 23 eleven year old learners which investigates the correlation between assessments of programming and debugging in the visual language Scratch and scores from the BRIEF 2 assessment of executive functions. The initial data shows moderate to large correlations between assessments of debugging and programming with the BRIEF2 teachers’ rating of executive function as manifested in classroom behaviour. Case studies from the empirical data are used to qualitatively illustrate how executive functions relate to a game making task. We discuss the implications of these findings for educators, and present suggestions for future work.