Computational Thinking Research Articles

Instrumen Literasi Numerasi Berbasis Kemampuan Berpikir Komputasi pada Matematika SMP: Pembuktian Validitas Isi dengan Aiken’s.

This research aims to prove the content validity of a numeracy literacy instrument based on computational thinking skills using Aiken's method. There are five questions divided into nine parts, all of which focus on the material “Algebraic Forms”, ​​and have been validated by five validators from two leading universities. The data analysis technique applied is the Aiken's method, which is used to assess the extent to which this instrument meets the validity criteria. The results of the analysis show that most of the questions in the instrument received good validity scores, with an average validity of 0.81. This score indicates that this instrument is relevant and effective for measuring students' abilities in numeracy literacy and computational thinking. Apart from that, input from validators regarding the use of simpler language for grade 8 students is very valuable and is expected to improve students' understanding of the questions given. It is hoped that these results can contribute to the development of higher quality educational evaluation instruments, as well as being the basis for further research involving instrument testing to prove construct validity and reliability in the context of mathematics learning

The importance of coding and translation between programming languages in sequential activities of pre-service teachers: an approach

AbstractIn the last two decades, computational thinking has gained wide relevance in international educational systems. The inclusion of this new type of thinking poses educational challenges with some underlying research questions that need to be answered to meet these challenges with quality. Thus, this study focuses on analyzing the difficulties that teachers in initial training experience have, when carrying out translation tasks of programming languages used by certain educational robots, in this case, the Cubetto. For this purpose, a specific learning sequence has been designed to work with different programming languages (Cubetto, Bee-Bot, Scratch) and natural language. The work of early childhood and elementary trainee teachers in these tasks has been analyzed using a descriptive approach. The main results are: (1) some of the difficulties encountered are clearly caused by the Cubetto hardware (regardless of the language to which it is translated) and (2) the designed learning sequence has enabled coding skills to be improved remarkably. We conclude that translation tasks between programming languages are necessary in initial teacher training to improve their ability programming and their computational thinking, and for them to be able to detect the disadvantages and benefits of educational robots in their transposition to the classroom.

Systematic Review of Instruments to Assess Computational Thinking in Early Years of Schooling

Computational thinking (CT) is considered a key competence in today’s digital era. It is an emerging construct that relates to critical thinking and creativity. Research on its assessment is in the process of consolidation. This systematic review aims to analyze studies that have used CT assessment instruments for children and adolescents aged 4 to 16 years in order to identify which variables, they assess and their psychometric properties. The search and analysis were carried out following the PRISMA statement protocol, analyzing 50 articles published between 2006 and March 2023. An increase in the publication of CT measurement instruments is observed, with 54% of them supported by evidence of validity and 88% by reliability, highlighting construct validity, followed by content and criteria validity. China leads in the number of publications, while Asia and Europe concentrate most of the research. There is a noticeable contribution from South America, evidencing the lack of participation from Central and South American countries in this field of study.

Enhancing Computational Thinking, Spatial Reasoning, and Executive Function Skills: The Impact of Tangible Programming Tools in Early Childhood and Across Different Learner Stages

Enhancing Computational Thinking, Spatial Reasoning, and Executive Function Skills: The Impact of Tangible Programming Tools in Early Childhood and Across Different Learner Stages

The influence of scaffolding for computational thinking on cognitive load and problem-solving skills in collaborative programming

The influence of scaffolding for computational thinking on cognitive load and problem-solving skills in collaborative programming

College of education students’ perceptions of their computational thinking proficiency

This study aimed to investigate college of education students’ level of computational thinking proficiency and the differences in their level based on their demographic characteristics, i.e., gender, program, and age. The study used a descriptive research design in which 190 students in the College of Education completed a computational thinking questionnaire. The computational thinking scale consisted of five dimensions, i.e., creativity, algorithmic thinking, cooperativity, critical thinking, and problem-solving. The results showed that the level of computational thinking among students was diverse and fell within a moderate range. Gender-based analysis indicated a significant difference in only one dimension of computational thinking, i.e., algorithmic thinking, with females scoring lower than males. In addition, based on students’ academic program, significant variations were observed in algorithmic thinking and overall computational thinking levels, particularly between Bachelor and PhD programs, with PhD students scoring higher than Bachelor students. Additionally, the age-based analysis highlights significant differences, with older students consistently outperforming younger ones across various computational thinking dimensions. Based on the findings a set of recommendations was provided.

Developing Computational Thinking through Mathematics Learning in Indonesia: Scientific Mapping and Bibliometric Analysis

This research aims to explore and map the teaching methods used in developing Computational Thinking (CT) through mathematics learning in Indonesia, using a bibliometric analysis approach. Based on a literature review from Scopus and Sprott-indexed databases, this research analyzes trends, contributions and challenges in the implementation of CT at various levels of education. Teaching methods such as Scratch, Problem-Based Learning (PBL), Augmented Reality (AR), and robotics were identified as the most effective strategies in improving students' computational thinking skills. The findings show that the majority of publications published in educational and CT-related sources about teaching mathematics are mostly about teaching computational skills and teaching computer programming using practice and algorithmic thinking, although these methods have had a significant impact, some limitations, such as lack of instrumentation, limited technological resources, and curriculum adaptation are still challenges. This analysis also highlights opportunities for further research in developing more comprehensive evaluation instruments and improving technology access in computational education. It is hoped that the results of this research can provide guidance for educators, policymakers and researchers to increase the integration of CT in the mathematics curriculum, as well as expand the scope of computational research in the Indonesian educational context. This research opens new insights to overcome barriers and optimize the potential of CT in the future.

지식재산 일반 교과를 통한 특허명세서 작성 교육의 시사점 및 개선 방안

Objectives This study scrutinizes the teaching of patent specification writing through the general intellectual property course, draws implications, and suggests ways to improve the 2022 curriculum. Methods This study was conducted in the following ways First, we compared and analyzed the documents of the general intellectual property curriculum of the 2015 and 2022 curricula to identify changes in the achievement standards related to patent specification writing education. Second, we systematically reviewed textbooks, teacher guides, and teaching and learning materials to investigate the content and methods of patent specification writing education in actual educational settings. Third, we analyzed the requirements of patent specification writing education and the differences between domestic and foreign countries by reviewing relevant laws and regulations such as the Patent Act and the Patent Act Enforcement Rules, and identifying international trends through overseas cases. Fourth, we verified the feasibility and effectiveness of patent specification writing education through generative AI by utilizing actual patent specification and Chet Giffity. Through this multifaceted analysis, we identified problems in the current patent specification writing education through general intellectual property courses and proposed improvement measures. Results The implications of patent specification writing education through general intellectual property courses are, first, that it does not fulfill both relevant performance standards and legal requirements. Second, there is a lack of consideration on the selection of invention ideas that are the subject of patent specification writing education. Third, the number of class hours required to teach patent specification writing through general intellectual property courses and the number of teachers to implement the program are insufficient. Conclusions To improve, first, all of the components of a patent specification should be available for writing. Second, it should be possible to protect student-generated invention ideas while broadening the scope of the patent specification. Third, generative AI can be utilized as an assistant teacher to solve the problem of lack of educational content, time, and teacher resources in patent specification writing education. If these improvements are applied and expanded, it is expected that the patent specification writing education through the general intellectual property curriculum in the 2022 curriculum will be more applicable in schools and have a significant educational effect on problem-solving and computational thinking skills.

A tool for qualitative data analysis designed to support computational thinking

A tool for qualitative data analysis designed to support computational thinking

Embodied Learning for Computational Thinking in a Mixed-Reality Context

This study examined the effects of embodied learning experiences on students’ understanding of computational thinking (CT) concepts and their ability to solve CT problems. In a mixed-reality learning environment, students mapped CT concepts, such as sequencing and loops, onto their bodily movements. These movements were later applied to robot programming tasks, where students used the same CT concepts in a different modality. By explicitly connecting embodied actions with programming tasks, the intervention aimed to enhance students’ comprehension and transfer of CT skills. Forty-four first- and second-grade students participated in the study. The results showed significant improvements in students’ CT competency and positive attitudes toward CT. Additionally, an analysis of robot programming performance identified common errors and revealed how students employed embodied strategies to overcome challenges. The effects of embodied learning and the impact of embodied learning strategies were discussed.

Exploring Debugging Challenges and Strategies Using Structural Topic Model: A Comparative Analysis of High and Low-Performing Students

Debugging is essential for identifying and rectifying errors in programming, yet time constraints and students’ trivialization of errors often hinder progress. This study examines differences in debugging challenges and strategies among students with varying computational thinking (CT) competencies using weekly coding journals from an online undergraduate CT course. Participants used Scratch, a block-based programming language, and their journals from five assignments were analyzed using Term Frequency-Inverse Document Frequency and Structural Topic Modeling. High-performing students engaged with diverse topics and specific blocks tied to their weekly projects while low-performing students faced repetitive and broad challenges, such as understanding motion blocks and broadcast concepts. These patterns reveal that low-performing students struggle particularly during the ‘diagnose the fault’ phase of debugging, often hindering their progress in the final stage. Such challenges highlight the necessity for targeted educational interventions to improve the debugging proficiency and overall CT skills. The study underscores the importance of further research into students’ logical thinking processes during code review and debugging, suggesting the use of think-aloud protocols and detailed tracking of debugging practices for deeper insights. This research contributes to the field by showing that differentiated instruction and strategic support can enhance debugging skills across different student performance levels.

Empowering K–12 pupils: Fostering problem-solving skills through sustainable entrepreneurship and computational thinking

ABSTRACT Preparing today’s students for a digital world with diverse social challenges requires innovative teaching–learning scenarios. To empower students to develop solutions in an increasingly complex world, it’s essential to strengthen both their subject-specific knowledge as well as their problem-solving skills. In the area of domain knowledge, the interplay between entrepreneurship, sustainability, and digital technologies has emerged as a critical factor in addressing global challenges through innovation. Although the individual competency areas are well documented in the relevant research, teaching–learning scenarios that combine sustainability, entrepreneurship, and information technology (IT) education are underrepresented. This article explores the integration of sustainability-oriented entrepreneurship education within IT education through a project-based teaching approach. To visualize and facilitate the learning process, a problem-solving canvas is integrated. Hence, it presents a best-practice example of how entrepreneurial IT education can be implemented in schools using hackathons. Additionally, the article provides recommendations for educational policy based on these insights.

The Effect of a training program based on the (TAWOCK) model for teaching computational thinking skills on teaching self- efficacy among female computer teachers

AbstractThe aim of research is to reveal the effect of a training program based on the TAWOCK model for teaching computational thinking skills on teaching self-efficacy among computer teachers. It used the quasi-experimental approach, with a pre-test and post-test design with a control group. An electronic training program based on the TAWOCK model was designed, and prepared (teaching self-efficacy scale). The research sample included (42) female teachers in the experimental group, and (39) female teachers in the control group. The research reached: There was a statistically significant difference at the level (α ≤ 0.05) between the mean scores of computer teachers in the experimental and control groups in the post application; In favor of the experimental group, the value of the ETA square for the total scale of teaching self-efficacy was (0.613); Which indicates the size of significant impact on the self-teaching effectiveness of female computer teachers. There was also a statistically significant difference at the level (α ≤ 0.05) between the mean scores of computer teachers in the experimental group in the pre and post applications; In favor of the post application, the value of Cohen’s coefficient for the total scale of teaching self-efficacy was (1.26).

Validating a measure of computational thinking skills in Chinese kindergartners

Validating a measure of computational thinking skills in Chinese kindergartners

Integrating unplugged and plugged activities for holistic AI education: An embodied constructionist pedagogical approach

AbstractThere is a growing consensus that AI literacy requires a holistic lens, including not only technical knowledge and skills but also social and ethical considerations. Yet, providing holistic AI education for upper-primary students remains challenging due to the abstract and complex nature of AI and a lack of pedagogical experiences in schools. Against this backdrop, this study employs a design-based research (DBR) methodology to develop pedagogical solutions and theoretical knowledge. Drawing upon theories about AI literacy and learning sciences, this study proposes a novel pedagogical approach, namely, the embodied constructionist approach. This approach, by integrating embodied analogies and constructionist making, forges a cyclical understand–make–reflect process. Through this process, students gradually comprehend the conceptual, technical, and ethical dimensions of AI, towards holistic development in AI literacy. This approach was implemented and fine-tuned in authentic classrooms with 107 sixth graders over two years. During the implementation, a variety of qualitative data were collected from classroom observation, video-recording, student interviews and artifacts, and debriefings with the teacher. Using a case studies method, this study uncovered the overall learning progress demonstrated by the class in AI knowledge, skills, and ethical and critical reflections, as well as the reflections and struggles experienced by individual students. This study offers an age-appropriate pedagogy to promote inclusive, holistic AI education in the crucial, yet under-examined upper primary context. It highlights the potential of integrating AI literacy and computational thinking (CT) in K-12 education, while contributing to theoretical knowledge about embodied cognition and constructionism in the context of AI education.

New Trends in Education: Computational Thinking and Its Role in Improving the Quality of School Human Resources

This study aims to analyze how the application of computational thinking can affect students' analytical and problem-solving skills, as well as change the mindset of teachers from conventional teachers to innovators in one of the Junior High Schools in Banjarmasin City. This study uses a qualitative case study approach. Data were collected through observation, interviews, and documentation. Data were analyzed using thematic analysis techniques, including coding, identifying important themes, and interpretation in the context of computational thinking theory. Data triangulation was carried out by comparing the results of observations, interviews, and document analysis to ensure the validity of the findings. The results of the study indicate that computational thinking plays a significant role in improving students' technical and analytical skills and encouraging the transformation of teachers' mindsets towards a more innovative and adaptive approach to technology. In addition, this study also found that the implementation of computational thinking successfully addressed the gap in technology skills among students, thereby increasing educational equality. The implications of this study indicate that the application of computational thinking in the school curriculum can be an effective strategy to improve the quality of education in Indonesia. However, this study is limited to one location. It does not consider gender factors and variations in student backgrounds, so further research is needed with a wider scope to obtain a more comprehensive picture.

THE MEDIATING EFFECTS OF ARTIFICIAL INTELLIGENCE LITERACY ON THE ASSOCIATION BETWEEN COMPUTATIONAL THINKING SKILLS AND ORGANIZATIONAL AGILITY AMONG SECONDARY SCHOOL TEACHERS

These days’ educational landscape forces teachers to adapt to changing demands and embrace innovations. In this study, Artificial Intelligence (AI) literacy was analyzed as how it mediates the association between Computational Thinking Skills (CTS) and Organizational Agility (OA) among secondary teachers. A quantitative causal mediation analysis design was utilized in this study. Standardized AI literacy test, CTS Test, and OA test instruments were utilized to gather pertinent data among 305 respondents. The test instruments were first subjected to confirmatory factor analysis for model fitness. Path and mediation analysis through structural equation modeling revealed that CTS significantly predicts AI literacy, AI Literacy significantly predicts OA, and CTS significantly predicts OA. It was found out that AI literacy partially mediates the relationship between CTS and OA among teachers. This recommends that schools should conduct a comprehensive training program to enhance teachers' CTS and AI proficiency for schools' sustained agility. Keywords: AI literacy, computational thinking skills, organizational agility, structural equation modeling, mediation analysis

Integration of computational thinking in initial teacher training for primary schools: a systematic review

Integration of computational thinking in initial teacher training for primary schools: a systematic review

Computational Thinking Readiness Level of First-Year Students of Mathematics Education

The main objective of this study was to measure the level of computational thinking readiness in prospective first-year mathematics education students. In addition, this study also aims to identify factors that influence their level of readiness towards computational thinking. This research is qualitative and descriptive in nature. This study describes first-year mathematics education students' mathematical computational thinking ability based on the theory of mathematical computational thinking. This study was conducted on first-year mathematics education students in the academic year 2023/2024. There were 16 first-year mathematics education students, all of whom were taken as samples in this study, to obtain more in-depth information about the computational thinking ability of first-year mathematics education students for further research development. The instruments used to collect data on first-year mathematics education students' mathematical computational thinking ability are (1) a mathematical computational thinking ability test and (2) an interview. The data obtained were calculated using statistical tests, and the results will be explained in depth. The mean score of the first-year mathematics education student's computational thinking ability test was 59.68, indicating that students generally have a fairly good level of computational thinking ability.

Bibliometric Computational Mapping Analysis of Publications on Computational Thinking in Science Education using VOSviewer

The use of computing tools has provided support for learning science content and assisted students in understanding modern science experiences. Therefore, students must have an understanding on how computation could be useful for supporting science learning goals. In other words, students need a new skill to fulfil the tasks, that is computational thinking. This study aims to determine the development of research on computational thinking in science education through a bibliometric approach using the VOSviewer application. The article data was obtained from the Google Scholar database. The application used to obtain the article data was Publish or Perish. The keyword used to search for articles is "Computational Thinking in Science Education". 344 articles that were considered relevant to these keywords were found. The articles used were articles published in the last 10 years (2013 – 2022). The findings showed that the research on this topic decreased from 57 studies to 13 studies after 2020, and it became very popular in 2020. Furthermore, the research on computational thinking in science education still has a high enough chance to be carried out. We examined how many articles had been published about computational thinking in science education and its relation to problem areas using VOSviewer. We hope that this research can be a starting point for research related to other fields.