Assessing computational thinking skills of science and mathematics upper-secondary school students

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 notesWhat 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.

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

<span lang="EN-US">Based on the study, computational thinking skills are influenced by science, technology, engineering and mathematics (STEM) skills, and there is a relationship between computational thinking skills and 21st-century skills. However, studies related to STEM attitudes, computational thinking and their impact on 21st-century skills are still very few and limited. The purpose of our study was to examine the impact of STEM attitudes and computational thinking on 21st-century. This research uses a quantitative approach. The participants of this study were students of a vocational school in Bantul Regency, Yogyakarta, Indonesia (N=290). Research data in STEM attitude, computational thinking, and 21st-century skills using a questionnaire. The data were analyzed using structural equation modeling techniques using the Smart PLS application. The results of the study obtained several findings, including: the model proposed in this study was valid; STEM attitude has a positive and significant effect on computational thinking; and computational thinking has a positive and significant effect on 21-st century skills. It can be argued that when STEM attitudes and computational thinking are more positive, 21-st century skills will improve. These findings have implications that curriculum development and STEM learning practices have to develop students’ computational thinking skills and 21st-century skills, especially in vocational schools.</span>

The latest TIMSS report highlighted that secondary school students from Malaysia did not perform well in this global assessment on mathematics achievement. Some studies have pointed out that students’ mathematics achievement can be improved by equipping them with computational thinking. Therefore, this study examined the development of computational thinking skill and mathematics problem-solving skills via mathematics modelling activities among secondary students in Malaysia. The research instrument used for the assessment of computational thinking was adapted from UK Berbras Challenges and CAS Barefoot Team from United Kingdom. In addition, rubrics for development of mathematics problem solving skill was adapted from Polya problem solving model. This study adopted qualitative approach and the modelling activities were conducted for six weeks. The activities were introduction of modelling, individual modelling task and group modelling task. Data were also collected based on results of computational thinking test and mathematics test. Data from observation and interviews were analyzed, and the scores obtained from both tests were compared and analyzed as well. Based on the findings of the study, it could be concluded that the students progressed at different levels during the development of their computational thinking skill and mathematics problem-solving competency via mathematics modelling activities. These results indicated that mathematics modelling activities can be conducted at schools to improve students’ performance in Mathematics.

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.

Introduction: This study aimed to explore the components of computational thinking skills at the End of Term Summative Assessment (ETSA) and End of Year Summative Assessment (EYSA) questions as well as the profile of computational thinking skills in science and mathematics subjects of fifth-grade students in Surakarta City, Indonesia. Method: This was a qualitative study with a case study approach. Data were collected through analysis of ETSA and EYSA documents, which include test instruments and student answers. Sampling was carried out using purposive sampling by considering the level of cognitive development of students. Results: The results showed that each ETSA question included components of decomposition, pattern recognition, abstraction, and algorithm design. Meanwhile, each EYSA question included different components from one question to another. The profile of students' computational thinking skills showed variation in the success of answering questions, with significant differences between components and types of questions. Conclusions: This study concludes that ETSA questions are more consistent in covering all components of computational thinking skills compared to EYSA. The profile of student skills varies, with some components showing lower results. The implications of these findings include the need for adjustments in the curriculum and teaching methods to emphasize more evenly distributed mastery of computational thinking skills. Further research should explore the causes of variation in mastery of these skills and develop more comprehensive evaluation instruments.

Analysis of the relation between computational thinking skills and various variables with the structural equation model

This research aims to examine the effect of Mind Games activities on problem-solving skills and computational thinking skills of 5th grade students. Sequential explanatory design, one of the mixed research methods, was used in the research. The research was carried out in a quasi-experimental design pretest-posttest without a control group with 17 5th grade students in a secondary school in Adıyaman. The research was carried out with an experimental period of 6 weeks. Before the experimental study, the problem-solving skills and computational thinking skills scales were applied to the students as a pre-test. Kapsul game activity was performed in the first week of the experimental study. ABC Baglama activity was held during the week. Sudoku activity was held in the 3rd week. In the 4th week, Three Stone game activities were held. Kendoku game activity was held in the 5th week. In the 6th week, Kakuro game activity was held. Statistical values in the study were calculated using the SPSS program. To collect quantitative data, a pre-test of problem-solving skills and computational thinking skills was applied to the students before the experimental process. After the experimental process, problem-solving skills and computational thinking skills scales were applied as a posttest. The applied pre-test and post-test results were analyzed with the paired sample t-test. Additionally, to collect qualitative data to strengthen the research, an interview form was applied to obtain the opinions of the students about the experimental process. In line with the findings obtained because of the experimental study, it can be said that the mind game activities have a positive effect on the students' computational thinking and problem-solving skills, and the lesson turns into more fun.

The study aimed to determine the effect of the information technologies course on students' computational thinking skills and technology-mediated learning process. The study was conducted on 237 first-year students of the Faculty of Education who were enrolled in the information technology course, and a one-group pretest-posttest design was used. Dependent t-test, independent t-test, and correlation analysis were used to analyze the data. In the results obtained from the study, it was found that the information technologies course did not make a significant difference on the students' computational thinking skills, while it made a significant difference on the effect of technology-mediated learning on the learning process. When the effect of the information technologies course on computational thinking skills and technology-mediated learning process in terms of gender factor was considered as pre-test and post-test, there was a significant difference in favor of male students in terms of computational thinking skills and technology-mediated learning process within the scope of pre-test data, while there was no significant difference within the scope of post-test data. The study also showed that there was a positive and moderate relationship between students' computational thinking skills and their attitudes toward the technology-mediated learning process. In the context of this finding, it can be stated that technology-enhanced learning environments can have a positive effect on the development of computational thinking skills, and that lessons delivered in such learning environments can contribute to the development of students' creativity, algorithmic thinking, critical thinking, problem solving and collaborative working skills.

With the sub-skills covered, there are many studies aimed at providing students with computational thinking skills that are known to be an important skill for today's students. In this study, it is aimed to investigate the effect of code.org applications on the development of computer thinking and algorithm development skills of the students. In this study, experimental research design with pre-test and post-test control group was used. A total of 67 middle school of 6th grade students, 32 of who were in the control group and 35 in the experimental group, participated in the study. The study was planned to cover 6 weeks of information technology and software courses with students. The course was enriched with the applications in Code.Org site for the experimental group students. The control group was treated appropriately course curriculum to their students. In the study, the scale of computer thinking skill levels and algorithm development achievement test were applied to the students as pre-test and post-test. When the data obtained in the study is examined, it is seen that there is no significant difference between the pre-test results of algorithm development achievement test and computer thinking skill levels scale. However, when the differences between pre-test and post-test scores of both tests were examined, it was seen that there was a significant difference in favor of the experimental group. As a result, it can be said that code.org applications used by experimental group students have positive effect on developing algorithms and computer thinking skills of students.

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.

Computational thinking skills have been a popular term for teachers worldwide, and PISA 2022 will become the first PISA in evaluating them. Computational thinking helps students enhance their potential in contributing to other disciplines. However, students’ computational thinking skills at SMP Negeri 8 Batam were low. In overcoming the problem, the teacher employed STEAM learning as an alternative approach in stimulating students’ computational thinking skills. A teaching aid, named 4Dframe, was utilised to support the STEAM-based teaching. The objective of this action research study is to illustrate the effect of employing STEAM approach and the 4Dframe as the teaching assistance in developing students' computational thinking skills. The study involved 40 students of 9th grade in SMP Negeri 8 Batam, Indonesia. Three STEAM activities incorporating Warka water tower, Batam-Bintan straw bridge, and planting machine were performed in eight online meetings. In each activity, the students administered decomposition, abstraction, pattern recognition, and algorithm as the cornerstones of computational thinking. The data were gathered through observational forms during the learning and test to evaluate students’ computational thinking skills. The results present that 73% and 88% of students acquired the minimum score for the computational thinking post-tests on the first and second cycle respectively. Although sample and methodology limitations prevent any claim to generalisation, this learning strategy could be implemented as an alternative for conducting mathematics learning activities in elevating students’ computational thinking skills with students in similar contexts.

This research aims to create a tool for assessing students' computational thinking (CT) skills in relation to biology concepts. The study followed a research and development approach, utilizing a modified 4D design model, with the dissemination phase excluded. Various data collection techniques were employed, including observations, literature reviews, documentation, surveys, interviews, and tests. The findings showed that the developed instrument was valid, having been evaluated by three experts. The material expert rated it at 95%, the assessment and evaluation expert at 88%, and the linguist at 90%. In terms of readability, the instrument scored 75%, indicating a "good" rating. The overall validity of the instrument was found to be 0.70, placing it in the high validity range, while its reliability score was 0.82, reflecting a very high level of dependability. The assessment of students' computational thinking skills in biology revealed that 25% of students scored in the low range, 28% in the medium range, and 57% in the high range. From these findings, it can be concluded that the CT test tool is both valid and appropriate for evaluating students' computational thinking skills.

Computational thinking skill is a skill that has its origins in ancient times but has gained importance today. The competences provided to individuals by computational thinking skills are also of great importance for the education system. Therefore, it is important for students to acquire and develop these skills in order to adapt to the requirements of the modern world. Based on this, in this study, the level of information processing thinking skills of higher education students was examined and the level of this skill was investigated in line with different variables. 'Computational Thinking' scale was used as a data collection tool in the study. Cronbach Alpha internal consistency coefficient of the scale. 96 was calculated as. Demographic characteristics such as gender, department, class and education level were taken into consideration. Quantitative research method was used in the study. The research was conducted with 298 participants studying in higher education. In the analysis of the data, independent t-test and ANOVA analyses were applied to determine the score differences between the groups. As a result of the study, higher education students were found to have high levels of computational thinking skills. Gender was found to be effective on computational thinking skills. As the level of education increased, it was determined that computational thinking skills increased. It was seen that the education given in different departments had an effect on computational thinking skills. Finally, it was found that there were significant changes in students' computational thinking skills as their grade level increased.

This study aims to develop a Research-Based Learning in Science, Technology, Engineering, and Mathematics (RBL-STEM) based learning material designed to improve students' computational thinking skills in solving Strong Rainbow Antimagic Coloring (SRAC) problems in river erosion. This learning material combines systematic research methods with the STEM approach, providing an immersive and applicable learning experience. The material development used the Research and Development (RnD) model to ensure its validity, effectiveness and practicality. The pilot test was conducted on Bachelor of Mathematics Education at one of the universities in Probolinggo, namely Zainul Hasan Genggong Islamic University. Data were collected through a validity sheet, learning implementation sheet, student activity observation sheet, questionnaire sheet, and pretest-posttest sheet of computational thinking skills. Furthermore, the effectiveness was analyzed using quantitative (t-test) and qualitative analysis (using Nvivo). The results showed that the use of this RBL-STEM material significantly improved students' computational thinking skills. The learning material showed 95% validity criteria, 92.5% practicality, and 90% effectiveness. Participating students demonstrated improved skills in data analysis, computer simulation, and complex problem solving related to river erosion using the SRAC concept. And, students also reported increased motivation and engagement in the learning process. The conclusion of this study is that the RBL-STEM material is effective and practical in developing students' computational thinking skills, while preparing them to face technical challenges in the real world. The wider implementation of this material is expected to support the development of a higher education curriculum that is more innovative and relevant to the needs of industry and the environment.