Adaption of the Computational Thinking Test into Turkish

In recent years, computational thinking (CT) skills have been globally recognized as a 21st-century skill that must be developed for future generations. However, the lack of validated CT assessments would be a major impediment in the efforts to incorporate CT into the school curriculum. This study is intended to validate the Computational Thinking Test (CTt) using the Rasch model by identifying whether the data fit the Rasch model measurement, determining the CT abilities among a small sample of Singapore secondary students through the test, and examining the presence of test items that functioned differently for gender and grade level of the students. In this study, 153 upper secondary school students from Grade 9 and Grade 10 were involved in a test that required them to do the CTt which comprises 28 test items. The performance of the students in CTt was utilized as quantitative data in this study and was analyzed using the Rasch model. The findings revealed that the data fit the Rasch model measurement. The majority of the male students and ninth-graders had a high level of CT abilities, while most of the female students and tenth-graders had a moderate level of CT abilities. Hence, the male students and ninth-graders performed better than the female students and tenth-graders. Four items functioned differently between male and female students where one gender had a better chance to get the correct answer in these four items compared to the other gender. Only one test item was functioning differently for Grade 9 and Grade 10. This means that the students of one grade level were more likely to obtain the correct answer in this item than the students in the other grade level. This study hopes to contribute to the literature in the area of CT assessments by providing a reference case for scholars and researchers in assessing CT abilities among the students.

The purpose of this study is (1) to describe the characteristics of a good mobile learning application to improve computational thinking and learning independence of high school students. (2) to produce a mobile learning application that is oriented towards computational thinking skills and student learning independence with good quality. The quality of the development results is determined based on Nieveen's criteria, namely valid, practical, and effective. This study is a research and development (R&D) that uses the Borg & Gall development model with 8 development steps, namely preliminary study, planning, initial product development, small group trials, main product revision, limited scale trials, operational product revisions and large-scale trials. The subjects in this study were 36 students from one class at SMA Negeri 1 Gamping, Sleman Regency. The instrument used to measure the validity of the mobile learning application is the expert validation sheet. The instrument to measure the practicality of the mobile learning application is the student response questionnaire. The instrument to measure the effectiveness of the application is the computational thinking test and the student learning independence questionnaire. Validity and practicality data analysis was conducted by converting quantitative data into qualitative form in the form of four standard scale values, while effectiveness data analysis based on test and questionnaire results was conducted using paired sample t-test. The results of the study showed that (1) Mobile learning applications have the characteristics of being easy to apply, flexible to time, lightweight and easy to carry anywhere and also implementing each computational thinking indicator in each stage of the material. (2) The results of expert validation showed that the developed mobile learning application met the valid criteria as seen by the Aiken's validity test score for media experts of 0.83 and 0.68 for material experts. The practicality of the mobile learning application is included in the very good category as seen from the average results with an average percentage of student responses of 87.17%. The effectiveness of the computational thinking test obtained a t-value of 47.22 greater than t (35,0.05) with a score of 1.69, the effectiveness of the learning independence test based on the t test obtained a t-value of 4.85 greater than t (35,0.05) with a score of 1.69. Based on the results obtained, it can be concluded that the developed mobile learning application meets the criteria of validity, practicality and effectiveness.

The purpose of the current study was to explore the effect of modality (constructionist mBlock, Scratch, and Python interventions) on six-grade students’ computational thinking, programming attitude, and achievement. The pre-test and post-test quasi-experimental design was used to explore the research questions. The study group consisted of 105 six grade students from three different classes. A constructionist learning environment was formed for Scratch, mBlock, and Python groups. All groups were given 8 week-instruction. Instruction included two forty-minute sessions each week. The data were collected through the programming achievement test, computational thinking test, and computer programming attitude scale. The results of the study showed that mBlock group outperformed the Scratch and Python groups with respect to computer programming attitude. Students who attended mBlock and Scratch groups had higher levels of programming achievement than those of the students who attended the Python group. No significant differences with respect to computational thinking were observed between the groups. This study has implications for educators who are teaching computational thinking and programming. Further research was recommended to explore the effect of modality.

Computational Thinking (CT) is an essential skill in digital society. With the growing momentum in integrating CT into K-12 education, a higher need can be seen in developing proper assessment tools to measure what students have learned about CT. Although numerous attempts have been made to design CT assessment tools, there is a scarcity of well-validated tests for summative assessment aimed at lower primary students. To bridge this gap, we designed the Computational Thinking Test for Lower Primacy (CTt-LP), targeting students aged 6–8. This study presents the test design, content validation, and pilot testing. For test design, Evidence-Centered Design (ECD) was applied, and four constructs were selected. A total of 30 items were designed, after which content validation was performed via expert judgement and cognitive interviews with students. Revisions were made based on the validation results. The pilot testing was conducted in a public primary school in northern China, with 72 participants from Grade 2. Results indicate that the test is balanced regarding the difficulty level for the target group. Item analysis was conducted for each item, based on which decisions about the refinement of the test were made. Directions for future research are discussed.

This study aimed to develop the Computational Thinking Test for Elementary School Students (CTT-ES) to assess young children’s CT competencies in non-programming contexts and also examine the relationship between CT competencies and CT dispositions. A survey including a pool of CTT-ES candidate items and the Computational Thinking Scale (CTS) was administered to 631 elementary school students. Rasch model of the Item Response Theory and the discrimination analysis of the Classical Testing Theory were conducted for item analyses. Pearson’s correlation analyses and hierarchical multiple regression analyses were used to examine the relationships between CTT-ES and CTS scores. The results showed that the final CTT-ES including 16 items had a good fitness, discrimination, and reliability to evaluate elementary students’ domain-general CT competencies. The convergent validity of CTT-ES was confirmed by its significant correlations with the CTS scores. The significant regression model not only showed students’ CT competencies can be predicted by their CT dispositions but also supported The Developmental Model of CT. This study provided a valid and reliable tool for assessing young children’s CT abilities. It also furthered our understanding about the developmental orders of CT abilities and contributed to the theoretical construction of CT.

<p>This research is motivated by the low level of students' computational thinking skills in mathematics learning, particularly in the topic of function composition. To address this issue, a Scratch-based learning media was developed with the aim of helping students understand the concept of function composition while also enhancing their computational thinking skills. The aim of this study is to produce <em>Komfun CT</em> learning media based on Scratch for function composition material. The research was conducted in the 2024/2025 academic year using the Research & Development (R&D) method based on the ADDIE model, which consists of five stages: Analysis, Design, Development, Implementation, and Evaluation. The quality of the developed media must meet the criteria of validity, practicality, and effectiveness. The instruments used in this study include observation sheets, interview guidelines, questionnaires, and tests. The observation sheets were used to obtain information about mathematics learning activities conducted by the teacher at school. The interview guidelines were used with students to collect qualitative data regarding the practicality of the developed media. The questionnaires consisted of a student response questionnaire, a material expert questionnaire, and a media expert questionnaire. Finally, the computational thinking test, which included a pre-test and post-test, was used to assess students’ computational thinking skills before and after using the media.The results showed that: (1) the media developed using the ADDIE model successfully produced <em>Komfun CT</em> learning media based on Scratch; (2) the <em>Komfun CT</em> learning media was declared feasible based on expert validation (material and media), covering aspects of validity, practicality, and effectiveness; (3) the developed media met the validity criteria with an average percentage of 93.86%. The practicality test results showed an average percentage of 83.60% from student responses. The effectiveness test based on N-Gain analysis showed an average gain score of 85.43%, indicating that the media is effective in enhancing students’ Computational Thinking.</p>

In modern society technology is widely used and, with the digitization of many services, this is an upward trend. Therefore, computational thinking (CT) is an increasingly important concept; an aspect that is being reflected on educational policies and the extracurricular offer of different countries. This study aims to look at the efficacy of private after-school extracurricular robotics activities, controlling fluid intelligence (Gf), a determining aspect in solving novel problems. A sample of 112 fifth-grade Spanish students was chosen, who completed two tests, the computational thinking test (CTt) (Román-González, 2016) and the KBIT fluid intelligence subtest (Kaufman, 1990). The results showed a great influence of Gf on the prediction of CT and significant differences between the students that had not attended after-school extracurricular classes and those that had attended for two or more years. Thus, this study substantiates the effectiveness of private extracurricular classes in promoting CT in the long term. Given the importance of CT nowadays, legislators should consider to include CT in compulsory education because private extracurricular classes could promote inequity.

This study investigated if using Dr. Scratch as a formative feedback tool would accelerate students' Computational Thinking (CT). Forty-one 4th-6th grade students participated in a 1-hour/week Scratch workshop for nine weeks. We measured pre- and posttest results of the computational thinking test (CTt) between control (n = 18) and treatment groups (n = 23) using three methods: propensity score matching (treatment = .575; control = .607; p = .696), information maximum likelihood technique (treatment effect = -.09; p = .006), and multiple linear regression. Both groups demonstrated significantly increased posttest scores over their pretest (treatment = +8.31%; control = +5.43%), showing that learning to code can increase computational thinking over a 2-month period. In this chapter, we discuss the implications of using Dr. Scratch as a formative feedback tool the possibilities of further research on the use of automatic feedback tools in teaching elementary computational thinking.

Robotics is needed as education keeps up with challenges students are facing in a technological environment. A long-term research project focuses on developing a feasible robotics-based learning environment that enables primary school teachers to introduce computer science education. This paper shows educational robotics combining storytelling to promote computational thinking through the method of Tell, Draw, and Code. The study was conducted via pre–post test, using the Beginners Computational Thinking test (BCTt), with third and fourth graders (N = 40) to determine if the integration of robotics-based storytelling activities enhances computational thinking skills. Results show that an increase in computational thinking is evident after the intervention is implemented. The approach of combining stories, texts, and literature with educational robotics seems to be a promising concept to equip students with the required skills.

Computational Thinking (CT) has emerged in recent years as a thematic trend in education in many countries. initiatives have been developed for its inclusion in school curricula. There are many pedagogical strategies to promote the development of elementary school students’ CT skills and knowledge. Unplugged learning tasks, block-based programming projects, and educational robotics are 3 of the most used strategies. This paper aimed to analyze the effect of Scratch-based activities, developed during one scholar year, on the computational thinking skills developed and concepts achieved by 4th-grade students. The study involved 189 students from two school clusters organized into an experimental group and a control group. To assess students’ computational knowledge, the Beginners Computational Thinking Test developed by Several Zapata-Cáceres et al. (2020) was used. The results indicate statistically significant differences between the groups, in which students in the experimental group (who performed activities with scratch) scored higher on the test than students in the control group (who did not use Scratch).

Many national curricula have incorporated computational thinking (CT) into compulsory education. Teacher ability to deliver the revised curriculum determines whether these new skills can be successfully integrated into teaching. Therefore, it is crucial to examine teacher readiness. This study measured Swedish K-9 teacher CT skills through a CT test validated by an expert review panel and a principal component analysis. Additionally, we engaged statistical analyses to examine the relationship between the teachers' background and their CT test scores, as well as their self-reported ability to teach CT. The result demonstrated the teachers' proficiency in different types of CT skills. Another finding revealed that the type of programming language mastered by teachers was associated with both their CT test score and self-reported ability to teach CT. This CT test can support teachers to identify specific areas for professional development and may facilitate the school management to plan teachers' competence training strategically.

Promoting computational thinking is one of the top priorities in CS education as well as in other STEM and non-STEM disciplines. Our innovative NSF-funded IC2Think project blends computational thinking with creative thinking so that students leverage their creative thinking skills to “unlock” their understanding of computational thinking. In Fall 2012, we deployed creative exercises designed to engage Epstein's creative competencies (Surrounding, Capturing, Challenging and Broadening) in introductory level CS courses targeting four different groups (CS, engineering, combined CS/physical sciences, and humanities majors). Students combined hands-on problem solving with guided analysis and reflection to connect their creative activities to CS topics such as conditionals and arrays and to real-world CS applications. Evaluation results (approximately 150 students) found that creative thinking exercise completion had a linear “dosage” effect. As students completed more exercises [0/1 - 4], they increased their long-term retention [a computational thinking test], F(3, 98) = 4.76, p =.004, partial Eta2 = .127 and course grades, F(3, 109) = 4.32, p =.006, partial Eta2 = .106. These findings support our belief that the addition of creative thinking exercises to CSCE courses improves the learning of computational knowledge and skills.

<p>The recent advancement in computational thinking (CT) research has reported numerous learning benefits to school-age children. The long-standing perceived difficulty of computer programming has challenged the acquisition of CT skills from programming education. Several block-based programming environments (BBPEs) have been developed to reduce this difficulty and enhance active engagement in computational-related activities. Although numerous studies have examined students’ level of interactions during block-based programming modality (BPM) activities, a major gap in the literature is the paucity of research evidence reporting the association between these interactions and CT. This study, therefore, investigates the association between interaction patterns during BPM activities and CT skills. The present study employed a longitudinal approach where the same participants were observed over eight weeks. Thirty-five, second-year-level computer science and computer education students (mean age: 19.8; male = 23, female = 12) from a research university in Nigeria were recruited. Their computational activities over the study periods were video-recorded. The participants’ CT skills were collected using the computational thinking test and the computational thinking scale. Findings indicate four interaction patterns: learner–learner, learner–content, learner–teacher, and learner–distractor. Learner–learner and learner–content were prevalent. The interaction patterns significantly predict CT skills although significant differences exist across gender, cognitive load, spatial ability, and programming proficiency. The research has provided opportunities for educators to integrate BBPEs in learning programming and CT concepts. Although such integration is likely to occur with the help of strong educational policies, teachers are encouraged to cultivate the spirit of collaboration in students during programming activities.</p>

This study aims to describe the Computational Thinking Skill (CTS) profile of prospective science teacher students in solving problems with dynamic electricity material. This study uses a descriptive method with a quantitative approach. The data collection technique in this study used a CTS essay test of 10 questions and a multiple-choice computational thinking test, which were then analyzed using quantitative descriptive analysis. Based on the results of the study, it is known that the level of CTS ability of prospective science teacher students is 43.74% so it is categorized as sufficient. The highest level that students can achieve is 53.15%, which is an indicator of pattern recognition ability, and the lowest level is 32.28%, which indicates abstraction ability. Meanwhile for other indicators, namely algorithms and decomposition, the results obtained were 40.34% and 49.19% respectively.

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.