Characterizing Computational Thinking for the Learning of Tertiary Educational Programs

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.

<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>

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.

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.

This study attempts to enhance high school learners' computational thinking and mathematical resilience skills. This study employs quantitative approaches with a quasi-experimental research design, and the type of research is Non-Equivalent Group Design. The tools used in this study were computational thinking skills tests and mathematical resilience questionnaires. From the results of the survey conducted, it is known that: 1) the Project Learning model accompanied by GeoGebra significantly improves computational thinking skills, and Project-Based Learning model has moderate improvement; 2) computational thinking skills of high school students who were taught through Project-Based Learning model aided by GeoGebra improved significantly compared to those taught with the Project-Based Learning model; 3) Project-Based Learning model aided by GeoGebra has a positive effect on the mathematical resilience of high school students, but only to a moderate extent.

Computational thinking skill is an important skill individuals should acquire to meet the requirements of the digital age. The aim of the study is to predict the computational thinking skills of middle school students through ANFIS approach, which is an adaptive neural network-based fuzzy logic. Students' computational thinking skill scores were predicted by creating a model based on grade level and academic achievement variables. Grade level and academic achievement served as the model's input variables, and computational thinking skill scores served as the model's output variable. Data were collected using personal information form and computational thinking scale. A comparison was made between students' real and artificial computational thinking skill scores using statistical methods. In the study, a strong and favorable association between the artificial scores produced using the ANFIS technique and the actual scores was discovered. Furthermore, there was no statistically significant difference between the real and artificial scores for computational thinking skills. These results indicate that the ANFIS approach is a suitable alternative analysis method for predicting students' computational thinking skills. The study provides a good example in the field of education where artificial intelligence can be used to predict students' educational characteristics.

This study compares computational thinking skills evidenced by two groups of students in two different secondary schools: one group per school was studying a qualification in Computer Science. The aim was to establish which elements of computational thinking were more prevalent in students studying Computer Science to a higher level. This in turn would evidence those elements likely to be present from their earlier computing education or through their complementary studies in Science or Mathematics, which all students also studied. Understanding this difference was important to identify any increased competence in computational thinking that was present in the Computer Science groups. Artefact-based interviews were carried out using questions and practical computing problems designed to elicit and demonstrate the students’ computational thinking skills based on the Brennan and Resnick (2016) model of computational concepts, practices and perspectives. Analysis of students’ responses showed surprisingly little difference between the computational thinking practices of the two groups in relation to abstraction, decomposition, evaluation, generalisation/reusing, logical reasoning and debugging/testing. The study concludes that general computational thinking skills can be developed either at a lower level of study or in cognate curriculum areas, leaving computer science as the rightful locus of computational thinking for automation.

The graphics calculator (GC) is a hand-held technology. With it, students visualize and understand concepts in mathematics and science better. It also allows them to make real-world connections, binding together advanced graphing functionality and conceptual science, technology, engineering, arts and mathematics (STEAM). As they gain a deeper understanding of abstract concepts, they acquire creative and critical thinking and problem- solving skills they need to reach greater academic successes. In learning, GC plays several roles in increasing students’ computational thinking and procedural skills. Despite being a learning tool that satisfies science and mathematics curriculum needs, the calculator often has been used as an add-on to traditional teaching methodology rather than central and in more integrated ways. This study looks into the potential of developing computational thinking skills using GC technology. The data of the study was obtained from secondary sources through a systematic review method. The study showed that GC seems to be effective tools to practice STEAM education as well as to develop students’ computational thinking through analysing and decompose real problem as well as engaging in the abstraction process and developing an algorithm using coding. The findings provides justifications on the impact of GC in developing computational thinking skills thereby maximizing the pedagogical benefits to students.

Computational thinking has become a crucial skill for students because it gives them the tools to solve complicated issues using organized methods. Implementing Problem-based learning and Design-based learning in science learning has significantly enhanced students' skills. This research aims to ascertain which of the two models is better for facilitating computational thinking skills among middle school students in science learning. The study used a sample of 69 middle school students selected through random sampling. This research employs a quasi-experimental, multi-group, post-test-only design. The instrument utilized in this research is a computational thinking skills test comprising five questions. The data were analyzed using one-way ANOVA to test the hypotheses. Tukey test results indicate that the mean difference score between the PBL and DBL groups is 1.2609, with a significance value greater than 0.05. The study confirms that Problem-based learning is more effective than Design-based learning in facilitating students' computational thinking skills. However, the difference between the two is not particularly noteworthy. PBL and DBL represent viable pedagogical approaches that can enhance middle school students' computational thinking skills in science learning. Keywords: problem-based learning, design-based learning, computational thinking skill. DOI: http://dx.doi.org/10.23960/jpmipa/v25i3.pp1214-1223

This study aims to provide an overview of the computational mathematical thinking abilities of male and female students in solving mathematical problems and the aspects (abstraction, decomposition, algorithmic thinking, and generalization) that influence these differences. This study uses a qualitative method with a case study approach in a junior high school in Jakarta for the academic year 2023/2024. The participants in this study are 36 students. Data were collected through written examinations and interviews and analyzed using the triangulation technique. The results of the study showed different patterns of computational thinking skills between male and female students. Male students excel in decomposition and algorithmic thinking but are weak in abstraction and generalization. Female students excel in abstraction and decomposition but are weak in algorithmic thinking and generalization. Both male and female students master the context of decomposition for computational thinking skills but lack mastery in the context of generalization. In conclusion, gender differences influence specific aspects of computational thinking skills, indicating the need for tailored educational strategies to address these differences.

"This research was aimed to 1) develop an inquiry-based learning management plan integrated with an online website platform to promote computational thinking skills among Grade 3 students 2) to evaluate the effectiveness of the online website platform 3) to compare students' academic achievement before and after the learning activities 4) to compare students' computational thinking skills before and after the learning activities and 5) to study students' satisfaction with the learning management approach. The participants were 26 Grade 3 students from Suraolakkorn School, Nonthaburi Province. The online platform was designed with learning activities based on the 5Es instructional model (Engage, Explore, Explain, Elaborate, Evaluate), incorporating computational thinking problem scenarios aligned with each learning stage. Research instruments included an achievement test, computational thinking skills assessment, and satisfaction questionnaire, all developed following the ADDIE model. The results revealed that: 1) the developed learning management plan was rated at a very good quality level by three experts 2) the effectiveness of the online learning was 80.10/81.03 3) students’ post-learning academic achievement significantly improved compared to pre-learning at the .05 significance level 4) post-learning computational thinking skills increased by over 70% and 5) students’ satisfaction with the learning experience was rated at a high level.These results demonstrate integrating computational thinking problem scenarios within the 5E inquiry-based learning framework and an online platform effectively enhances computational thinking skills and academic achievement among primary school students. "

This paper investigates the relationship between the use of robotics in learning towards self-efficacy and computational thinking skills. This paper also examines whether there is a relationship between computational thinking skills and self-efficacy. This paper employed a systematic literature review method by examining forty articles drawn from ‘computational thinking’, ‘self-efficacy’ and ‘educational robotics’ keywords in the literature. The majority of research indicates that the use of robotics in learning facilitates the development of computational thinking skills as well as learners’ self-efficacy. The paper advocates that future research should examine the extent of computational thinking skills and self-efficacy influence on student behavior.

Mathematical computational thinking skills are essential in mathematics learning, particularly in training systematic problem-solving abilities. However, the limited availability of interactive and effective learning media has remained a significant obstacle to developing these skills. This study aims to develop learning media based on Articulate Storyline 3, which is designed to enhance students' mathematical computational thinking skills. The method employed in this research is Research and Development (R&D) using the ADDIE model, which includes the stages of analysis, design, development, implementation, and evaluation. The subjects of the study were high school students selected through purposive sampling. The research instruments included expert validation questionnaires, user response questionnaires, and tests to assess computational thinking skills. The study results have shown that the developed learning media has achieved a very high level of validity according to evaluations from both material and media experts. Additionally, user responses have demonstrated high satisfaction with the interactivity and ease of media use. Field trials have revealed a significant increase in students' mathematical computational thinking skills after using the learning media. Based on these findings, learning media based on Articulate Storyline 3 has effectively improved mathematical computational thinking skills. These results are expected to contribute positively to more interactive and practical mathematics education innovations.

The aim of this study was to investigate psychometric related issues of the TechCheck-K instrument for assessing the computational thinking skills of Turkish kindergarteners as well as explore whether age in month and gender made a significant difference in their general and domain-specific computational thinking skills. For this purpose, data were collected from 352 kindergarten-aged children attending public kindergartens in Türkiye. Item response and comparative analysis were used to analyse collected data. Item response results indicated that the TechCheck-K instrument had good psychometric properties, was suitable for use with Turkish kindergarten children and was more powerful in discriminating kindergarten children with moderate and low ability levels. It was also shown in the results that there was a significant difference between three age groups in months regarding participants’ general computational thinking skills. Significant differences in the general computational thinking skills were also observed within boys and girls according to their age in month. Specifically, boys and girls in the older month groups had statistically significantly higher mean scores. There was a significant difference in the domain-specific powerful ideas of computational thinking skills with respect to age in month. Finally, implications and directions for future research were discussed.

The PISA data results show that computational thinking abilities are still lacking. Computational thinking ability is influenced by gender. This research aims to analyze patterns of computational thinking skills of prospective elementary school teachers based on gender at 8 universities in Indonesia. In this research, the components of computational thinking skills analyzed are abstraction, algorithmic, decomposition, and pattern recognition. This research is a mix method research with research subjects as many as 234 prospective elementary school teachers at 8 higher educational institutions. The instruments used were test and interviews. The data analysis technique used is a quantitative data analysis technique using SEM PLS and for qualitative data analysis using miles and Huberman. The research results show that computational thinking skills are still low on the decomposition and pattern recognition components. Based on the SEM PLS test results, it shows that computational thinking abilities are related to gender. In general, the computational thinking ability of female students is slightly higher in all sub-indicators than men and there are differences in the pattern of computational thinking ability between male and female elementary school teacher prospective. The ability of prospective female elementary school teachers to answer in more detail and more structured, while the answers of male prospective teachers are shorter and less comprehensive. Recommendations for developing computational thinking skills by developing problem-based learning, contextual project-based learning and STEAM based learning.