Interactive Multimedia Development to Improve Computational Thinking Abilities And Student Learning Motivation

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.

Computational thinking skills can help students in solving problems. Teaching materials such as student worksheets are still limited to textbooks. Physics learning can use GeoGebra to help visualise phenomena. This study aims to analyse the computational thinking ability of students through the implementation of GeoGebra integrated student worksheets on motion material on indicators of abstraction, decomposition, algorithm thinking, and generalisation. This type of research is a combination of quantitative and qualitative. Quantitative data analysis uses formula calculations to assess student worksheets. Meanwhile, qualitative data analysis uses an interactive approach by Miles and Huberman. The results showed that the students' computational thinking ability on the abstraction indicator of as many as 25 people, decomposition on as many as 20 people, and algorithmic thinking on as many as 25 people are classified as very good. This is indicated by students being able to determine important information, identify problems to be simpler, and explain steps systematically. In the generalisation indicator, students' average computational thinking ability is in a good category. In short, most students in computational thinking skills on abstraction, decomposition, and algorithm thinking are classified as very good, while the generalisation indicator is classified as good.

Background and Aim: Based on relevant policies and literature, such as higher education planning at home and abroad, policies of the Chinese Ministry of Education, educational concepts, cognitive learning theories, project-based learning methods, teaching strategies, and teaching evaluations, researchers interviewed teachers and students on the current foundation of the programming design course. This research and development aimed 1 to study the background information focusing on the course components of the foundation of programming design course to enhance students’ computational thinking ability. 2) To develop the foundation of a programming design course based on Cognitive learning theory, combined with Project-based learning to enhance students’ computational thinking ability. 3) To determine the effectiveness of implementing the foundation of programming design course based on Cognitive learning theory combined with Project-based learning. Materials and Methods: The sample of this research was 30 first-year students (1 class) majoring in Network Engineering class 1, in the academic year 2024-2025 of Zhoukou Normal University, Henan Province, China. They are derived from using a cluster random sampling method. The experimental design adopted in this research was a group posttest-only design. The research instruments from each Phase of the study were as follows: Phase I: Interview forms for teachers and students on course-related questions. Phase II: 1) Foundation of programming design course based on Cognitive learning theory combined with Project-Based Learning. 2) 12 lesson plans for the foundation of the programming design course. 3) Evaluation form of computational thinking skills. 4) Learning achievement test. 5)Satisfaction questionnaire. The data were analyzed by using mean, standard deviation, and the one-sample t-test. Results: The results of this research were as follows: 1) The researcher reviewed the related documents about the Foundation of Programming Design Course and interviewed the 4 teachers and 30 students about problems of the Foundation of Programming Design Course, and the information gathered was used to develop the course. 2) The course development in six aspects: Course principles, Course objectives, Course content, Course instructional strategies, Course media and resources, and Course evaluation. 3) After implementing through Foundation of Programming Design Course based on Cognitive Learning Theory combined with Project-Based Learning, students’ computational thinking ability (Knowledge) was higher than the determined criterion of 70% at a significance level of 0.05; students’ computational thinking ability (Skills) was higher than the determined criterion of 70% at a significance level of .05. 4) The mean scores of students’ satisfaction after implementing the Foundation of Programming Design Course based on Cognitive Learning Theory combined with Project-Based Learning was 4.838 from a possible full mark of 5, and the standard deviation was 0.176, which was statistically higher than the criterion of 70% at the .05 level of statistical significance. Conclusion: This research confirms the effectiveness of the teaching model based on Cognitive learning theory combined with Project-Based Learning to enhance students' computational thinking ability.

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 is a person's ability to present problems and their solutions through certain algorithms so that the algorithms can be reused by other people and computers to solve the same problems. This study aims to comprehensively examine students' computational thinking skill reviewed from different self-efficacy levels. This research is descriptive qualitative research. The subjects in this study were 3 seventh grade students of Bumi Cendekia Junior High School in the 2022/2023 school year who were selected based on low, medium, and high self-efficacy levels. The instruments used were test, questionnaire, and interview. Data analysis was carried out using qualitative data analysis which included data reduction, data presentation, verification, and conclusion. The results showed that students with low self-efficacy level were only able to fulfill 2 indicators of computational thinking ability, students with moderate self-efficacy level fulfilled 3 indicators of computational thinking ability. Meanwhile, students with high self-efficacy level have excellent computational thinking ability by being able to fulfill 4 indicators of computational thinking ability.

This research aims to determine the relationship between computational thinking ability and mathematical critical thinking ability of seventh-grade students at SMPN 49 Jakarta. Computational thinking ability is skills or processes in solving problems effectively, while mathematical critical thinking ability is a process of analyzing problems to make an accurate decision. This research used correlation research with research subjects consisting of 14 female students and 16 male students. The instrument in this study is a test in the form of a description, which is measured using indicators. This study used decomposition, pattern recognition, abstraction, and algorithm thinking as indicators of computational thinking ability. This study uses elementary clarification, essential support, inference, advanced clarification, strategy, and tactics as indicators of mathematical critical thinking. The outcome of this research showed a positive correlation between computational thinking ability and students’ mathematical critical thinking ability. The relationship analysis shows a simultaneous and significant relationship between computational thinking and essential mathematical thinking abilities. The correlation test results using Pearson Product Moment obtained a result of 0.897 with a coefficient of determination of 80.5%. The magnitude of the correlation indicates that the two abilities have a solid relationship. If computational thinking ability is high, then mathematical critical thinking ability is also high, and if computational thinking ability is low, then mathematical critical thinking ability is also low.

This research focuses on developing and implementing the Physics e-Module PjBL-STEM Model to improve the creative thinking skills and learning motivation of grade X students in straight-motion topics discussion. The purpose of this development research is to 1) Produce a feasible Physics e-Module PjBL-STEM Model. 2) Knowing the effectiveness of the implementation of the Physics e-Module PjBL-STEM Model in order to improve students' creative thinking skills and learning motivation. 3) Describe the students' creative thinking skills and learning motivation profile. The e-module development procedure in this study adapted the Research and Development (RD) method using the ADDIE model developed by Dick and Carry (1996). The subjects of this study were first-grade high school students who used the 2013 curriculum at a school in the city of Yogyakarta. The results of the study show that: 1) The Physics e-Module PjBL-STEM Model is feasible to use in physics learning based on the assessment of experts and practitioners. 2) Implementation of the Physics E-Module PjBL-STEM Model is effective in increasing students' creative thinking skills by 85% and students' learning motivation by 68% which is in the good category. 3) The students' creative thinking ability profile was 54.16%, while the students' learning motivation was 60.41%. Both have average and above-average values. Students with the ability to think creatively and have the motivation to learn above the average are most students who use the Physics e-Module PjBL-STEM Model in physics learning.

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.

Industry 4.0 era is characterized by the development of technology and the existence of flexible and effective data exchange. This has an impact on the emergence of new jobs that require the ability to solve problems effectively and efficiently, especially computational thinking. This Classroom Action Research aims to improve students’ computational thinking (abstraction, data collection, data analysis and algorithms) in solving problems about probability through problem-based learning integrated with differentiation learning. This research was conducted in four stages: planning, implementation, observation, and reflection. Thirty-four students of class X-E7 SMA Negeri 5 Surakarta in Indonesia were the subjects of this research. It was concluded that the application of problem-based learning model integrated with differentiated learning (content and process) significantly improves students’ computational thinking skills and promotes cognitive development through problem-solving activities. The improvement of computational thinking ability is caused by: data collection activities in the form of dice/coin simulations, abstraction activities of sample points and important information in the problem, activities to formulate solution steps (algorithms) and data analysis activities in the form of interpretation of results and calculations. Differentiated learning (content and process) plays a role in improving students’ computational thinking through ability-based scaffolding and content based on their interests and learning modalities.

As the importance of computing education for nurturing computational thinking skills is emphasized in preparation for the era of the 4th industrial revolution, computing education for non-majors is also expanding in liberal arts education at universities. In this study, a software liberal arts course based on the CT-CPS model was designed and applied to non-software majored university students, and the effect on creative problem-solving ability and learning motivation were analyzed. The CT-CPS (computational thinking-based creative problem solving) model is an instructional model devised by fusing each element of computational thinking ability to the creative problem-solving stages. Creative problem-solving ability test paper and learning motivation test paper were used as test tools. Moreover, quantitative analysis through independent sample t-test and paired sample t-test and qualitative analysis through subjective responses were conducted. As a result of the study, it was verified that the software class applied with the CT-CPS model had a statistically significant effect on the creative problem-solving ability and learning motivation of non-software majors. In particular, compared to the control group, the experimental group showed significant changes in the motivational elements among the sub-factors of creative problem-solving ability and the self-efficacy factor among the sub-factors of learning motivation. In addition, it was confirmed through qualitative analysis that the software class to which the CT-CPS model was applied helped develop the problem-solving ability and learning motivation based on computational thinking through the process of discovering and solving problems on their own in real life.

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>

Melatih kemampuan berpikir komputasional mahasiswa membuka peluang untuk lebih menguasi konsep, menganalisis permasalahan, dan membangun solusi dunia nyata. Tujuan penelitian adalah menganalisis kemampuan berpikir komputational mahasiswa Pendidikan Ilmu Komputer berupa kemampuan abstraksi, dekomposisi, berpikir algoritmik, dan generalisasi. Metode penelitian yaitu studi kasus dengan pendekatan kualitatif deskriptif. Pembelajaran dilakukan kepada 40 mahasiswa semester 1 (satu) secara kolaboratif dalam penyelesaian masalah luas daerah dengan pendekatan limit. Pada akhir pembelajaran mahasiswa diberikan soal tes kemampuan berpikir komputasional mahasiswa. Jawaban tes setiap mahasiswa dianalisis dari segi sisi fungsi mental yang muncul untuk mengetahui karakteristik akusisi kemampuan penyelesaian masalah. Pada penelitian yang telah dilakukan mahasiswa dikategorikan dalam kelompok novice, advanced beginner, competent, proficient, dan expert berdasarkan karakter penyelesaian masalahnya. Pada umumnya setiap mahasiswa telah memiliki kemampuan berpikir algoritmik. Sebagian besar mahasiswa (kecuali kategori novice) juga telah mampu mengabstraksi dan mendekomposisi permasalahan. Sedangkan kemampuan pengenalan pola baru terlihat pada mahasiswa dengan kategori competent, proficient, dan expert. Training students' computational thinking ability provides opportunities to comprehend concepts, analyse problems, and build solutions in real-life contexts. The purpose of the study was to analyse the computational thinking abilities of Computer Science Education students, i.e., abstraction, decomposition, algorithmic thinking, and generalization abilities. The research method used was a case study with a descriptive qualitative approach. The learning process was conducted by 40 students for semester 1 (one) semester collaboratively in solving area problems using the limit approach. At the end of the lesson, the students were tested through students' computational thinking abilities. Each student's answers were analyzed in terms of the mental functions that emerged to determine the characteristics of the acquisition of problem-solving ability. In this study, the students were categorized into groups of novices, advanced beginner, competent, professional, and expert based on the natures of their problem solving. In general, every student had the ability to think algorithmically. Most students (except the novice category) were able to abstract and unravel the problems. Meanwhile, the ability to recognize new patterns were demonstrated by the students in the competent, professional, and expert categories.

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 is a theory born in computer science that applies computational principles to solve a problem. It is a new concern in the PISA 2021 mathematical assessment to accommodate human resources needs that can compete in the 21st-century digitalization era. This study aims to develop a learning tool called student worksheet (LKPD) that integrates indicators of computational thinking skills into the material ratio. The method used is Research and Development (R&D), with the subject of research being 32 students in one Junior High School in Ciamis Regency. The data collection technique is done by observation, interview, and questionnaire given to material experts, media experts, and students. The data were analyzed quantitatively using descriptive product validity and practicality scores. The results showed that the assessment of material experts, including aspects of legality and morality, the feasibility of content, the feasibility of presentation, and aspects of computational thinking, received a level of validity of 99%, so it is included in the category of very valid. Likewise, the assessment of media experts covering anatomy, graphics, and use of language was declared very valid, with a validity rate of 82 %. The product's practicality gets a very practical category with an average score of 86% covering material aspects, use of language, interest, and aspects of computational thinking. The products that have been developed are considered valid and practical for use as educational resources for learning ratios and enhancing computational thinking ability.