Development of Figma Educational Game Based on Mathematics Computational Thinking Ability for Vocational Students

This research aims to find out about students' computational thinking abilities in solving algebraic problems in cultural contests. This research is qualitative research carried out at Yogyakarta Middle School. The participants involved were 31 students in the even semester of grade 7. The data sources in this research were the results of students' computational thinking tests, interviews with students who were selected based on their communication skills and the results of test answers. Data instrument testing uses validity and reliability tests with data validity using triangulation techniques. Data analysis in this study used the pullulation technique between student test results and student interview results, then data reduction, data categorization, power display and conclusion drawing were carried out. The results of this research are that students in the high category can complete all indicators of computational thinking and problem-solving abilities. Students in the medium category can only complete two indicators of computational thinking and problem-solving abilities. Students in the low category have not been able to complete all indicators of computational thinking and problem-solving abilities. The study reveals a significant variance in the computational thinking abilities among junior high school students in Piyungan Development class VIII when solving algebra problems within a cultural context. High-achieving students demonstrated proficiency across all indicators of computational thinking, effectively navigating through various stages from abstraction to solution verification. In contrast, students categorized as moderate showed partial success, managing only a subset of the indicators, while struggling with the more complex stages of problem decomposition and implementation. Meanwhile, students classified in the low category were unable to achieve any indicators of computational thinking and problem-solving skills. This indicates a clear need for targeted educational interventions to enhance computational thinking among students, particularly those who are struggling, to ensure all students can develop the necessary skills to solve problems effectively.

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.

Introduction: Prospective teachers' computational and creative thinking skills show quite low results because classroom learning is less innovative. This requires the use of innovative models. This study was conducted to determine the effectiveness of the Hybrid Learning Microsite Project STEAMER in improving prospective elementary school teachers' Computational and Creative Thinking Skills.Methods: The study subjects were prospective elementary school teachers from 10 Educational Personnel Education Institutions in six provinces. This method of study used a mixed approach. Data were collected through tests, interviews, and observations. Data were analyzed quantitatively and qualitatively. Quantitative data were analyzed using Multivariate statistics, SEM LISREL 8.80, while Miles and Huberman data analysis techniques were used to analyze qualitative data.Results: This study shown that the average post-test score in the experimental class increased by 69.95 and in the control class by 55.65. This study concludes that the application of the learning model has implications for the variables of creative and computational thinking abilities by 29.6% and 10.6%.Conclusions: The implementation of the STEAMER Hybrid Learning Project has influenced students' computational and creative thinking abilities through a series of model stages, such as reflection, conducting research, finding strategies, implementing design results, and communicating the results of the developed project.

This study aims explicitly to look at differences in computational thinking and mathematical ability of students who received learning with augmented reality media based on gender. Background Problems: This research is motivated by students’ low mathematical Computational Thinking (CT) ability and the rapid development of information technology in the digital era. Augmented Reality is a technology that combines three-dimensional virtual objects into a natural environment and then projects these virtual objects in real-time. The research subjects were 30 class VII students of SMPN 34 Pekanbaru in the 2022/2023 school year, randomly selected. This research was conducted on flat geometric materials, especially triangles and quadrilaterals. The data collection methods used a test of mathematical computational thinking ability. Parametric statistical tests processed test results data. The results showed differences in computational thinking and mathematical ability of students who received learning using augmented reality media based on gender. Male students’ computational thinking and mathematical ability are better than female students.

The background of this research is that the rapid pace of technology today creates new abilities, namely computational thinking ability to be improved. In addition, Indonesian culture also needs to be introduced to students today. This study aims to improve students' computational thinking ability using Scratch with the concept of Indonesian culture and Math-trail in mathematics learning. The subject of this research is class VIII students of Eka Sakti Junior High School, Banyumanik District, Semarang City with a total of 32 students with details of 14 girls 18 boys. Students' computational thinking ability is still low because there is no learning media that supports the improvement of students' computational thinking ability. This research uses quantitative methods. The suggestion from this research is the need to conduct further research that is more in depth to find out what factors make the increase.

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.

The purpose of this study was to determine differences in the computational thinking skills of first students of the Department of Informatics Engineering based on genders. This study uses quasi-experimental methods. The subjects in this study were semester two students of the Department of Informatics Engineering in 2019/2020. The research subjects were 34 male students and 23 female students. Methods of data collection using tests and observations. The research instrument used was a computational thinking ability test and an observation sheet. Data analysis using a t-test (independent sample) with analysis prerequisites in normality and homogeneity tests. Test analysis utilizing the help of IBM SPSS Statistics 20. The study of research data shows that there are significant differences between the computational thinking ability of male and female students. The average results of the computational thinking ability test showed that male students' computational thinking ability is better than the female students' computational thinking ability. The male and female students' computational thinking skills reach the generalization stage, where male students can find solutions directly through easy-to-understand and straightforward ideas. Meanwhile, female students can explain the flow and concepts used to solve problems. AbstrakTujuan penelitian ini adalah untuk mengetahui perbedaan kemampuan berpikir komputasi mahasiswa semester awal jurusan Teknik Informatika berdasarkan jenis kelamin. Penelitian ini menggunakan metode eksperimen semu. Subjek dalam penelitian ini adalah mahasiswa semester 2 jurusan Teknik Informatika tahun ajaran 2019/2020. Subjek penelitian adalah 34 siswa laki-laki dan 23 siswa perempuan. Metode pengumpulan data menggunakan tes dan observasi. Instrumen penelitian yang digunakan adalah tes kemampuan berpikir komputasi dan lembar observasi. Analisis data menggunakan uji-t dengan prasyarat analisis berupa uji normalitas dan homogenitas. Uji analisis menggunakan bantuan IBM SPSS Statistics 20. Hasil penelitian dapat disimpulkan bahwa terdapat perbedaan yang signifikan antara kemampuan berpikir komputasi siswa laki-laki dan perempuan. Hasil rata-rata tes kemampuan berpikir komputasi diperoleh bahwa kemampuan berpikir komputasi siswa laki-laki lebih baik daripada kemampuan berpikir komputasi siswa perempuan. Kemampuan berpikir komputasi mahasiswa putra dan putri mencapai tahap generalisasi, dimana mahasiswa putra mampu mencari penyelesaian secara langsung melalui ide sederhana dan mudah dipahami. Sedangkan mahasiswa putri mampu menjelaskan alur dan konsep yang digunakan untuk menyelesaikan masalah.

Computational thinking ability is a very important, and it is a basic necessary skill for future talents. This paper describes the shortcomings of the current education of cultivating students’ computational thinking ability, analyzes the needs of cultivating students’ innovative ways of computational thinking in the information age, and expounds the necessity of innovative education and teaching. In this paper, the project driven teaching mode and the teaching method of computational thinking cultivation are proposed. The Small Private Online Course (SPOC) teaching method is used in the teaching practice, which is a kind of information technology method. Combined with project driven and SPOC teaching methods, the students' computational thinking ability is further cultivated. In the teaching practice, the information technology and project driven learning are made full use, which are two key factors in the information age, so the students’ computational thinking ability has been greatly improved, and the teaching effect is obvious.

This research is motivated by the habits we often encounter in learning, especially in mathematics. Each student has different computational thinking abilities. Computational thinking ability is a thinking ability that supports problem-solving solutions. Computational thinking components include decomposition, pattern recognition, abstraction, and algorithm design. This research aims to: 1) Describe the computational thinking abilities of students with high self-regulated learning in solving trigonometry problems, 2) Describe the computational thinking abilities of students with moderate self-regulated learning in solving trigonometry problems, 3) Describe the computational thinking abilities of students with low self-regulated learning in solving trigonometry problems. This research used a qualitative approach with a case study type of research. This research was conducted at SMKN 2 Tulungagung which was attended by all students of class XI TKRO 3, totaling 32 students. Of the 32 students, 6 students will be selected as subjects who are classified based on the level of self-regulated learning. Data collection techniques used are observation, tests, interviews, and documentation. Data analysis techniques were carried out through the stages of data collection, data presentation, and conclusion. The results of this research indicate that: 1) students with high self-regulated learning can fulfill 3-4 indicators of computational thinking skills in solving trigonometry problems, 2) students with moderate self-regulated learning can fulfill 2-3 indicators of computational thinking skills in solving trigonometry problems, 3) and students with low self-regulated learning can fulfill 0-1 indicators of computational thinking skills in solving trigonometry problems

Education is a crucial key in shaping individuals who are capable of competing and actively participating in an increasingly complex and dynamic environment. However, education today often remains focused on teacher-centered approaches, which can hinder students' problem-solving abilities, including computational thinking skills. This research aims to implement the Problem-Based Learning (PBL) model with the assistance of interactive multimedia in database learning to enhance students' Computational Thinking (CT) abilities. The research method used is the Research and Development (RD) method with the ADDIE multimedia development model and a One Group Pretest post-test research design. The research findings indicate that: 1) The developed multimedia received expert validation with a validity level of 93.55% and categorized as "Very Good". 2) The implementation of the PBL model in database learning has a positive effect on improving students' computational thinking abilities, with an average n-gain of 0.478 categorized as "Moderate". 3) The average student response to the interactive multimedia is 93.45% with the category "Very Good".

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

In the era of rapid development of information technology, deep learning, as the core driving force in the field of artificial intelligence, is leading profound changes in the education industry. Computational thinking, as a key ability to solve complex problems and design innovative systems, has become one of the important indicators to measure the comprehensive quality of college students. This paper focuses on the cultivation of college students’ computational thinking in the context of deep learning, and explores through empirical research how to effectively improve college students’ computational thinking ability in the current technological environment, as well as its impact and promotion on the cultivation of college students’ computational thinking. By designing and implementing an empirical study targeting students majoring in Electronic Information Engineering at Nanchang Normal University, this study aims to explore the actual effects of deep learning-based teaching models in enhancing college students’ computational thinking abilities. Students majoring in Electronic Information Engineering at Nanchang Normal University were selected as the research subjects. A questionnaire survey was conducted, which constructed nine dimensions including decomposition ability, abstract ability, modeling ability, algorithmic thinking, creativity, cooperation ability, iterative optimization, transfer ability and evaluation. These dimensions were found to have significant Pearson correlations at the 0.01 level (two-tailed). Further exploration of gender differences in each dimension revealed that there were significant differences between males and females in terms of decomposition ability, abstract ability, modeling ability, creativity, iterative optimization, transfer ability, and evaluation, with males having significantly higher average scores than females. However, no significant gender differences were observed in algorithmic thinking and cooperation ability. The study points out that deep learning technology provides a new perspective for computational thinking education, contributing to the cultivation of students’ innovative thinking and autonomous learning abilities. This research provides practical references and theoretical foundations for the teaching reform of electronic majors in universities.

Many teachers in kindergarten do not know how to stimulate early childhood computational thinking ability. One way to stimulate early childhood computational thinking ability is through coding games, either using digital device media or without digital device media. This article aims to analyze the types of coding games as a medium that can help stimulate early childhood computational thinking ability. The method used is a systematic literature review using descriptive qualitative data analysis to analyze relevant previous studies. This study examined 40 articles on coding games to stimulate early childhood computational thinking ability in various international journals between 2020 and 2025. The results of the analysis of theoretical studies show that coding games can stimulate early childhood computational thinking ability. This is because coding games involve children getting used to thinking logically, being structured, processing tasks systematically, and solving problems by developing the right solutions. The implications of this study can provide an overview of the types of coding games that can be implemented or practiced by teachers to stimulate early childhood computational thinking ability, by adjusting facilities in schools can use digital media or without digital media.

This development research uses a 4-D design model by Thiagarajan, namely define, design, develop, and disseminate. However, in this study only at the development stage. The subjects of this study were 20 students in class X Mathematics and Natural Sciences at the Private MA Miftahul Falah Diski. The validity of the learning media developed in terms of the analysis of the results of the validity of the learning media by the validators with a total average value of 3.72 (category "Valid"). Meanwhile, the practicality of learning media is seen from the observation score of the implementation of learning in the second trial, which is 3.71 (category "Well Implemented"). The effectiveness of learning media in terms of four aspects, namely classical completeness, student active activity observation scores, student self-efficacy scores, and student responses. The classical completeness of students' computational thinking ability in the second trial was 87% (17 students). The average percentage of students' achievement in the ideal time of activity in the second trial for three meetings was 21.98%, 20.2%, 21.7%, 26.5%, 10.9%, and 1.9%. The average score of the overall self-efficacy scale in the second trial for three meetings was 3.16 so it was included in the positive category. The average student response in the second trial was 91.6% (category "Interested"). Based on the normalized gain index, it was found that in the second trial there was an increase in the value with a score of 0.4 (the "medium" criterion). The average score of the overall self-efficacy scale in the second trial for three meetings was 3.16 so that it was included in the positive category. The average student response in the second trial was 91.6% (category "Interested"). Keywords: Macromedia Flash, Problem Based Learning, Computational Thinking Ability, Self-Efficacy, Development of Mathematics Learning Media, Three Variable Linear Equation System. DOI: 10.7176/JEP/12-34-03 Publication date: December 31 st 2021

In the era of increasing digitalization, the integration of technology in education is becoming increasingly important. One area that has received a major contribution from technology is mathematics education at the secondary school (SMA) level. The use of mathematics software has become a highly effective tool for teachers and students in understanding complex mathematical concepts, developing computational skills, and solving problems more efficiently and interactively. This article analyzes various literature studies related to the use of mathematics software in high school, with a focus on developing students' computational thinking abilities. Computational thinking (CT) abilities, which were first introduced by Seymour Papert, are important skills that help students in decision making and problem solving. Various studies show that the integration of CT in educational curricula, particularly through teaching programming and the use of mathematical software, can improve students' computing skills. Although there are challenges in implementation, such as lack of infrastructure and teacher training, this study highlights the importance of using technology in mathematics education to create a dynamic, interactive, and relevant learning environment. This research aims to provide a comprehensive analysis of literature studies related to the use of mathematics software in high school and its influence on the development of students' computational thinking skills. By understanding the findings from previous studies, it is hoped that this research can make a significant contribution to designing a more effective mathematics curriculum and provide practical guidance for educators in integrating mathematics software in everyday learning. The results of the analysis show that technology-based interactive learning methods, the use of special software such as Matlab and Geogebra, as well as programming training with languages ​​such as Java and Python, all show positive results in improving students' computing skills. However, there is still a need to improve abstract thinking skills and address variations in computational abilities among students.