Hour of Code: Classroom Escape

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.

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.

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 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.

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.

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 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.

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.

Interactive multimedia is one of the most popular types of learning media and provides a significant increase in the success of the learning process. The achievement of mathematics learning objectives can be seen based on the level of students' computational thinking abilities and learning motivation. Therefore, this research was conducted to develop interactive multimedia that can improve students' computational thinking skills and learning motivation. This development research uses the ADDIE (Analysis, Design, Development, Implementation and Evaluation) model. The sample for this research was class IX students at Tunas Karya Batangkuis Middle School. The research results show that the interactive multimedia developed meets the criteria of being valid, practical and effective in improving students' computational thinking skills and learning motivation. Interactive multimedia obtained a validity value of 3.6 with very good criteria. Interactive multimedia obtained a practicality score of 3.4 (very good category) from the response questionnaire and 3.2 (good category) from the learning implementation questionnaire. The effectiveness of interactive multimedia can also be seen from several aspects, including students' classical completion level which reached 92%, achievement of learning objectives by 80%, very positive student responses, and good levels of student activity. Apart from that, the use of interactive multimedia also succeeded in increasing computational thinking abilities by 0.54 (medium category) and student learning motivation by 0.65 (medium category).

With the development of the digital age, online teaching and learning is becoming more widespread in schools around the world. In the online teaching environment, the teaching mode of the course is an important element that receives attention in education and teaching. The online teaching mode based on the cultivation of computational thinking can improve students' learning interest and cultivate their innovative thinking ability. However, the author found through educational internship that there are problems such as single teaching activities, lack of teacher-student interaction, poor cooperative learning, and short independent learning time in high school information technology classrooms, which lead to low computational thinking ability and are not conducive to the development of students' innovative ability. The development of students' computational thinking ability is a requirement put forward by the high school information technology curriculum to secondary school students, and the improvement of computational thinking can help students adapt to the future society and meet the demand of future innovative talents. Therefore, this study takes high school students as the research object, under the guidance of constructivism and cognitivism theories, adopts survey research, experimental research and other research methods to construct and verify the online teaching mode based on the cultivation of computational thinking in high school information technology courses. The results of the study show that the online teaching mode based on the development of computational thinking can effectively improve students' algorithmic, evaluation, decomposition, abstraction and generalization thinking abilities, and thus enhance the online learning effect.

Computational thinking ability need to be trained from an early age through the mathematics ability approach at the primary schools level. This study aims to analyze the effect of the analysis of mathematic ability to computational thinking abilities in primary schools age in sdn 2 sekarteja with 2 measurement variables including: computational thinking ability and math ability. This type of research is quantitative using descriptive methods. The population of this study was class V SDN 2 Sekarteja with a total of 30 students and the entire population becomes the sample, the type of research sample is saturated sample. Data collection techniques in this study used tests and documentation. The technique used to analyze the data was descriptive statistics. The results of this study indicated that, with n = 30 and a significant level of 5%, r table = 0.361, while the result rcount = 0.304. The results obtained were rcount ≤ rtabel, then Ha was rejected and Ho was accepted and the direction of the correlation was negative. It can be concluded that there was no significant relationship between the computational thinking abilities of elementary school age children in terms of mathematics abilities at SDN 2 Sekarteja

This Innovative Practice Full Paper presents an approach to improve teaching materials and assessment tools for K-12 programming education together by creating a virtuous cycle. Improving teaching materials for computing education is in line with the conference theme “Creating a convergence in engineering education and workforce development”. In this research, coding sheets are used as a part of the teaching materials, and the assessment tools are used to assess the algorithmic thinking ability of the students. The assumption here is that there is a mutual impact between the improvement of teaching materials and that of assessment tools. This kind of strategy is important, especially in the setting of elementary school education in Japan in which conducting a pilot study is difficult. In Japan, the new curriculum guidelines were fully implemented in April 2020 in elementary schools and in April 2021 in junior high schools respectively. They will be implemented in April 2022 in high schools. Since the announcement of the new curriculum guidelines, the boards of education in the local governments have been preparing for the programming education in the schools. However, there are still remaining problems, including the shortage of trained teachers and the lack of good assessment tools. In order to remedy the shortage of trained teachers, we designed some coding sheets for the teaching materials consisting of block parts, servo motors, DC-motors, LEDs, and sensors. In our assessment tools which are supposed to assess students' Computational Thinking ability, we included only the questions for assessing algorithmic thinking ability, as there is a limited amount of time for the assessment in schools. We have used our teaching materials and our assessment tools in some elementary schools. Based on the results of the teaching activities, we discuss the strategy to improve the teaching materials and the assessment tools together.

This study integrated the augmented reality (AR) technology into the “Coding Ocean” board game to provide players with real-time simulation of ship paths and learning scaffolds. Combined with Scratch block-based programming, an interactive learning environment is developed to assist elementary school students in learning coding skills from the unplugged board game to enhance their computational thinking concepts. The AR board game is focused on the programming concepts of sequential, and/or and loop. Through the process of treasure hunting, the basic concepts of computational thinking can be developed, i.e., abstraction, problem decomposition, pattern recognition and algorithmic thinking. In order to investigate the learning effectiveness of the AR board game on computational thinking and programming skills, a number of 51 third graders from an elementary school were recruited as research samples. The experimental group (n = 26) used the AR board game and the control group (n = 25) used the traditional board game for game-based learning. The experimental results indicate: (1) the learning effectiveness of computational thinking for the experimental group was significantly higher than that of the control group; (2) the learning achievement of the block-based programming skills for the experimental group was significantly higher than that of the control group; (3) the cognitive load of the experimental group was significantly lower than that of the control group. The AR technology can combine the unplugged board games with plugged learning modules to assist students in game-based learning, which is useful for enhancing computational thinking abilities while reducing the cognitive load.

This paper presents the results of a project on Computational Thinking education for primary school pupils. During the project – called Computational Thinking for children education – 81 students from a primary school in Italy have been guided to the design and development of computer games through the Microsoft Kodu game development platform. Different activities have been proposed to the pupils with the aim of promoting Computational Thinking abilities and skills. A narrative approach has been adopted throughout the project. Preliminary results of the educational experience highlight as the adoption of narrative learning and physical reproduction of manipulative programming objects provide an affordance for the development of Computational Thinking abilities. Furthermore, constancy during the learning process affects the acquisition of game development skills; finally, the design and implementation of computer games using Kodu have had a significant positive influence on the perception of computer programming.

This research was conducted as an innovation related to learning problems that often occur in students. This research aims to develop a technological prototype of the mathematics-computation learning environment for playing skills using the Zone of Proximal Development (ZPD) approach based on intelligent technology. This type of research is Research and Development using the 4-D model flow (Four-D Models). The sampling technique is purposive sampling. Data collection in this study uses angles for learning environment data sources and computational thinking. Then interviews are used as a source of learning experience data. Data analysis on quantitative data types used descriptive and inferential statistics in the form of independent sample t-tests and the Miles and Huberman model. This study found differences in the computational thinking abilities of male and female students, and the dominant computational thinking abilities were male students. This development research has produced an online learning environment product where the product is valid in the opinion of experts in the good category, exciting and feasible to implement. The learning environment assists and facilitates students in learning mathematics by using technology geared toward improving thinking.