Coding with Minecraft: The Development of Middle School Students’ Computational Thinking

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

Background: A common critique of adventure education research methodology is the overreliance on pre-/post-study designs to measure change. Purpose: This paper compares and contrasts two methods of data analysis on the same adventure education data set to show how these distinct approaches provide starkly different results and interpretation. Methodology/Approach: Using secondary data analysis, we employ a longitudinal data set of the social skill development of urban middle school students who participated in an adventure education program over the course of three academic years. First, change was assessed using a pre-/post-design by a traditional analysis of variance (ANOVA). Next, change was assessed with a six-wave, longitudinal design using multilevel modeling. Findings/Conclusions: Results show that the multilevel modeling approach revealed nonlinear change in the social skill development of middle school students, resulting in more accurate, nuanced estimation of change in social skill development than the ANOVA approach. Implications: The use of longitudinal data and multilevel modeling can be a useful methodological approach and statistical tool for adventure education researchers to not only address the criticisms of quantitative research in adventure education, but more importantly, provide a more thorough understanding of the impact of adventure education on human development.

This presented research has three purposes: The first purpose of this study is to examine the power of middle school students' social emotional learning and daily life decision-making skills together as a predictor of their career development. The second purpose is to examine the career development of middle school students according to gender. Third purpose is to examine the career development of middle school students according to targeted high school type. The research group consisted of 263 middle school students (141 female, 116 male, 6 unknown). These students were studying in 3 middle schools in the center of a large city in the northwestern part of Turkey and their ages ranged between 10-15 (X̄=12.31; sd=1.07). The research data were collected by applying the Chilhood Career Development Scale, Social Emotional Learning Scale for Adolescents, Daily Life Decision Making Scale and Personal Information Form. The research data were analysed using multiple linear regression analysis, t test, and one-way ANOVA. The research results showed that middle school students' social emotional learning and daily life decision-making skills scores together accounted for a significant proportion of the variance 0.19% of the career development scores of middle school students. The results showed that the career development score mean of students targeted Anatolian high school were higher than those aiming for science high school and vocational and technical high school. There was not significantly differences in career development scores of the students according to gender. The research results were discussed based on the relevant literature, provided important implications for the theoretical and practical literature on career development, social emotional learning and daily life decision-making skills and suggestions were presented for future theoretical and practical research.

Bilgi işlemsel düşünme son yıllarda akademisyenlerin, ülkelerin ve eğitimcilerin gündemine girmiştir. Bir kavramın, becerinin veya bilginin geliştirilip geliştirilemediğini belirlemek için onun ölçülmesi önemlidir. Bu çalışmanın amacı İspanyolca olarak geliştirilen bilgi işlemsel düşünme testinin Türkçeye uyarlanmasıdır. Uyarlama için öncelikle test Türkçeye çevrilmiştir ve uzmanlar tarafından değerlendirilmiştir. Ardından test yeniden İspanyolcaya çevrilmiştir ve testin ilk hali ve geri çevirisi karşılaştırılıp çeviri işlemi tamamlanmıştır. Türkçeye çevrilen test 602 ortaokul öğrencisine uygulanarak madde güçlüğü, madde ayırt ediciliği ve iç tutarlılık açısından değerlendirilmiştir. Bu analizler sonucunda İspanyolcasında 28 madde bulunan test 24 maddeye düşürülmüştür. Testten elde edilen puanlar cinsiyet ve sınıf seviyesi açısından değerlendirilmiştir. Test puanları cinsiyet açısından istatistiksel olarak anlamlı bir farklılaşma göstermemiştir. (i) Beşinci ve altıncı sınıf öğrencileri ve (ii) yedinci ve sekizinci sınıf öğrencileri arasında bilgi işlemsel düşünme açısından istatistiksel olarak anlamlı bir fark bulunmamıştır. Fakat bu iki grup (5-6 ve 7-8) öğrenci arasında anlamlı bir fark tespit edilmiştir. Bilgi işlemsel düşünme testi akademisyenler ve eğitimciler tarafından çalışmalarında ve pratik öğretimleri içerisinde kullanılabilir.

The work is devoted to the consideration of improving the quality of teaching students the discipline “Numerical methods” through the development of the cognitive component of computational thinking based on blended learning. The article presents a methodology for the formation of computational thinking of mathematics students, based on the visualization of algorithmic design schemes and the activation of the cognitive independence of students. The characteristic of computational thinking is given, the content and structure of computational thinking are shown. It is argued that a student with such a mind is able to manifest himself in his professional field in the best possible way. The results of the application of the technique are described. To determine the level of development of the cognitive component of computational thinking, a diagnostic model has been developed based on measuring the content, operational and motivational components. It is shown that the proposed method of developing computational thinking of students, taking into account the individual characteristics of students’ thinking, meaningfully based on the theoretical and practical aspects of studying the discipline, increases the effectiveness of learning the course “Numerical methods”. The materials of the article are of practical value for teachers of mathematical disciplines who use information and telecommunication technologies in their professional activities.

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

The study aimed to investigate the computational thinking traits of third-grade middle school students while using RoboMind for programming within a project-based learning setup. It also aimed to determine if incorporating RoboMind into project-based instruction improved students' computational thinking skills, attitudes toward programming, and programming performance based on project outcomes. Implemented through a quasi-experimental design with 138 students from two Saudi Arabian schools, the results indicated a significant improvement in computational thinking skills and positive changes in attitudes toward programming post-RoboMind implementation. The study identified four primary dimensions and seven sub-dimensions of computational thinking, emphasizing its diverse aspects. Furthermore, notable correlations were found between RoboMind project scores and post-RoboMind computational thinking scores in the experimental group. These findings advocate for the integration of RoboMind into programming education, especially within Saudi Arabian educational institutions.

While various studies have focused on the significance of computational thinking (CT) for the future career paths of individuals in science, technology, engineering, and mathematics (STEM), few studies have focused on computational thinking for non-STEM college students. This study explores the relationship between computational thinking and learning satisfaction for non-STEM-major college students. A conceptual model is proposed to examine the structural relationships among computational thinking, self-efficacy, self-exploration, enjoyment and learning satisfaction in an AppInventor-based liberal education course. Collecting data from 190 undergraduate students from Taiwan and analyzing the data by using partial least squares (PLS) methods, the research framework confirms the six proposed hypotheses. These results show that both computational thinking and enjoyment play significant roles in both self-exploration and digital self-efficacy. Moreover, digital self-efficacy and self-exploration also have a significant positive influence on learning satisfaction. These findings have implications for influencing the learning outcomes of non-STEM-major college students, computational thinking course instructors, and computational thinking relevant policies.

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.

Computational thinking is an important and necessary part of a modern person’s thinking. It has been proven that the development of this way of thinking in students with mental disabilities allows them to navigate quickly in the modern world, identify problems and create complex solutions. Online schooling during the COVID-19 pandemic demonstrated the possibilities of the usage of web technologies in the education of children with mental disabilities. This study aims to evaluate the impact of web technologies on the development of computational thinking of students with mental disorders. The experiment involved 14 students aged 8-12 and 4 tutors. For 8 weeks children were trained in computational thinking and computer science. Assessment of computational thinking was performed with cCT-test by El-Hamamsi et al. before and after the experiment. After conducting computer science lessons using web technologies the respondents showed a higher level of computational thinking (M=15,7, SD=3,69), compared to the results of preliminary testing (M=5,93, SD=2,3). Web technologies can significantly increase the effectiveness of inclusive pedagogy, which establishes the importance of integrating web technologies into the teaching system in inclusive classes of general education schools.

Computational thinking is increasingly important in the secondary curriculum beyond the computer science classroom, especially in technology heavy STEM fields. We applied the Computational Thinking in Mathematics and Science Taxonomy (Weintrop et al., 2016) to explore how secondary students demonstrated computational thinking in research projects from a month-long STEM enrichment summer program. The preliminary data show that the papers and posters of four students, one from each area of the summer curricula, demonstrate all four of the practices: Data Practices, Modeling and Simulation Practices, Computational Problem Solving Practices, and Systems Thinking Practices. These results indicate that computational thinking provides a useful framework for planning and assessing secondary students’ STEM independent research projects. Key words: computational thinking, research.

Physics learning provides a context for future careers in fostering ability in high-end logic with the 21st learning goals. Applying computational thinking in schools is challenging and requires systemic transformation and teacher attention. This study aims to investigate the computational thinking of students in physics learning. This study used exploratory qualitative research. Data were gathered through observation, interviews, and portfolio documents. The data are analyzed through six stages: preparing and organizing, exploring, building descriptions, representing the findings, interpreting the results, and validating the accuracy. The result indicated four primary computational thinking skills: decomposition, abstraction, simulation, and evaluation. The computational thinking skills in physics learning can develop students’ understanding and implementation of physics concepts based on data, not just mathematical formulas. Computational thinking in physics learning gives students the opportunity and space to explore and develop their ideas and logical reasoning more deeply in problem-defining, solutions, and evaluation. Students use their logical reasoning to solve the problem precisely. This study is expected to be used as a basis and support for physics teachers to integrate computational thinking into their learning classroom.

Computational thinking has emerged as a critical 21st-century skill, yet many secondary students in Malaysia have not been formally exposed to structured computational thinking education. This study evaluates the effectiveness of a “Basic to Advanced Computational Thinking for Secondary Students” program implemented in Melaka, Malaysia. To assess the impact of a four-day computational thinking program on secondary students’ knowledge, skills, and confidence in computational thinking concepts. A pre-post evaluation design was employed using the validated form provided by Research, Innovation, Commercialisation, and Entrepreneurship (RICE) University Technical Malaysia Melaka (UTeM) assessment instrument. Forty-eight secondary students (Forms 1-3) participated in the program, which covered introduction to computational thinking which includes Microbit, Scratch, artificial intelligence (AI), and robotics. Participants completed self-assessment questionnaires before and after the program using a 5-point Likert scale. The program demonstrated significant effectiveness across all measured competencies. Overall mean scores improved from 2.45 to 3.71 (51.3% improvement). The highest improvements were observed in knowledge acquisition (60.9%) and program relevance perception (53.2%). Female students (n=9) and male students (n=20) both showed substantial improvements, with the program successfully engaging diverse learners across different form levels. The structured computational thinking program effectively enhanced secondary students’ competencies in computational thinking. The findings support the integration of comprehensive computational thinking curricula in Malaysian secondary education to prepare students for digital literacy demands.

We live in a century where technology has become part of our lives, and it is crucial that we become active creators of technology, not just passive users. Learning to program computers enables a person to create twenty-first-century solutions. Computer programming is more than just learning how to code; it also exposes students to the opportunity to develop computational thinking (CT), which involves problem-solving using computer science concepts. In this chapter, we explore strengths and weaknesses of students’ CT skills and compare a group of seventh- and eighth-grade students who engaged in a Scratch programming environment. Scratch is a popular visual programming language that introduces computer programming to youth. We use Dr. Scratch, a CT assessment tool, to analyze students’ Scratch projects for evidence of CT. The results of this study can show researchers and educators how they might use Dr. Scratch to analyze students’ Scratch data to help improve their CT.

Software education has emerged as a hot topic around the world, with the goal to raise interests on computational thinking. However, assessments on the computational thinking have not been actively conducted thus far. According to a study by Lee (2019), which analyzed 138 papers on computational thinking published in Korean journals from 2015 to 2018, software education has been introduced and studies on computational thinking are being conducted, but studies on teaching methods that2 improve computational thinking are needed. In this study, we developed and applied a primary educational programming language(EPL) program focused on execution time analysis aimed at improving computational thinking. By using the “Bebras Challenge” as an assessment tool and SPSS as a statistical tool, educational effects were analyzed through the results of pre- and post-computational thinking assessments. The analysis outcomes showed that the EPL education focused on execution time analysis was effective in improving the computational thinking of elementary school students. Putting execution time analysis EPL into primary software education as an educational topic will be effective in improving computational thinking.