Informatics in Education

This study aims to explain the relationships between secondary school students' digital literacy, computer programming self-efficacy and computational thinking self-efficacy. The study group consists of 204 secondary school students. A relational survey model was used in the research method and three different data collection tools were used to collect data. The structural equation model was used in data analysis to reveal a model that explains and predicts the relationships between variables. According to the results of the research, it was determined that digital literacy of secondary school students affected their computer programming self-efficacy, digital literacy affected their computational thinking self-efficacy, and computer programming self-efficacy affected their computational thinking self-efficacy. It was also found that digital literacy skills have an indirect effect on secondary students' computational thinking self-efficacy on computational thinking self-efficacy.

In Education 4.0, a personalized learning process is expected, and that students are the protagonist. In this new education format, it is necessary to prepare students with the skills and competencies of the 21st-Century, such as teamwork, creativity, and autonomy. One of the ways to develop skills and competencies in students can be through block programming, which can be used with emerging technologies such as robotics and IoT and in an interdisciplinary way. Thus, block programming in High School is important because it is possible to work on aspects such as problem-solving, algorithmic thinking, among other skills (Perin et al., 2021), which are necessary in the contemporary world. Thus, our Systematic Mapping Study (SMS) aims to identify which block programming tools support of Education 4.0 in High School. Overall, 46 papers were selected, and data were extracted. Based on the results, a total of 24 identified block programming tools that can be used in high school collaboratively and playfully and with an interdisciplinary methodology. Moreover, it was possible to see that most studies address block programming with high school students, demonstrating a lack of studies that address block programming with teachers. This SMS contributed to identifying block programming tools, emerging technologies, audience (teacher or student), and learning spaces where block programming is being worked on.

Computing science which focuses on computational thinking, has been a compulsory subject in the Thai science curriculum since 2018. This study is an initial program to explore how and to what extend computing science that focused on STEM education learning approach can develop pre-service teachers' computational thinking. The online STEM-based activity-Computing Science Teacher Training (CSTT) Program was developed into a two-day course. The computational thinking test (CTT) data indicated pre-service teachers’ fundamental skills of computational thinking: decomposition, algorithms, pattern recognition, pattern generalization and abstractions. The post-test mean score was higher than the pre-test mean score from 9.27 to 10.9 or 13.58 percentage change. The content analysis indicated that there were five key characteristics founded in the online training program comprised: (1) technical support such as online meeting program, equipment, trainer ICT skills (2) learning management system such as Google Classroom, creating classroom section in code.org (3) the link among policy, curriculum and implementation (4) pre-service teachers' participation and (5) rigor and relevance of how to integrate the applications of computing science into the classroom.

The Computational Thinking (CT) teaching approach allows students to practice problem-solving in a way that they can use the Computer Science mindset. In this sense, Collaborative Learning has a lot to contribute to educational activities involving the CT. This article presents the design and evaluation of a Collaborative Learning framework for the development of CT skills in students. To design the proposed strategy, several fundamental features of the Collaborative Learning concept of the literature have been studied and sketched. The strategy was applied to middle school students through a digital games programming workshop. Data were collected by three means: (1) collecting artifacts produced during activities; (2) recording of game programming sessions; and (3) applying a structured interview to students. The data analysis showed evidence that the strategy was able to mobilize Computational Thinking skills in addition to mobilizing collaborative skills in learners.

Research trends on computational thinking (CT) and its learning strategies are showing an increase. The strategies are varying, for example is using games to provide enjoyment, engagement, and experience. To improve the high level of immersion and presence of game objects, learning strategies through games can be improved by virtual reality (VR) technology and its application. However, a systematic review that specifically discusses game based in VR (GBiVR) settings is lacking. This paper reports previous studies systematically about the strategies used to learn CT through games and VR applications. 15 papers were selected through Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. As the result, this study proposes a conceptual framework for designing a strategy to learn CT through GBiVR settings. The framework consists of critical aspects of variables that can be considered in the learning environment like game elements, VR features, and CT skills. All the aspects are discussed below.