Even though working with data is as important as coding for understanding and dealing with complex problems across multiple fields, it has received very little attention in the context of Computational Thinking. This paper discusses an approach for bridging the gap between Computational Thinking with Data Science by employing and studying classification as a higher-order thinking process that connects the two. To achieve that, we designed and developed an online constructionist gaming tool called SorBET which integrates coding and database design enabling students to interpret, organize, and analyze data through game play and game design. The paper presents and discusses the results of a pilot study that aimed to investigate the data practices secondary students develop through playing and modifying SorBET games, and to determine the impact of game modding on student critical engagement with CT. According to the results, students developed and used certain data practices such as data interpretation and data model design to become better players or to design an interesting classification game. Moreover, game modding process motivated students to question the original games’ content, leading them to develop a critical stance towards the game data model and representations.
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.
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.
Computer science concepts have an important part in other subjects and thinking computationally is being recognized as an important skill for everyone, which leads to the increasing interest in developing computational thinking (CT) as early as at the comprehensive school level. Therefore, research is needed to have a common understanding of CT skills and develop a model to describe the dimensions of CT. Through a systematic literature review, using the EBSCO Discovery Service and the ACM Digital Library search, this paper presents an overview of the dimensions of CT defined in scientific papers. A model for developing CT skills in three stages is proposed: i) defining the problem, ii) solving the problem, and iii) analyzing the solution. Those three stages consist of ten CT skills: problem formulation, abstraction, problem reformulation, decomposition, data collection and analysis, algorithmic design, parallelization and iteration, automation, generalization, and evaluation.
In this study, effectiveness of a computer science course at the secondary school level is investigated through a holistic approach addressing the dimensions of instructional content design, development, implementation and evaluation framed according to ADDIE instructional design model where evaluation part constituted the research process for the current study. The process has initiated when the computer science curriculum had major revisions in order to provide in-service teachers with necessary support and guidance. The study is carried through as a project, which lasted more than one year and both quantitative and qualitative measures were used through a sequential explanatory method approach. The intention was to investigate the whole process in detail in order to reveal the effectiveness of the process and the products. In this regard, not only teachers' perceptions but also students' developments in their perceptions of academic achievement and computational thinking, as well as correlations between the computational thinking sub-factors were investigated. The findings showed that the instructional materials and activities developed within the scope of the study, positively affected the computational thinking and academic achievement of students aged 10 and 12 years old. The teachers' weekly feedbacks regarding application structures and implementation processes were also supported the findings and revealed some more details that will be useful both for instructional designers and teachers.