Research on collaborative learning of computer science has been conducted primarily in programming. This paper extends this area by including short tasks (such as those used in contests like the Bebras Challenge) that cover many other computer science topics. The aim of this research is to explore how problem-solving in pairs differs from individual approaches when tackling contest tasks.
An observational study was conducted on tens of thousands of contestants aged 8–12 years. Statistical tests showed that, compared to individuals, pairs have a higher ratio of correct answers and solve slightly more tasks. They seem to be more successful in some components of computational thinking and are more confident in their answers. In tasks with instant feedback, pairs find the correct solution faster than individuals. As the age of the pupils increases, a trend of decreasing advantages of working in pairs can be observed. These results could be useful for curriculum makers who create computer science textbooks.
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.
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.
Although there is no universal agreement that students should learn programming, many countries have reached a consensus on the need to expose K-12 students to Computational Thinking (CT). When, what and how to teach CT in schools are open questions and we attempt to address them by examining how well students around the world solved problems in recent Bebras challenges. We collected and analyzed performance data on Bebras tasks from 115,400 students in grades 3-12 in seven countries. Our study provides further insight into a range of questions addressed in smaller-scale inquiries, in particular about the possible impact of schools systems and gender on students' success rate.
In addition to analyzing performance data of a large population, we have classified the considered tasks in terms of CT categories, which should account for the learning implications of the challenge. Algorithms and data representation dominate the challenge, accounting for 75-90% of the tasks, while other categories such as abstraction, parallelization and problem decomposition are sometimes represented by one or two questions at various age groups. This classification can be a starting point for using online Bebras tasks to support the effective learning of CT concepts in the classroom.
As an international informatics contest, or challenge, Bebras has started the second decade of its existence. The contest attracts more and more countries every year, recently there have been over 40 participating countries. From a single contest-focused annual event Bebras developed to a multifunctional challenge and an activities-based educational community building model. This paper aims to introduce the Bebras model using ten years of observations in implementing the contest in different countries. The model is essentially based on democratic and inclusive education values. Systematic literature review of research papers concerning Bebras activities has made an integral background for this model. The model is represented both at international and national levels and consists of several components where the development of Bebras tasks has taken a very significant role. Reasoning on innovated learning informatics and strengthening computational thinking by utilising carefully selected informatics concepts is discussed as well.