Informatics in Education

Integrating computational thinking into K-12 Education has been a widely explored topic in recent years. Particularly, effective assessment of computational thinking can support the understanding of how learners develop computational concepts and practices. Aiming to help advance research on this topic, we propose a data-driven approach to assess computational thinking concepts, based on the automatic analysis of data from learners’ computational artifacts. As a proof of concept, the approach was applied to a Massive Open Online Course (MOOC) to investigate the course’s effectiveness as well as to identify points for improvement. The data analyzed consists of over 3300 projects from the course participants, using the Scratch programming language. From that sample, we found patterns in how computational thinking manifests in projects, which can be used as evidence to guide opportunities for improving course design, as well as insights to support further research on the assessment of computational thinking.

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.

In computer science education at school, computational thinking has been an emerging topic over the last decade. Even though, computational thinking is interpreted and integrated in classrooms in different ways, an identification process about what computational thinking is about has been in progress among computer science school-teachers and computer science education researchers since Wing's initial paper on the characteristics of computational thinking. On the other hand, the constructionist learning theory by Papert, based on constructivism and Piaget, has a long tradition in computer science education for describing the students' learning process by hands-on activities. Our contribution, in this paper, is to present a new mapping tool which can be used to review classroom activities in terms of both computational thinking and constructionist learning. For the tool, we have reused existing definitions of computer science concepts and computational thinking concepts and combined these with our new constructionism matrix. The matrix's most notable feature is its scale of learners' autonomy. This scale represents the degree of choices learners have at each stage of development of their artefact. To develop the scale definitions, we trialed the mapping tool, coding twenty-one popular international computing activities for pupils aged 5 to 11 (K-5). From our trial, we have shown that we can use the mapping tool, with a moderate to high degree of reliability across coders, to analyse classroom activities with regard to computational thinking and constructionism, however, further validation is needed to establish its usefulness. Despite a small number of activities (n = 21) being analysed with our mapping tool, our preliminary results showed several interesting findings. Firstly, that learner autonomy was low for defining the problem and developing their own design. Secondly that the activity type (such as lesson plan rather than online activity) or artefact created (such as physical artefact rather than onscreen activity or unplugged activity), rather than the computational thinking or computer science concept being taught was related to learner autonomy. This provides some tentative evidence, which may seem obvious, that the learning context rather than the learning content is related to degree of constructionism of an activity and that computational thinking per se may not be related to constructionism. However, further work is needed on a larger number of activities to verify and validate this suggestion.

Despite a growing effort to implement computational thinking (CT) skills in primary schools, little research is reported about what CT skills to teach at what age. Therefore, the research questions that guide this study read: (1) How is age related to students' success in computational thinking tasks? (2) How are computational thinking tasks perceived by students? (3) How do students' experience learning with respect to computational thinking? 200 primary school students between the age of 6 and 12 participated in this study. These students got introduced to two CT subjects: abstraction and decomposition. We found that age seems to be related with these concepts, with an interaction effect for gender in the abstraction task. No differences found between young and older students in the constructs perceived difficulty, cognitive load, and flow indicate that young primary school students can engage in learning these CT skills.

Mathematical logic is a discipline used in sciences and humanities with different point of view. Although in tertiary level computer science education it has a solid place, it does not hold also for secondary level education. We present a heterogeneous study both theoretical based and empirically based which points out the key role of logic in computer science, computer science education and knowledge representation. We focus on the key contrast of semantics and syntax, the resolution principle as a leading inference technique (giving also interesting non-clausal generalization of the rule). Further we discuss the possibilities of inclusion the non-classical (many-valued) logics in education together with the original generalization of the non-clausal resolution rule into fuzzy logic. The last part describes partial results of the research concerning the secondary education in the Czech Republic especially in the mathematical logic field. The generalization of the presented ideas entails the article.