Informatics in Education

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.

The paper elaborates on experiences and lessons learned from the course on object-oriented analyses and design at the Faculty of Sciences, Novi Sad. The course on OOAD is taught to students of computer science and to the students of mathematical programme. Conclusions made in this paper are based on results of students' assignments as well as results of conducted survey. In the paper we identify a set of issues concerning teaching modelling and UML. It is noticed that difficulties in mastering OOAD arise primarily from the absence of appropriate real case studies from the field of designing information systems. In order to overcome this problem, students worked on their own homework projects which include all phases of software development. Concerning the results of survey it is noticed that OOAD course should be taught in different manners regarding previous knowledge of students. Suggestions how to teach OOAD to students of computer science and to students of other programmes are given in this paper.

This paper represents a first attempt at constructing a language for describing the potential learning value of computers as a learning material. A lack of precision in describing the value computers add to the learning process has paradoxically made it easy for people to elevate the significance of using computers in pedestrian ways while simultaneously marginalizing higher-order uses such as Logo programming. Colleagues are invited to extend or challenge this paper's hypotheses.

Computer simulations seem to be one of the most effective ways to use computers in physics education. They encourage students to carry out the processes used in physics research: to question, predict, hypothesise, observe, interpret results etc. Their effective use requires an availability of appropriate teaching resources fitting secondary schools curricula.

This paper presents model-based assessment and forecasting of the Lithuanian education system in the period of 2001-2010. In order to obtain satisfactory forecasting results, constructing of models used for these aims should be grounded on some interactive data mining. Data mining of data stored in the system of the Lithuanian teacher's database and of data from other sources representing the state of education system and the demographic changes in Lithuania was used. The models cover the estimation of data quality in the databases, the analysis of flow of teachers and pupils, the clustering of schools, the model of dynamics of pedagogical staff and pupils, and the quality analysis of teachers. The main results of forecasting and integrated analysis of the Lithuanian teachers' database with other data reflecting the state of the education system and demographic changes in Lithuania are presented.