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In recent years, many European countries have revised their statutory compulsory education curriculum, introducing basic Computer Science concepts. This has paved the way for the development of students’ Computational Thinking (CT) skills. Further impetus in this direction is coming from the European Commission’s Digital Education Action Plan 2021-2027, where quality Computing Education is a key element under the priority “Enhancing digital skills and competences for the digital transformation”. Despite increasing uptake, a range of issues and challenges are emerging for the effective integration of CT skills in compulsory education. This report updates and extends findings from the 2016 CompuThink study, providing an updated overview in 22 EU Member States and eight non-EU countries. The study has gathered a wide range of evidence from a systematic literature review, a survey with representatives of Ministries of Education, two online consultation events, and through in-depth case studies in nine European countries involving semi-structured interviews (with experts, policy makers, school leaders, teachers) and focus groups (with students). The report discusses significant developments concerning the integration of CT skills in compulsory education in Europe between 2016 and 2021. It also provides a comprehensive summary of evidence, including eleven recommendations for policy and practice.

The introduction of the new Informatics curriculum in the Netherlands in 2019 raises the need for new teaching material that includes practical assignments and guidelines for their assessment. As a part of our research project on teaching Computational Science (modeling and simulation), we participate in these efforts and developed a curriculum intervention and an assessment instrument consisting of a practical assignment and grading rubrics to assess student’s level of understanding. The rubrics we developed can be used both for formative and summative assessment. In this paper we describe the design of this assessment instrument and indicate further research directions focusing on validation of this instrument.

How the development of a personalised learning environment should be enabled for students? In this paper the definitions of a teaching/learning method, learning activity are analysed, the problem of classification of teaching/learning methods is discussed, and by using comparative analyses the classifications of learning activities and learning methods are presented in a more detailed way. This model is the first step of creating intelligent technologies for future schools. This technology is a recommender system that should interconnect the learning methods and other educational components with students’ learning styles. Afterwards, the classification of teaching/learning methods is proposed in this paper. The authors apply their model in classifying learning methods and present an example of expansion of the classification of student-centred learning methods and their learning activities. This classification model will help in later works for creating interconnections between students’ learning styles, their preferred learning activities, relevant teaching/learning methods, and LOs types. Kaip būtų galima kurti ir įgyvendinti personalizuotą mokymąsi? Šiame straipsnyje nagrinėjami mokymo(si) metodų bei veiklų apibrėžimai, mokymo(si) metodų klasifikacijos problema ir pateikiamos mokslinėje literatūroje aprašomos mokymo(si) metodų klasifikacijos. Be to, pasiūlytas apibendrintas ir praplėstas mokymo(si) metodų klasifikavimo modelis. Šis modelis – tai pirmasis intelektualios technologijos kūrimo etapas. Ši technologija – rekomendacinė sistema, jungianti mokymosi metodus ir kitus mokymosi komponentus su mokinio mokymosi stiliais. Autoriai pritaiko pasiūlytą metodų klasifikavimo modelį ir pateikia į mokinį orientuoto mokymo(si) metodo ir jo veiklų klasifikavimo pavyzdį. Pasiūlytas modelis padės ateities darbuose susieti mokinio mokymosi stilius su jam tinkamais mokymo(si) metodais, veiklomis ir mokymosi objektais.