Informatics in Education

As computing has become an integral part of our world, demand for teaching computational thinking in K-12 has increased. One of its basic competences is programming, often taught by learning activities without a predefined solution using block-based visual programming languages. Automatic assessment tools can support teachers with their assessment and grading as well as guide students throughout their learning process. Although being already widely used in higher education, it remains unclear if such approaches exist for K-12 computing education. Thus, in order to obtain an overview, we performed a systematic mapping study. We identified 14 approaches, focusing on the analysis of the code created by the students inferring computational thinking competencies related to algorithms and programming. However, an evident lack of consensus on the assessment criteria and instructional feedback indicates the need for further research to support a wide application of computing education in K-12 schools.

This paper presents an approach to the initial programming learning using the four components instructional model and the Alice software. The quasi-experimental design was developed with two groups of students that attended two schools with very different socioeconomic status and school retention levels. The differences obtained in the mean of the programming knowledge test when co-variated with the Logical Development Scale score were positive in the two groups, with no statistical significance in the difference between both (p = 0.05). The differences obtained in the Logical Development Scale score (Échelle Collective de Devéloppement Lógique [ECDL]), before and after the experimental treatment, revealed positive differences in the experimental group with no statistical significance (p > 0.05), and in the control group with statistical significance (p < 0.05). These results suggest that the Alice software when combined with the 4C-ID instructional model has positive effects in programming learning and in logical reasoning.

Computerized Adaptive Testing (CAT) is now widely used. However, inserting new items into the question bank of a CAT requires a great effort that makes impractical the wide application of CAT in classroom teaching. One solution would be to use the tacit knowledge of the teachers or experts for a pre-classification and calibrate during the execution of tests with these items. Thus, this research consists of a comparative case study between a Stratified Adaptive Test (SAT), based on the tacit knowledge of a teacher, and a CAT based on Item Response Theory (IRT). The tests were applied in seven Computer Networks courses. The results indicate that levels of anxiety expressed in the use of the SAT were better than those using the CAT, in addition to being simpler to implement. In this way, it is recommended the implementation of a SAT, where the strata are initially based on the tacit knowledge of the teacher and later, as a result of an IRT calibration.

In this paper we report a study in which we have developed a teaching cycle based closely on Bloom's Learning for Mastery (LFM). The teaching cycle ameliorates some of the practical problems with LFM by making use of the STACK online assessment system to provide automated assessment and feedback to students. We report a clinical trial of this teaching cycle with groups of university level engineering students. Our results are modest, but positive: performance on the exercises predicted mastery according to the formative tests to a small extent. Students also report being supportive of the use of the new teaching cycle.

This longitudinal study investigates the impact of an extra-curricular programming workshop in student interest development in computer science. The workshop was targeted at 12-18-year old youngsters. A survey was sent to all previous participants with a known home address; 31.5% responded the survey (n = 197). This data was then combined with pre-workshop survey data, and analyzed with mixed methods. Positive development of interest was discovered for 57% of the respondents, of which nearly all attributed their interest increase to the workshop at least partly (92%). Qualitative inspection revealed that the workshop provided three anchors that facilitated students' reengagement with programming and development of interest: disciplinary content, a concrete artifact built by students themselves, and tools. Neutral development and interest regress were also discovered, though the impact of the workshop on these interest trajectories remains unclear.

During the last decade, coding has come to the foreground of educational trends as a strong mean for developing students' Computational Thinking (or CT). However, there is still limited research that looks at coding and Computational Thinking activities through the lens of constructionism. In this paper, we discuss how the knowledge we already have from other thinking paradigms and pedagogical theories, such as constructionism and mathematical thinking, can inform new integrated designs for the cultivation of Computational Thinking. In this context, we explore students' engagement with MaLT (Machine Lab Turtle-sphere), an online environment of our design that integrates Logo textual programming with the affordances of dynamic manipulation, 3D graphics and camera navigation. We also present a study on how the integration of the above affordances can promote constructionist learning and lead to the development of CT skills along with the generation of meanings about programming concepts.

The aim of this study was to reveal pre-service teachers' experiences in learning robotics design and programming. Data were collected from 15 pre-service teachers through semi-structured interviews and analyzed using the content analysis method. Three themes were identified in this study: Course process, professional development and teaching children. The pre-service teachers indicated that they found opportunities to learn by doing and experience, enjoyed doing robotics activities and felt in flow in this process. They also expressed that the robotics programming course positively influenced their attitudes towards programming and improved their programming skills. They emphasized the importance of keeping their intrinsic motivation high by maintaining their individual efforts to solve problems. Moreover, they made various suggestions for teaching robotics to children. Implications are discussed in terms of practices for educational robotics in teacher training, and further research directions.

Amount of educational data has been constantly increasing for years in all domains and kinds of education (formal or informal) and educational activities (teaching, learning, assessment, use of social media and collaboration and so on). Accordingly, Learning Analytics (LA) become a powerful mechanism for supporting learners, instructors, teachers, learning system designers and developers to better understand educational processes and predict learners' needs and performances. In this paper, we analyze the important dimensions and objectives of LA, application possibilities and some challenges to the beneficial exploitation of educational data. The required skills and capabilities that make meaningful use of LA techniques and technologies in this domain are considered and identified. Presented findings can act as a valuable guide for setting up LA services in support of educational practice. Also, they can be used as learner guidance, in quality assurance, curriculum development, and in improving learning process effectiveness and efficiency. Finally, this paper proposes the unavoidable constraints that affect LA technologies in education.

The European Commission Science Hub has been promoting Computational Thinking (CT) as an important 21st century skill or competence. However, "despite the high interest in developing computational thinking among schoolchildren and the large public and private investment in CT initiatives, there are a number of issues and challenges for the integration of CT in the school curricula". On the other hand, the Digital Competence (DC) Framework 2.0 (DigCom) is promoted in the same European Commission Science Hub portal. It shows that both topics have many things in common. Thus, there is the need of research on the relationship between CT and digital competence.

Many countries have focused on the improvement of education system performance. Small number of studies consider system of a country as unit of assessment where indicators represent all levels of education system. In the paper, we propose the methodology for the performance analysis of education systems as a whole hybridizing Data Envelopment Analysis and Principal Component Analysis. Its applicability is illustrated by the analysis of the data collected for 29 European countries. In the analysis we used publicly available data from EUROSTAT and OECD which European Commission uses for the performance monitoring of education in European Union. No prior assumptions were made or expert judgements included. We demonstrated good performance of the method on limited data set. The proposed methodology of hybrid Data Envelopment Analysis and Principal Component Analysis allows researchers analyse education systems quantitatively. The recommendations for improvements and assessment of real world education systems should be based on the analysis of a sufficiently large data set comprehensively representing the considered education systems.