Pair programming is an important approach to fostering students’ programming and collaborative learning skills. However, the empirical findings on pair programming are mixed, especially concerning ...

Collaborative and cooperative learning is important to prepare students for their future work and to increase their learning performance in university courses. Several studies have shown promising ...

The training of future-relevant competencies – so called Future Skills or 21st Century Skills – is currently moving to the center of the educational discourse in light of increasing technological developments and accessibility of AI systems, e.g. ChatGPT. It is our view that bringing together, thinking about and promoting Digital-, Data- and AI literacy in teaching is a major concern of future education. We focus in particular on teacher education, since teachers have a dual role: on the one hand, pre-service teachers are also learners who must first develop the appropriate competencies themselves, and on the other hand, they are multipliers as teachers in schools who must impart the appropriate competencies. Particularly in the context of novel generative AI systems and large language models, it is important to take a holistic and critical-reflective look at them from a technological, socio-cultural and user-oriented perspective.

Computing graduates are frequently reported by members of industry to lack in professional dispositions and/or non-technical skills (often referred to as "soft skills"). In this work, we conduct a gap analysis of the alignment between academic preparation and industry expectations through a three-pronged study. First, a literature review explored the academic perspective of how fostering professional dispositions and non-technical skills occurs in tertiary computing education. Second, a literature review identifying industry's expectations of those dispositions and skills for entry-level computing professionals. Finally, a mixed-methods approach, combining a survey and structured interviews of computing industry professionals to identify their opinions on the relative importance of those skills and dispositions. In each of these prongs, we additionally consider whether and how Diversity, Equity, Inclusion, and Accessibility (DEIA) may have been approached and/or incorporated. Our work uncovers a number of gaps. Several skills and dispositions, such as leadership, ethics, and inventiveness, are over-represented in the academic literature compared to industry's expectations, while others such as lifelong learning and professionalism are under-emphasised. Furthermore, some terms such as 'ethics' and 'professionalism' are defined differently by various stakeholder groups, leading to a gap between academic training and industry expectations. Finally, several skills and dispositions, such as collaboration, teamwork, communication, and leadership show evidence of exposure in academia, but require more scaffolded instruction to meet industry expectations. We also found a dearth of coverage in the literature and a lack of focus in industry for DEIA considerations.

This paper develops a method for the construction and evaluation of cognitive models to support students in their problem-solving skills during robotics in school, aiming to build a basis for an implementation of a tutoring system in the future. Two Wizard-of-Oz studies were conducted, one in the classroom and one in the lab. Based on the cognitive model, the human wizards gave support to 20 students working in pairs. The studies were video recorded and a qualitative analysis was conducted. This qualitative research approach is described in detail. The evaluation of the studies showed that students reacted mostly positively to the wizards. We also uncovered ways in which students’ problem-solving skills could be improved. Based on the evaluation and observations of the Wizard-of-Oz studies, the paper proposes a design for a future robotics skills tutoring system.

This study examines students’ perceptions of the subjects geography, mathematics, and computer science in integrated science, technology, engineering, and mathematics (STEM) lessons. Although the importance of an integrated approach in STEM education is emphasized, researchers are not clear about whether students perceive connections between the subjects on the one hand and subject-specific working methods and content in integrated lessons on the other. Data was collected in an integrated teaching unit on the sustainability of apples using an open-ended digital questionnaire in to two ninth grade classes in Hamburg, Germany (n = 38); this data was analyzed using qualitative content analysis. The results reveal that students perceive the subjects differently, but similarities can also be identified. While subject-specific content is perceived—such as the use of maps in geography, the calculation of volumes in mathematics, and Dijkstra’s algorithm in computer science—methodological connections, such as calculating, analyzing diagrams, or solving problems, are anchored across disciplines. This suggests that the subject-specific contents are not lost in integrating lessons, and that connections among the subjects are, to a certain extent, promoted.