Software project management faces increasing demands as development practices evolve, motivating the development of new support tools. Recent advances in generative AI, particularly large language models (LLMs), offer opportunities to enhance project management by analysing project data and providing guidance using a natural-language interface. This paper presents a Design Science Research study that designs and implements a retrieval-augmented generation (RAG) chatbot integrated with an existing project monitoring tool for student software projects. The prototype validates the system architecture and evaluates prompt engineering using a commercial LLM. The results exhibit that project metrics can be effectively leveraged in a RAG chatbot to provide useful, context-aware assistance to project managers.

Open-source software (OSS) development has become increasingly influential in the software industry, promoting collaboration and knowledge sharing among developers and users. Along with rapidly evolving OSS projects, this paper explores requirements engineering (RE) practices and challenges through a systematic literature review (SLR). Synthesizing data from 43 selected papers, the study reports practices, techniques, and methods that assist RE activities in OSS projects, and also addresses challenges faced by practitioners and the potential solutions. The results of the literature review indicate a growing interest in using machine learning and statistical methods to assist RE activities, focusing on automated requirements identification and analysis using information from project discussion forums, issue reports, and other online resources. The findings also highlight the importance of community involvement, with many studies examining developers’ interaction patterns, expertise levels, and influence on projects. These findings provide valuable insights for OSS project managers and researchers, offering guidance on effectively handling requirements in OSS projects.

Many countries all over the world are in the process of introducing programming into their K-12 curricula. New Finnish Curriculum includes programming mentioned especially in accordance with mathematics and crafts. Consequently, Finland needs to train teachers to teach programming at elementary school level. In this paper, we describe how elementary math teachers were educated online to teach programming using the Racket programming language. The aim of the course was to increase both content knowledge (CK) and technological pedagogical content knowledge (TPACK). By analyzing the course feedback, questionnaires and exercise data, we present the teachers’ views on the course and effects on their professional development (TPD). Finally, we describe development ideas for future online courses.

The ways in which informatics is covered in K-12 education vary among European countries. In Finland and Sweden, informatics is not included in the core curriculum, whereas, for example, in Lithuania, all students are exposed to some informatics concepts starting in the fifth grade. Bebras is an annually arranged international informatics contest for K-12 level, resulting in a large collection of data about contestants and their results. In this paper, we analyse contest data from the Finnish, Swedish and Lithuanian 2013 con- tests, focusing on students' performance on tasks related to algorithmic thinking. Our findings suggest that despite coming from different educational systems, students perform rather similarly on the tasks. The same tasks are difficult and the thinking behind picking an incorrect answer seems rather similar throughout the countries. The analysis also points out that there is a lack of easy questions -- this needs to be fixed in order to not risk scaring students away.

Software project education is an important part of software engineering studies in all universities. A well written final report gives an overview how the project went and what students have learned from the project. In this paper we analyze risks in 76 final reports from students' software projects from academic years 2006-7 and 2007-8. The projects were done in two Finnish universities. We recognized that four major risks are tools and skills to use the tools (61% of projects), technological problems (53%), scheduling problems (61%) and working or studying too many other courses during the project (45%). We also give guidelines to teachers and project managers to take into account the special nature of student projects.