Mid Sweden University

Generative artificial intelligence (GenAI) has shown a strong potential to automate tasks, increase productivity, and enhance software quality. Managers have an important role in adopting GenAI as they lead strategic planning and team coordination. This study examines the software engineering tasks that managers consider suitable for large language models (LLMs), as well as the role of management and education in software engineering practices. The study reviews current applications in practice and explores the challenges encountered during implementation. We conducted a workshop with managers from diverse organizations to collect insights on the growing use of LLMs in areas such as code development, debugging, documentation, and training. The discussion highlighted several key concerns, including intellectual property issues, quality assurance, and integration difficulties. Overall, our findings suggest that LLMs can potentially transform software engineering practices if technical and organizational challenges are carefully addressed. 

The gender distribution in computer science (CS) education remains uneven, with a persistent underrepresentation of women. One challenge in improving diversity is that many women choose non-technical tracks in high school, and therefore often lack the required mathematics qualifications for STEM educations. The purpose of this study was to investigate gender differences in performance and challenges in an introductory programming course and examining the impact of prior experience. The course is part of a CS program with a balanced gender ratio and relatively low mathematical prerequisites compared to similar programs in Sweden, allowing students with backgrounds in social sciences, economics, or humanities to apply. Bringing in students from diverse academic backgrounds may offer valuable perspectives and contribute to a broader understanding of computer science. The study was based on observations, a survey, and longitudinal statistics of student performance. Our analysis showed that women and men passed the course at equal rates, and struggled with similar learning barriers, regardless of their prior knowledge in mathematics. However, prior experience in programming may have played a role in grade differences, with men tending to achieve higher average grades. These findings raise interesting questions about whether lowering entry requirements, particularly in mathematics, could be a viable approach to improving gender balance in computer science education. 

In the present narrative analysis, we explore how coworking in a rural context is understood by stakeholders and members in relation to ideas on centre/periphery. Coworking, encompassing a variety of activities, is mostly understood as an urban phenomenon in practice and research. There is a gap in the literature when it comes to how coworking spaces in rural settings are made sense of by stakeholders and members. Here, these understandings specifically will be explored in relation to a theoretical framework on centre/periphery. That is, the dichotomisation of urban-rural is here understood as a social construct implying an urban norm where what is defined as the centre is made sense of as preferable in relation to what is defined as the periphery. Stories of coworking in rural settings are explored through narrative analysis. Based on interviews with 15 persons in northern Sweden, the analysis shows that coworking in rural settings was made sense of in relation to three different storylines, presented as vignettes. From the results of the narrative analysis, we discuss perspectives on centre/periphery and how these concepts can deepen and contribute with further nuances for the understanding of coworking in rural conditions.

Computer science is a higher education domain that still show a significant male dominance. Many research studies have highlighted the importance of diversity and gender balance in computer science related areas such as software engineering and system development. However, there is still a well-identified problem that university programmes and courses on computer science fail to attract the female audience. The objective of this study is to investigate the concept of gender-inclusive computer science (CS) education with the aim of broadening participation in CS courses and programs. This is conducted through a literature study, initially focusing on keywords and research areas, and subsequently searching into existing research. The research question that guided the study was: "What concepts can be found in literature to make computer science education more gender-inclusive?". Data were analysed thematically in a two-step analysis process inspired by the grounded theory methods of Open coding and Axial coding. Findings suggest that there is significant room for learning in this field, particularly from Critical CS education studies. The Open coding analysis showed that the findings can be categorised into eight main themes. In the Axial coding the themes were merged, refined, renamed, and centred around the main axial theme of 'Epistemological pluralism'. Other essential themes that all are related to the axial main theme were: 'Design and creativity', 'Bias awareness and ethics', 'Collaboration and communication', 'Self-regulated learning', 'Real-world applications', and 'Role models and mentorship'. The result of this study is presented through a visual model that illustrates essential aspects of inclusive computer science education. The paper also proposes various directions for future research.

The rapid growth of software industry highlights the importance of the education system in producing competent professionals to meet industry demands. Previous research has identified a gap between industry needs and the content of educational programs. This study presents Vocational Education and Labour Market Analyser (VELMA), a tool designed to extract information from job ads and educational curricula (both from Sweden), utilising topic modelling to identify the diverse technologies and skills in demand within the industry and those covered by professional education. Particularly, we use Latent Dirichlet Allocation (LDA) to categorise keywords into cohesive themes for document frequency analysis. Our findings highlight industry demand for skills in cloud and embedded technologies, security engineering, and software architecture. In contrast, the Higher Vocational Education (HVE) curricula emphasise the education of web developers and general object-oriented programming languages. 

In this concluding chapter, we point to themes that emerge from the chapters in this book on sustainable networked learning. The themes cut across different sections of the book, indicating their broader significance. These themes are the lasting effects of lockdown online teaching; Digital sustainability for the future; Future roles of networked learning in society; Balancing utopia and dystopia in visions of AI and open data; Speculative methods in research, education and design; and Balancing qualitative and quantitative data in the research of networked educational settings: Studies at the community and project levels.

The present book has emerged from the 13th International Conference on Networked Learning (NLC, 2022), held 16–18 May 2022 at Mid-Sweden University, Sundsvall, Sweden. The conference had a high number of interesting, high-quality research papers, which made it a difficult task to select papers to be further developed into chapters for this book. To aid our editorial decisions, in the final plenary session of the conference, we encouraged the delegates to discuss what themes and ideas they had found most interesting and/or thought-provoking during the many presentations. Comments were collated on an online board (a padlet), creating a rich plethora of potential focal points for this volume. With this as the outset, we found a set of overarching themes that each encompassed a sufficient number of papers corresponding to delegates’ articulated interests. From there, the process leading to the present collection included several rounds of reviews and revisions through which authors of the chosen papers further developed their contributions.

In software engineering research, academia-industry collaboration is predominantly understood as partnerships between academic institutions and large companies. Small and Medium-sized Enterprises (SMEs) are vital contributors to the industry, and they are numerous. Their unique preconditions and challenges differentiate their collaboration dynamics from larger corporations. We seek to identify guiding principles and practices for initiating collaborations between researchers and SMEs. Through a meta-synthesis approach drawn from two systematic literature reviews, we introduce a collaborative model canvas. This emphasizes the importance of SMEs’ business contexts and the relationships between researchers and SMEs. Our research offers insights for those looking to collaborate with SMEs, considering potential challenges and limitations.

The present book has emerged from the 13th International Conference on Networked Learning (NLC, 2022), held 16–18 May, 2022 at Mid-Sweden University, Sundsvall, Sweden. The conference had a high number of interesting, high-quality research papers, which made it a difficult task to select papers to be further developed into chapters for this book. To aid our editorial decisions, in the final plenary session of the conference, we encouraged the delegates to discuss what themes and ideas they had found most interesting and/or thought-provoking during the many presentations. Comments were collated on an online board (a padlet), creating a rich plethora of potential focal points for this volume. With this as the outset, we found a set of overarching themes that each encompassed a sufficient number of papers corresponding to delegates’ articulated interests. From there, the process leading to the present collection included several rounds of reviews and revisions through which authors of the chosen papers further developed their contributions.

Learning Analytics (LA) is an established field of research and prac-tice. Yet, there is still scarce evidence of LA on improved learning and teaching. In this regard, researchers highlight a need to involve not only students but also teachers in the development of LA systems to ensure that LA is implemented effectively. Earlier research has pointed out several ethical issues that are im-portant to consider when designing and using LA services. Ethics are interrelated with stakeholders’ values since the values represent things that are seen as im-portant to individuals. These values are rarely considered when designing LA systems; it is problematic since it may influence the design and the implementa-tion of effective LA solutions in a negative way. The aim of this study is therefore to explore which values teachers consider important in relation to LA systems to be used in higher education. The selected and adapted set of envisioning cards was used during an online workshop with 11 teachers. The results indicate that there are several critical values that are important for teachers in relation to LA systems, including variation, personalization, flexibility, insight, transparency, efficiency, and trust. By taking these values into consideration when designing LA systems, teachers’ needs can be better met in the setting of higher education.