The Linnaeus University Knowledge Environment Digital Transformations hosted the Fourth International Symposium on Digital Transformation (ISDT) from 17–18 September 2025 in Kalmar, Sweden. Following the precedent set in previous years, the symposium accepted 47 papers, organized around six themes: Digital Business (7), Digital Working Life (6), e-Health (7), Digital Learning and Education (10), Artificial Intelligence (6), and Digital Humanities (11). All abstracts underwent anonymous peer review, and authors were invited to revise their submissions based on feedback. Together, these contributions highlight the technical sophistication, methodological diversity, and societal relevance of contemporary research in digital transformation.

In addition to paper presentations, ISDT 2025 featured three keynote addresses that underscored the symposium’s scholarly and practical significance. Prof. Mato Brautović (University of Dubrovnik, Croatia) presented “Research as a political act: data access, power and the future of digital platform accountability”; Prof. Kathrin Creswell (University of Edinburgh, UK) discussed “Putting the UK at the forefront of using artificial intelligence for the benefit of health and care: a mixed methods formative evaluation of the NHS Artificial Intelligence Lab”; and Prof. Sarah Prestridge (Griffith University, Australia) examined “It’s an evolution not a revolution: examining digital learning that requires pedagogical change”. These keynotes provided conceptual anchors for the symposium, highlighting the societal, ethical, and pedagogical implications of digital transformation research.

Over two engaging days, participants explored emerging trends, current efforts, and innovative possibilities across the field. ISDT 2025 proudly welcomed researchers pursuing versatile and interdisciplinary approaches to societal challenges shaped by digitalization. The symposium emphasized not only methodological innovation but also the integration of theory and practice, demonstrating how design- and technology-oriented research can contribute to both academic knowledge and real-world applications.

We extend our sincere thanks to the Steering Committee of the Knowledge Environment Digital Transformations—Jesper Andersson, Kristoffer Holt, Päivi Jokela, Italo Masiello, Lina Nilsson, and Glenn Sjöstrand—for their guidance and support, as well as to Johan Vaide and Soumitra Chowdhury for planning assistance and Brian Kottonya for technical support. We are grateful to the administration of Linnaeus University for financial support via the internationalization fund, to the 19 reviewers who generously volunteered their time, and especially to the Communications Department at Linnaeus University for their support with the practical organization and logistics of ISDT 2025.

This study investigates the potential of prompt-based programming using generative AI, specifically large language models (LLMs), to support the development of computational thinking (CT) and programming skills in K-12 education. Through a series of workshops conducted with 9th-grade students in a Swedish public school, we compared two programming approaches: traditional block-based programming and prompt-based programming using a chatbot. Through a mixed-methods approach, we analyzed student performance across a range of algorithmic exercises, examined if the code delivered the requested output for each task, and assessed students’ self-reported engagement and learning outcomes. Results show that while block-based programming yielded higher success rates in the initial session, prompt-based programming surpassed BBP in later sessions in terms of success rate, particularly as task complexity increased and students became more familiar with prompt programming. Students reported higher engagement and perceived learning benefits when doing prompt-based programming. These findings suggest that prompt programming could have the potential of being a valuable complement to traditional programming methods, especially in supporting students with limited prior programming experience. However, further research is needed to explore how such tools can be effectively used in the classroom to foster genuine problem-solving skills and deep CT development.

Computational thinking (CT) is a fundamental cognitive skill that provides a problem-solving approach applicable across various domains. Integrating CT into K–12 education is crucial for developing the competencies that students need; however, its implementation presents significant challenges. While most research on CT has focused on specific areas and stakeholders, a more systematic and holistic approach is essential for successful integration. This paper, using a systems thinking theoretical lens, explores the complexities and interdependencies of this process, informed by 5 years of empirical research. Through the development of a detailed rich picture illustrating the integration, we identified four key dimensions as leverage points within the system: context and settings, stakeholders, theoretical and pedagogical strategies, and tools and approaches. These dimensions collectively shape the educational system for CT. This paper enriches the understanding of this integration by highlighting these leverage points, setting the stage for the application of additional systems thinking tools for integrating CT into education.

The EU funded Exten(DT)2 project explores how Design Thinking (DT) and emerging technologies have the potential to transform education. This study explores how Swedish students harnessed DT with ChoiCo to design choice-based games tackling media and information literacy related socio-scientific issues (SSI). Students immersed themselves in decision-making scenarios, demonstrating a powerful blend of creative expression and technological application. The intervention highlighted novel aspects of DT, notably fostering abstract reasoning and prompting critical reflection on societal values within simulated contexts. This efforts underscores the potential of innovative educational approaches, directly aligning with the Exten(DT)2 project’s goal of advancing Digital Transformation in education. To better integrate DT into SSI in education, this study focuses on key themes aimed at promoting pedagogical innovative digital transformation.

The integration of Artificial Intelligence (AI) in education has underscored the urgent need to equip educators with essential AI literacy and related competencies. This paper highlights the critical importance of advancing research on the development of teachers' AI literacy, particularly through targeted professional development (PD) programs. The study piloted a PD program involving 19 mid-career teachers in Singapore. Over six sessions, each lasting three hours, participants engaged in an intensive program designed to enhance their ability to integrate AI into educational practices. The program placed a strong emphasis on ethical considerations and the responsible use of AI. Mixed methods were employed. Data collection included pre-and post-intelligent Technological Pedagogical Content Knowledge (TPACK) surveys, teachers' perceptions on AI, in-class group discussions, and written assignments. Data analyses included content analysis and quantitative data analysis. The results showed a significant enhancement in i-TPACK, accompanied by a noteworthy shift in their overall perceptions of AI. The teachers not only acquired a good understanding of ethical frameworks but also demonstrated adept application in envisioning innovative AI in teaching, schools, and assessment. Importantly, they formulated tailored action plans for implementing AI in their respective schools. The study employed a novel analytical matrix based on the Aristotelian tripartite division of knowledge-episteme, techne, and phronesis-to compare action plans between teachers with different perceived i-TPACK levels, focusing on AI's application in teaching, schools and assessment. This study contributes valuable insights into teacher PD concerning AI in education and informs the implementation of AI in teaching practices.

In this paper we propose a comprehensive analytical pipeline that efficiently processes 1.5 million multilingual tweets about the Ukraine-Russia conflict, relying on multilingual NLP techniques and strategic sampling to produce interpretable sentiment and emotion visualizations. By incorporating temporal and geospatial metadata as multimodal information, our approach reveals complex emotional patterns: filtering predominantly neutral content highlights fear (often over 60%) and anger (10–25%) as dominant emotions, with temporal analysis showing negative sentiment surges during crises. Geographically, conflict zones are fear-dominant, while Western democracies and state-influenced systems exhibit mixedemotional profiles; visualizations further demonstrate how national data can obscure media outlet polarization. Crucially, we enhance explainability by analyzing confusion matrix patterns to identify emotionally ambiguous or surprising predictions, such as fear being frequently assigned to neutral or positive content indicating pervasive underlying emotional currents. The outcomes of our work offer advanced, multimodal, and interpretable tools for analyzing large-scale discursive phenomena.

From previous research, it can be inferred that students already show their capabilities in developing and applying characteristics of computational thinking (CT) in a variety of educational settings at a very young age. Unfortunately, less attention appears to be paid to students with special educational needs, learning disorders, developmental disadvantages, or students suffering from other limitations who can benefit from acquiring and applying skills attributed to CT from an diversity and inclusion perspective. Remarkably in this context, it is reflected from practical experience that students with special needs can achieve high CT performance, but this is not always reflected in curricula, facilities or available learning and testing methods. This is despite growing evidence showing that CT activities are ideally suited for students with learning disabilities and specific educational needs, where unplugged and technology-enhanced CT learning applications can act as reinforcing elements. To capture opportunities, as well gaps and unexplored areas regarding facilitation of CT for students with special educational needs, an inventory survey was therefore conducted in six different countries in primary education and childcare. This to identify perceptions of headmasters/managers regarding the implementation possibilities of CT in curricula, whether and how teachers/child attendants have already integrated CT into their teaching, and what activities are available in schools/child centers to facilitate CT development. Despite the fact that CT enables a development of both generic and specific skills from which all students can benefit, our survey revealed when it concerns teaching, learning and acquiring CT-skills, the pedagogical provision is often not attuned to specific needs of students, and the educational offer is often approached from a purely didactic perspective in order to teach specific (digital) skills for programming. Moreover, students sometimes appear excluded from CT activities based on their personal requirements; that such activities are only reserved for excellent students, or where facilities are not optimal. This is notable because managers and teachers/childcare workers indicate they believe it is important to integrate CT practices into schools, and developing CT-skills can equip students with skills for our future society. It also becomes apparent that, although materials for facilitating CT development are frequently available, they are often incompletely used, or teachers/childcare workers are not sufficiently equipped to use them effectively. Our survey also reveals that the assessment of CT seems to be insufficiently attuned to specific needs and required preferences of students to make concise statements on the demonstrated added value of CT for learning and development. It also appears that teachers are often still unfamiliar with the possibilities that CT contains, or teachers are insufficiently equipped to teach or integrate CT into a development-oriented provision. It is further indicated for teachers, childcare workers and staff it is important to receive training on diversity and inclusion. The results of our exploration shed light on the development, implementation, testing and training for new forms of pedagogy in primary education and childcare, and for professionalization of managers, teachers and childcare workers regarding a developmental focus on CT for children with special educational needs.

As artificial intelligence (AI) becomes increasingly integrated into daily life, understanding how young people perceive and emotionally respond to this technology is crucial to leverage AI in novel ways to make education more meaningful and inclusive. This study explores K-12 students from South East Sweden and their sentiments toward AI by analyzing open-ended responses from 183 participants aged 9 to 16 years. Sentiment analysis of the collected data, using both VADER and TextBlob algorithms, revealed a broad spectrum of attitudes, ranging from enthusiastic optimism to explicit distrust. A linear regression analysis examined demographic predictors of sentiment scores, identifying a modest but significant effect of gender and age at first phone acquisition. Male K-12 students expressed more negative sentiments compared to female K-12 students, while students who received their first phone at an older age tended to hold slightly more positive views of AI. These findings indicate that factors such as early exposure to technology and gender influence adolescents' emotional responses to AI. This underscores the importance of addressing emotional and affective aspects in AI literacy programs and research. To deepen our understanding, future studies should broaden sentiment analysis to capture students' perspectives on ethical issues including fairness, bias, and accountability in AI systems. Such an approach will provide a more comprehensive view of how young people engage with both the opportunities and challenges presented by emerging AI technologies.

In this abstract we present and discuss the central themes of a collaborative research project that examines the role of emotional mobilization in shaping democratic discourse and enhancing societal resilience amidst ongoing digital transformation. In today’s increasingly fragmented and hybrid media landscape, emotionally charged narratives—particularly those propagated by populist actors via alternative media and social platforms (Holt, 2023)—frequently challenge evidence-based communication, thereby contributing to heightened polarization and a decline in public trust. With the continued rise of populist and far-right political movements, it is crucial to understand how to elicit emotional engagement with active citizenship and forms of democratic deliberation. While emotional appeals are often portrayed as antithetical to rational deliberation, they may also serve as catalysts for democratic engagement, social cohesion, and civic participation. Our research questions how emotional narratives in the media may interact with and challenge evidence-based communication in democratic discourse, what role emotional mobilization has in shaping user engagement, polarization and trust in journalistic expertise, and how can an understanding of affective mobilization contribute to building more resilient, inclusive and trustworthy democratic communication practices.The core ideas that guide our research emerge from a collaboration between the A Questioned Democracy and Digital Transformations Knowledge Environments at Linnaeus University. Our research approach adopts an intermedial and cross-disciplinary methodology to analyse the interplay between emotional and factual appeals across diverse media ecologies (for the emotional turn in media studies, see Wahl-Jorgensen, 2019). Drawing on digital media content from Sweden—including alternative news sites, mainstream journalism, and social media platforms—the study combines computational methods (e.g., sentiment and network analysis), qualitative approaches (e.g., discourse and frame analysis), and participatory workshops to investigate how emotions and facts co-constitute public discourse (Acheampong et al, 2021).By moving beyond the conventional dichotomy between reason and emotion, the project seeks to advance a more nuanced understanding of affective dynamics in digital communication. In doing so, it contributes to ongoing debates on democratic resilience by examining how emotional mobilization can both distort and strengthen deliberative processes. The broader objective is to inform the design of inclusive, trustworthy, and emotionally attuned communication strategies—particularly within a European context characterized by epistemic uncertainty, algorithmic amplification, and rising populist influence (Moffitt, 2016).Although the project ideas described above are in currently in their early stages, this presentation will outline its conceptual underpinnings, research design, and collaborative framework. Emphasis will be placed on the methodological challenges and opportunities associated with studying affect, evidence, and trust in an intermedial, data-rich environment. The expected outcomes range from strengthening democratic resilience through improved media practices, informing public communication strategies that balance reason and affect, and developing educational resources and policy recommendations to enhance societal trust in democratic institutions and knowledge systems.