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Research on Digital Learning

Illustration: Malin Strihagen

The Digital Learning research group analyzes the opportunities and challenges that technologies bring to education, teaching, and learning. We are studying how technologies are used, how teachers use technology, and how they contribute to the development of learning processes, methods, and technologies that can be used in practice.

Digital technologies are reshaping education. Our research group critically explores the circumstances under which learning and teaching are supported by such technologies across diverse contexts. We bring together researchers and doctoral students with pedagogical and technical expertise to study different technologies in educational settings and develop prototypes and methods that advance our understanding of digital learning. Our work also contributes to improving the quality of digital education at KTH.

Our research investigates how digital technologies shape learning and teaching in schools, higher education, and beyond, from in-person classrooms to fully online environments, including technology-intensive and post-digital environments. We are particularly recognized for our expertise in communities of inquiry, collaborative learning environments, online tutoring, and futures of education. Our research addresses how students collaborate and how emerging tools, such as artificial intelligence (AI), can be used in education now and in the future. Ultimately, we aim to create knowledge that informs teaching and learning, and the design of high-quality learning environments.

Projects

GRADE research consortium

The GRADE Research Consortium brings together nine Swedish universities to provide a joint doctoral education environment focused on how the ongoing digitalization of society affects education. In total, more than 50 doctoral students have either completed their dissertations or are currently active within the consortium.

Math coach online

Math Coach Online is a free service where students studying primary and secondary school mathematics courses can receive support with their mathematics studies from university students. The service is staffed by future mathematics teachers and engineering students who have all completed training in online tutoring.

How is presence supported at a distance?

– A mixed-methods study of municipal adult distance education

This project builds on the Community of Inquiry framework, which addresses how to reduce isolation by supporting social, cognitive, and teaching presence in distance education. The aim is to investigate students’ sense of presence in Swedish municipal adult distance education and to identify factors that support or hinder student achievement.

Transforming engineering education with multimodal genAI and intelligent agents for improving students’ problem-solving skills

This project aims to develop and evaluate a pedagogically aligned virtual teaching assistant powered by large multimodal models to support problem-solving with physical systems in real-world settings for engineering education. 

Generative AI and Adult Education 

This project explores how generative AI can support educational practices in the Swedish folk high school and study association system. Through participatory action research, the project involves teachers, developers, and leaders in testing and analyzing AI tools in real learning environments. The aim is to understand how generative AI can enhance participation, create new learning opportunities, and be implemented ethically and pedagogically.

Doctoral student projects

Education Research and Fiction: The Case of Artificial Intelligence in the Future of Education

This research uses education fiction as speculative narratives to approach the (im)possible futures that artificial intelligence creates for higher education. Through empirical data analysis and theoretical contributions, this thesis takes a futures-focused approach to the current issue of AI implementation in education.

Higher education students (voluntarily) studying together

With my PhD project I aim to contribute to the understanding of higher education students’ practices of (voluntarily) studying together with peers; as well as, how studying together is meaningful to higher education students.

Mapping Patterns in Engineering Communities of Inquiry

The PhD project aims to validate the Communities of Inquiry framework within the specific context of blended engineering education. Purposeful research methods are employed in accordance with the project’s objectives to identify underlying patterns within the Communities of Inquiry in engineering higher education environments.

Publications 

[1]
T. Karunaratne and E. Lindblad, "Imagining assessment futures through artificial intelligence in higher education teachers’ perspectives," Discover Education, vol. 4, no. 1, 2025.
[2]
T. Karunaratne, N. (. Aghaee and M. Ferati, "Harnessing the Generative AI Wave Towards Fair and Diverse Higher Education Assessments : A Comprehensive Analysis through an Innovative Lens of Students," in Proceedings of the 24th European Conference on e‑Learning, 2025, pp. 456-464.
[3]
N. Aghaee, T. Karunaratne and J. Bandelin, "Co-Designing Gamified Learning for Soft Skills : A Participatory Future Workshop," in Proceedings 24th European Conference on e‑Learning (ECEL 2025), 2025, pp. 1-10.
[4]
I. Gidiotis and S. Hrastinski, "Beyond the story : a three-lens analysis of education fiction," Learning, Media & Technology, 2025.
Full list in the KTH publications portal

Members of the research group

Contact persons 

Stefan Hrastinski
Stefan Hrastinski professor
Stefan Stenbom
Stefan Stenbom associate professor

We work in the research group

Patricia Cirera Diaz
Patricia Cirera Diaz research engineer
Fredrik Enoksson
Fredrik Enoksson researcher
Iosif Gidiotis
Iosif Gidiotis doctoral student
Malin Jansson
Malin Jansson assistant professor, research engineer
Thashmee Karunaratne
Thashmee Karunaratne associate professor
Richard Lee Davis
Richard Lee Davis assistant professor
Marcus Lithander
Marcus Lithander researcher
Hanna Skarelius
Hanna Skarelius
Malin Strihagen
Malin Strihagen doctoral student, research engineer
Jeongin Yoon Blomstervall
Jeongin Yoon Blomstervall doctoral student

Alumni

Eva-Lena Forslind
Tiina Leino Lindell
Emma Riese
Kathy Tian