Research project WASP-ED work area 4: Pedagogical development and learning analytics
Recent developments in AI affect us in many ways, also in higher education. The research project "WASP-ED work area 4: Pedagogical development and learning analytics" is a part of the national WASP-ED program which aims to increase AI capability and capacity in Sweden.
The purpose of the Wallenberg AI and Transformative Technologies Education Development (WASP-ED) program is to significantly increase the capability and capacity of Swedish universities in providing timely, relevant, and scalable education in AI and other transformative technologies.
The program is led by Fredrik Heintz (Linköping University). Within the WASP-ED program, Teresa Cerratto Pargman (Stockholm University) in collaboration with Olga Viberg (KTH) are responsible for work area 4 which is focused on pedagogical development and learning analytics. Cerratto Pargman is the leader for WP4, and Viberg is the co-leader for WP4.
This work area puts efforts into building a community around artificial intelligence (AI) and pedagogy issues to better understand the university teachers’ needs to develop AI competence. We will provide a guiding framework for contributing to nurturing responsible learning analytics and AI practices in Sweden.
Our work aims to contribute to:
- Mapping teachers’ perceptions of AI in university practices
- Guiding framework for responsible learning analytics and AI practices
- Cultivating community building
Project description
The expected impact of the WASP-ED program is a national step-change in the quality and quantity of available competence in artificial intelligence (AI) and the capability of addressing the need for such competence also for coming transformative technologies. Further impact on the international level is expected as WASP-ED is very well aligned with the increasing activities in Europe and elsewhere related to the need for up-skilling and reskilling.
In the work area that we conduct on pedagogy, we understand that to scale up and scale-out education in AI, and related transformative technologies, there is a need to provide a solid pedagogical, and educational basis. By providing this, emerging data-driven practices involving learning analytics systems or/and AI can ultimately lead to improved learning and teaching at scale.
More info on the people and universities that we collaborate with in the program
Project members
Project managers
Teresa Cerratto-Pargman
Professor
