Your browser doesn't support javascript. This means that the content or functionality of our website will be limited or unavailable. If you need more information about Vinnova, please contact us.

Proof of concept of an adaptive learning system for engineering students

Reference number
Coordinator Crash Course Sverige AB
Funding from Vinnova SEK 1 700 000
Project duration May 2024 - May 2025
Status Ongoing
Venture Ground-breaking technology solutions
Call Groundbreaking and scalable technology solutions in 2024

Purpose and goal

The aim of the project is to develop an adaptive learning system (ALS) for engineering students, with the aim of improving their productivity, motivation and engagement in their studies. We create a personal tutor, KAI, that adapts to the student´s individual needs and offers an interactive learning experience. By using advanced AI technology and collaborating with student associations and teachers, we aim to increase the throughput and depth of knowledge of engineering students, thereby addressing national educational challenges.

Expected effects and result

The expected effects and results of the project include increased student engagement and motivation, faster learning and higher throughput. Students will achieve a deeper understanding of the course material, leading to higher score and better well-being. For teachers, this means increased class engagement and insights into student progress with minimal extra effort. Universities benefit from lower dropout rates and improved academic standards, strengthening their reputations and budgets.

Planned approach and implementation

The project is divided into four phases. First, the foundations are established with course selection and engagement of key partners. Then the first version of the KAI is developed and tested with feedback from students. In the third phase, a detailed prototype of the study plan is created with rigorous testing and evaluation. Finally, the study plan is launched operationally and the scalability is assessed. Collaboration with student associations, faculty and AI experts is critical to success, with a focus on ease of use and continuous development.

External links

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 14 June 2024

Reference number 2024-00476