Learning analytics for teachers and students (OPEN UNI), Summer 2026

After participation in the course: - Students knows definitions, goals, stakeholders, applications of learning analytics (LA) and artificial intelligence (AI) use in educational contexts - Is aware of the possible advantages and challenges of data-based technologies in education ​- Students can analyze the use of LA and AI as a support for learning, teaching and guidance. - Students know different purposes and pedagogical approaches for using LA with different stakeholder groups. - Students can critically evaluate the limitations of data use and improve data literacy skills. - Students get competencies to design, utilize and evaluate LA use as part of different pedagogical processes. - Students can design and use LA for teaching and guidance in their own working environments. ​

Study Methods Online-course: recorded lectures, independent work in Moodle environment, synchronous learning and demo sessions Teaching Methods Student can complete the course with flexibility, varying from 1 credit to 5 credits. The criteria for completeing different amount of credits is described in the beginning of the course. 5 credits course: Lectures and guided learning 24 hours, independent and group work 110h, in total 134h.

You can complete the course with a scope of 1-5 credits. The study fee is 100 euros despite the scope of completed studies. The course is implemented in co-operation with the Faculty of Information Technology and Electrical Engineering.

​​Study material consist of course literature and timely scientific articles that will be announced during the course​. Charles Lang, George Siemens, Alyssa Friend Wise, Dragan Gašević, Agathe Merceron (Eds.). 2022. Handbook of Learning Analytics (2nd. ed.). SoLAR, Vancouver, BC. DOI: 10.18608/hla22.

Assessment methods and criteria: Participation in online teaching, completion and sharing of learning analytics assignments. Assessment of learning outcomes will be done based on the students’ course products, assignments and/or portfolio that student produces during the course.  

Anni Silvola, Satu Tamminen, Danyu Yang

Pass/fail