I'm currently working on creating 'smart' learning environments. These environments can provide contextualized and personalized feedback to students, and adapt themselves to the student's level.

This work involves a number of challenges;

• reliably recognizing and classifying mistakes in students' learning artifacts (e.g. hypotheses, concept maps)
• providing automated feedback that is specific and encourages students to reflect on their mistakes
• extracting useful information (indicators) from a semi-structured event stream (logbook), and building a student model that accurately reflects the students' development
• matching learning content that is likely to have the highest impact learning gains to individual students

Publications

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• Communication Science

• Educational Science and Technology

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.

 

• 202100031 - Big data & network analysis (R)

• 202100031 - Big data & network analysis (R)

Organisations

• Faculty of Behavioural, Management and Social Sciences (BMS), BMS - Laboratory (LAB)