Departments of Instructional Technology, and Research Methods, Measurements and Data Analysis.
Research on '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