Adaptive Learning group is a small, but enthusiastic research lab at Faculty of informatics, Masaryk university.
Mission
Make learning more efficient and engaging by personalizing educational systems using artificial intelligence techniques.Main Research Themes
- Student modeling, domain modeling (based on students' answers estimate student knowledge and/or structure of the domain).
- Instructional policies (algorithms for selection of appropriate questions/problems for a particular student).
- Design and evaluation of learning environments (general methodological issues, specific case studies).
- Introductory programming, problem solving, difficulty and complexity of tasks.
Motivation
The goal of adaptive learning is to make educational system personalized, so that they can adapt to needs of a particular students. Adaptive learning is very interesting area at the intersection of basic research and wide ranging applications.
Research: The adaptive behaviour is based on mathematical models, these models are often constructed and evaluated using machine learning techniques. The most relevant research forums to our work are: Educational Data Mining, Artificial Intelligence in Education, Intelligent Tutoring Systems, our work has also connections to statistics, machine learning, psychometrics, cognitive science, ...
Applications: Our research has direct widespread application. As part of our research, we are developing systems that are used by thousands of users. Research questions that we study are relevant to many non-profit and commercional large scale systems, e.g., Khan Academy, Duolingo, MOOCs, Carnegie Learning, Reasoning Mind, Math Whizz, ...