Adaptive Learning of Programming
Adaptive Learning of Programming is the research project that is being conducted by Adaptive Learning research group at the Masaryk University, Brno, Czech Republic. Their mission is to make learning more efficient and engaging by personalizing educational systems using artificial intelligence techniques.
Adaptive Learning research group develops applications that provide personalized learning experience by estimating students’ skills as they practice and recommending them tasks of the optimal difficulty. Suitable challenges, neither too easy, nor too difficult, help the students immerse themselves into the problem solving activity and achieve the state of flow.
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).
- Evaluation of educational systems (general methodological issues, specific case studies).
- Problem solving, difficulty of problems.
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.
Overview of main adaptive educational systems developed by Adaptive Learning research group (all systems are available in Czech, unless stated otherwise, some also in other languages):
|RoboMission||introductory programming game|
|Anatomy practice||Anatomy for medical students using high quality images from the Memorix textbook.|
|Poznávačka přírody||Nature quiz – practice of names of animals, trees, …|
|Umíme Matiku||Math practice.|
|Umíme Česky||Practice of Czech spelling and grammar.|
|Edulint||a Python linter designed to help beginning programmers learn better coding style (English only)|
|Umíme informatiku||introductory programming, computational thinking, digital technologies|
More information at fi.muni.cz/adaptivelearning/
- Beyond Binary Correctness: Classification of Students’ Answers in Learning Systems
- Exploration of the Robustness and Generalizability of the Additive Factors Model
- Impact of methodological choices on the evaluation of student models
- Design and Analysis of Microworlds and Puzzles for Block-Based Programming