Sensor Measures of Motivation for Adaptive Learning (SensoMot)
A research project granted by the Federal Ministry of Education and Research (BMBF) within the program “Tangible Learning”
Motivation is one major factor for facilitating deep learning processes. Motivation makes learning fun and interesting, and results in improved learning success. If motivational problems are detected early on, learning processes can be modified and learning content can be adapted to the needs of the learner.
Goals and Procedure
The goal of the research project „SensoMot“ is to predict critical motivational conditions using sensor measures. By deriving adaptive mechanisms, the learning process can subsequently be tailored to the motivational needs of the learner. Objective measures of the learner – indicating e.g. stress or boredom – will be collected using wearable devices. Afterwards, algorithms of the learning environment will subsequently adjust internal variables like the learning speed. Prototypical adaptive learning scenarios for the university course “Nanotechnology” and a distance learning course “Mechanical Engineering” will be implemented and evaluated. The resulting learning systems will be made available to a broad variety of educational applications as soon as possible.
Innovation and Perspectives
For the first time ever, “SensoMot“ will facilitate detecting motivational obstacles in the way of learning with the help of unobtrusive sensors, and adapt learning content accordingly. Learning motivation increased in such a way could lead to greater learning success and lower dropout rates in a wide range of technology-based learning situations.
Coordinator of the sub-project “Motivational Indicators and Adaptation Algorithms (MotAdapt)“
Prof. Dr. Thomas Martens
Coordinator of Project Cluster
Herr Michel Dorochevsky
1.8 million € (74% of which funded by the BMBF)
01.04.16 until 31.03.19