
Project
Reasoning machine in social science
There is an increasing demand for personalized education within society
and a lot of evidence that such an approach could increase education
effectiveness (Bloom, 1984; Brusilovsky & Peylo, 2003). This project is
aimed to create more efficient Adaptive learning systems (ALS) with the use
of the process data, for example, response times (RT; Maris & Van der
Maas, 2012; van der Linden & Glas, 2000).
I will explore how response time could be integrated into different
approaches to measure students abilities with both simulations and data
from the industry. I will start with researching the characteristics of the
estimates resulting from ELO and Urnings rating systems. Later on I wish I
could work with different types of the process data, eye-movement, use of
hints. I hope to contribute to the knowledge of how personalized hints and
feedback are constructed.
The project will support better implementation of personalized learning
throughout society as well as contribute to psychometric society with both
innovative methodology and the well-documented open code software.
Supervisors
Prof. Dr. Jeroen Vermunt
Dr. Maria Bolsinova
Dr. Matthieu Brinkhuis
Financed by
Tilburg University
Period
1 October 2024 – 31 September 2028