PLATO researchers explore (i) academic domain learning processes or results and (ii) their relation to internal (mental) or external (physical/digital) information representations (iii) at one, two, or across multiple levels (iv) using multiple time scales (in real time, over time) and (v) in specific domains, starting with the well-defined domains economics and physics, then, progressively including mathematics, computer science and medicine, and finally, expanding to less well-defined domains such as sociology.
To explore the theoretically expected interactions and (causal) relations among (i)-(v), we are conducting a four-year panel study to continue preliminary projects as well as a technological project to integrate (big) educational data computationally and enable cross-format analyses. On this basis, predictive models of student learning will be developed.
- Research Area A: Information and Learning Landscape
- Research Area B: Individual Learning
- Research Area C: Learning in Groups and Systems