We address the problem of transferring information learned from experiments to a different environment, in which only passive observations can be collected. We introduce a formal ...
Kernels are two-placed functions that can be interpreted as inner products in some Hilbert space. It is this property which makes kernels predestinated to carry linear models of l...
We present the machine learning framework that we are developing, in order to support explorative search for non-trivial linguistic configurations in low-density languages (langua...
IMS Learning Design (LD) is a specification that aims at computationally representing any learning process. However, the possibilities of LD to represent collaborative learning sce...
This paper describes a novel method to create a quantitative model of an educational content domain of related practice item-types using learning curves. By using a pairwise test t...
Philip I. Pavlik Jr., Hao Cen, Kenneth R. Koedinge...