In this paper, we review the paradigm of inductive process modeling, which uses background knowledge about possible component processes to construct quantitative models of dynamic...
Will Bridewell, Narges Bani Asadi, Pat Langley, Lj...
Developing a learner model containing an accurate representation of a learner’s knowledge is made more difficult in distributed learning environments where the learner uses mult...
Christopher A. Brooks, Mike Winter, Jim E. Greer, ...
Recently, opening the learner model to the learner it represents has become more common in adaptive learning environments. There have also been systems that allow instructors acces...
Susan Bull, Andrew Mabbott, Abdallatif S. Abu-Issa
In this paper we use genetic programming for changing the representation of the input data for machine learners. In particular, the topic of interest here is feature construction i...
Visualization techniques are commonly used in computer science, particularly for understanding the interactions intrinsic in the object-oriented paradigm. The visualization effect...