TOWARDS THE ELABORATION OF A META­MODEL UNIFYING LEARNING STYLES

The question of how to enhance the interest and motivation of adolescents has gained increasing prominence [1] especially in secondary mathematics [2]. Students

To do so, we rely on the highly accurate candidate mappings generated in the first step of the ServOMap matching process, the lexical similarity computing

Finally, in order to show that any effects of interface preferences were related to matching with the user’s cognitive style rather than just a preference for any adaptive interface,

Background and Objectives: This paper presents the results of a Machine- Learning based Model Order Reduction (MOR) method applied to a complex 3D Finite Element (FE)

MDLChunker represents them using sets of initial symbols or features called hereafter canonical chunks (in the example of section 2, this is the initial alphabet used

Domain knowledge in the form of deep knowledge of the relationships be- tween different features, the nature of the data, the difficulty and cost of labelling as well as

Therefore, we chose a within-subject design where the participants complete the comprehension task using both risk modeling notations for two different application scenarios (OB

Three modules were created for the implementation of the LMPAELS AM: (i) the Learner Groups Module, (ii) the Topic Sequence Module, and (iii) the Course Content Adaptation Module.