@inbook{efab16423b1b4c7db6b0b3d543e0062a,
title = "Analyzing learner characteristics and courses based on cognitive abilities, learning styles, and context",
abstract = "Student modeling and context modeling play an important role in adaptive and smart learning systems, enabling such systems to provide courses and recommendations that fit students{\textquoteright} characteristics and consider their current context. In this chapter, three approaches are presented to automatically analyze learners{\textquoteright} characteristics and courses in learning systems based on learners{\textquoteright} cognitive abilities, learning styles, and context. First, a framework and a system are presented to automatically identify students{\textquoteright} working memory capacity (WMC) based on their behavior in a learning management system. Second, a mechanism and an interactive tool are described for analyzing course contents in learning management systems (LMSs) with respect to students{\textquoteright} learning styles. Third, a framework and an application are presented that build a comprehensive context profile through detecting available features of a device and tracking the usage of these features. All three approaches contribute toward building a foundation for providing learners with intelligent, adaptive, and personalized support based on their cognitive abilities, learning styles, and context.",
keywords = "Cognitive abilities, Context profile, Learning styles, Personalization, Student modeling",
author = "El-Bishouty, {Moushir M.} and Chang, {Ting Wen} and Renan Lima and Thaha, {Mohamed B.} and Kinshuk and Sabine Graf",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2015.",
year = "2015",
doi = "10.1007/978-3-662-44447-4_1",
language = "English",
series = "Lecture Notes in Educational Technology",
number = "9783662444467",
pages = "3--25",
booktitle = "Lecture Notes in Educational Technology",
edition = "9783662444467",
}