TY - GEN
T1 - Representative characteristics of felder-silverman learning styles
T2 - IADIS International Conference on Cognition and Exploratory Learning in Digital Age, CELDA 2006
AU - Graf, Sabine
AU - Viola, Silvia Rita
AU - Kinshuk,
AU - Leo, Tommaso
PY - 2006
Y1 - 2006
N2 - Learning styles are more and more incorporated in technology enhanced learning and a lot of research work is done in this area. For example, systems are developed which provide adaptivity according to the learning styles of students; relationships to students' performance and other characteristics of students such as cognitive traits are investigated, and techniques are designed to derive the learning styles from the behaviour of students during an online course. The more information about learning styles is available and the more detailed the description of learning styles is, the better such approaches can work and can be investigated. The aim of this paper is to analyse data about learning styles with respect to the Felder-Silverman learning style model (FSLSM), in order to provide a more detailed description of the learning style dimensions. Therefore, we used linear discriminant analysis in order to detect the most representative characteristics of learning styles as represented in the gathered data. Furthermore, we analysed how representative these characteristics are for the specific learning style dimensions. For cross-validation, we conducted empirical frequencies analysis as well as correlation analysis. As a result, we provide a more detailed description of the learning style dimensions of FSLSM. This description is especially important when learning styles are incorporated in technology enhanced learning.
AB - Learning styles are more and more incorporated in technology enhanced learning and a lot of research work is done in this area. For example, systems are developed which provide adaptivity according to the learning styles of students; relationships to students' performance and other characteristics of students such as cognitive traits are investigated, and techniques are designed to derive the learning styles from the behaviour of students during an online course. The more information about learning styles is available and the more detailed the description of learning styles is, the better such approaches can work and can be investigated. The aim of this paper is to analyse data about learning styles with respect to the Felder-Silverman learning style model (FSLSM), in order to provide a more detailed description of the learning style dimensions. Therefore, we used linear discriminant analysis in order to detect the most representative characteristics of learning styles as represented in the gathered data. Furthermore, we analysed how representative these characteristics are for the specific learning style dimensions. For cross-validation, we conducted empirical frequencies analysis as well as correlation analysis. As a result, we provide a more detailed description of the learning style dimensions of FSLSM. This description is especially important when learning styles are incorporated in technology enhanced learning.
KW - Data mining
KW - Felder-Silverman learning style model
KW - Learning styles
KW - Student models
UR - http://www.scopus.com/inward/record.url?scp=79960367034&partnerID=8YFLogxK
M3 - Published Conference contribution
AN - SCOPUS:79960367034
SN - 9781627483315
T3 - IADIS International Conference on Cognition and Exploratory Learning in Digital Age, CELDA 2006
SP - 235
EP - 242
BT - IADIS International Conference on Cognition and Exploratory Learning in Digital Age, CELDA 2006
Y2 - 8 December 2006 through 10 December 2006
ER -