A Framework for Creating, Training, and Testing Self-Organizing Maps for Recognizing Learning Styles

Dynamic Learning Style Prediction Method Based on a Pattern Recognition Technique

“…The adaptive educational system [9] uses the fieldindependent/-dependent cognitive style to construct a learner profile and this allows the learning process to be adapted to different learners. The INSPIRE system [10] uses the Honey-Mumford learning style to construct learner profiles, while the iWeaver system [11] their personalized learning services [12], [13], [14], [15], [16], [17], [18], [19], [20], [23], [24], [27], [28].…”

“…Compared with questionnaires, automatic detection can obtain more accurate information because the data are acquired dynamically in the current learning environment. Many useful techniques are available for the automatic detection of learning styles, such as neural networks [13], Bayesian networks [14], rule-based reasoning [15], [27], classifiers [28], and data mining [16]. These techniques abstract the typical learning behaviors from human-computer interaction processes, which can represent the characteristics of different learning style preferences.…”

“…Garcia et al [14] proposed the use of Bayesian networks to predict learning style preferences by constructing conditional probability tables for the learning behaviors and different learning style dimensions. Zatarain-Cabada et al [13] used neural networks to predict learning style preferences by training a sevenneuron network using sample questionnaire data obtained from learners and their specific learning behaviors. AHA!…”