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Appraisal of Felder - Silverman Learning Style Model with Discrete Data Sets


Affiliations
1 Sathyabama University, Rajiv Gandhi Road, Jeppiaar Nagar, Chennai – 600119, Tamil Nadu, India
 

Objectives: E-learning is adapted to suit the different heterogeneous learners with different leaning styles. Felder and Silverman have given a catalogue of learning styles (FSLS). This paper is indented to analyze the reliability of their recommended learning styles. Method: Personalization is the latest improvement in E-learning system. Personalized E-learning system (PES) is suggested as the next generation of E-learning system. Various factors are analyzed to address the prediction of user's preferences. Learning styles is main deciding factor of personalizing E-leaning system. Most of the personalized models personalizing on learning styles have used FSLS. Previous research works performs the analysis of FSLS with single set of data. In this paper, the model is tested with two distinct of data using Karl's Pearson Coefficient method. To carry out analysis, adaption model is developed with FSLS using JAVA language. Findings: The observation of Appraisal of FSLS model states that it is strongly accepted by one set of data and there is small divergence in another set of data. Applications/Improvement: The study can be expanded with larger set of data and more than two distinct set of data.

Keywords

Learning Styles, Learning Style Preferences, Pearson Correlation Coefficient, Technology-Enhanced Learning
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  • Appraisal of Felder - Silverman Learning Style Model with Discrete Data Sets

Abstract Views: 180  |  PDF Views: 0

Authors

S. Muruganandam
Sathyabama University, Rajiv Gandhi Road, Jeppiaar Nagar, Chennai – 600119, Tamil Nadu, India
N. Srinivasan
Sathyabama University, Rajiv Gandhi Road, Jeppiaar Nagar, Chennai – 600119, Tamil Nadu, India

Abstract


Objectives: E-learning is adapted to suit the different heterogeneous learners with different leaning styles. Felder and Silverman have given a catalogue of learning styles (FSLS). This paper is indented to analyze the reliability of their recommended learning styles. Method: Personalization is the latest improvement in E-learning system. Personalized E-learning system (PES) is suggested as the next generation of E-learning system. Various factors are analyzed to address the prediction of user's preferences. Learning styles is main deciding factor of personalizing E-leaning system. Most of the personalized models personalizing on learning styles have used FSLS. Previous research works performs the analysis of FSLS with single set of data. In this paper, the model is tested with two distinct of data using Karl's Pearson Coefficient method. To carry out analysis, adaption model is developed with FSLS using JAVA language. Findings: The observation of Appraisal of FSLS model states that it is strongly accepted by one set of data and there is small divergence in another set of data. Applications/Improvement: The study can be expanded with larger set of data and more than two distinct set of data.

Keywords


Learning Styles, Learning Style Preferences, Pearson Correlation Coefficient, Technology-Enhanced Learning



DOI: https://doi.org/10.17485/ijst%2F2016%2Fv9i10%2F131455