Web Log Pre-processing and Analysis for Generation of Learning Profiles in Adaptive E-learning

Pai, Radhika M. and Kolekar, Sucheta V. and M., Manohara Pai M. (2016) Web Log Pre-processing and Analysis for Generation of Learning Profiles in Adaptive E-learning. EAI Endorsed Transactions on e-Learning, 3 (10): 4. ISSN 2032-9253

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Abstract

Adaptive E-learning Systems (AESs) enhance the efficiency of online courses in education by providing personalized contents and user interfaces that changes according to learner’s requirements and usage patterns. This paper presents the approach to generate learning profile of each learner which helps to identify the learning styles and provide Adaptive User Interface which includes adaptive learning components and learning material. The proposed method analyzes the captured web usage data to identify the learning profile of the learners. The learning profiles are identified by an algorithmic approach that is based on the frequency of accessing the materials and the time spent on the various learning components on the portal. The captured log data is pre-processed and converted into standard XML format to generate learners sequence data corresponding to the different sessions and time spent. The learning style model adopted in this approach is Felder-Silverman Learning Style Model (FSLSM). This paper also presents the analysis of learner’s activities, preprocessed XML files and generated sequences.

Item Type: Article
Uncontrolled Keywords: Web Log Analysis, Felder-Silverman Learning Style Model, Adaptive E-learning Systems, XML, Data Pre-processing, Sequences, Adaptive User Interface
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor I.
Date Deposited: 17 Sep 2020 10:26
Last Modified: 17 Sep 2020 10:26
URI: https://eprints.eudl.eu/id/eprint/425

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