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Web Usages Mining in Automatic Detection of Learning Style in Personalized e-Learning System

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Proceedings of the Fifth International Conference on Fuzzy and Neuro Computing (FANCCO - 2015)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 415))

Abstract

The e-learning system generates huge amount of data which contain hidden and valuable information and they are required to be explored for useful knowledge for decision making. Learner’s activity related data and all behavioral vis-a-vis navigational data are stored in the log files. Extracting knowledgeable information from these data by using Web Usage Mining technique is a very challenging and difficult task. Basically, there are three steps of Web Usage Mining i.e. preprocessing, pattern discovery and pattern analysis. This paper proposes a Dynamic Dependency Adaptive Model (DDAM) based on Bayesian Network. This model mines learner’s navigational accesses data and finds learner’s behavioral patterns which individualize each learner and provide personalized learning path to them according to their learning styles in the learning process. Result shows that learners effectively and efficiently access relevant information according to their learning style which is useful in enhancing their learning process. This model is learner centric but it also discovers patterns for decision making process for academicians and people at top management.

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Acknowledgments

We would like to show our gratitude towards the Prof. (Dr.) S.P. Lal Director, Birla Institute of Technology, Mesra, Ranchi (Patna) for sharing their pearls of wisdom with us during the course of this research.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, Ranchi (Patna), India

    Soni Sweta & Kanhaiya Lal

Authors
  1. Soni Sweta
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  2. Kanhaiya Lal
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Corresponding author

Correspondence to Soni Sweta .

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Editors and Affiliations

  1. IDRBT, Center of Excellence in Analytics, Hyderabad, India

    Vadlamani Ravi

  2. Dept of Electrical Engineering, IIT Delhi, Delhi, Delhi, India

    Bijaya Ketan Panigrahi

  3. Indian Statistical Institute, Electronics and Communication Sci Unit, Kolkata, India

    Swagatam Das

  4. Div of Ctrl & Instrumentation, Nanyan Technological Univ, Singapore, Singapore

    Ponnuthurai Nagaratnam Suganthan

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Sweta, S., Lal, K. (2015). Web Usages Mining in Automatic Detection of Learning Style in Personalized e-Learning System. In: Ravi, V., Panigrahi, B., Das, S., Suganthan, P. (eds) Proceedings of the Fifth International Conference on Fuzzy and Neuro Computing (FANCCO - 2015). Advances in Intelligent Systems and Computing, vol 415. Springer, Cham. https://doi.org/10.1007/978-3-319-27212-2_27

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  • DOI: https://doi.org/10.1007/978-3-319-27212-2_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27211-5

  • Online ISBN: 978-3-319-27212-2

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