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Idiosyncratic applications of data mining in E learning environments

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documents in English
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  1. Abstract
  2. Introduction
  3. E-learning
  4. Data mining in E-learning
  5. Applications of data mining in elearning
    1. Discovering interestingness of symmetric association rules in educational data
    2. Analysis of automated chat to understand and support the inquiry learning process
    3. Discovering student preferences in E-learning
    4. Classifying students on the basis of usage of data and their final marks
  6. Conclusion
  7. References

Data Mining is a very popular and effective way of discovering new knowledge from large and complex data sets. Its benefits are its ability to gain deeper understanding of the patterns previously unseen using current available reporting capabilities. Internet education arose from traditional education in order to cover the necessities of remote students and/or help the teaching-learning process, reinforcing or replacing traditional education. In our context we call this internet education as E-Learning. In E-Learning large amounts of information describing the scale of teaching and learning interactions are generated endlessly and are universally available. By applying data mining techniques in E-learning, it would be of great use in enriching the management with precious information and knowledge that would escort to efficient decision-making. Data Mining can be used to extract knowledge from E-Learning systems through the analysis of the information available in the form of data generated by their users. Keywords: Data Mining, E-Learning, Knowledge Management

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