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Web Usage Mining for a Better Web-Based Learning Environment

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TLDR
Some data mining and machine learning techniques that could be used to enhance web-based learning environments for the educator to better evaluate the leaning process, as well as for the learners to help them in their learning endeavour are discussed.
Abstract
Web-based technology is often the technology of choice for distance education given the ease of use of the tools to browse the resources on the Web, the relative affordability of accessing the ubiquitous Web, and the simplicity of deploying and maintaining resources on the WorldWide Web. Many sophisticated web-based learning environments have been developed and are in use around the world. The same technology is being used for electronic commerce and has become extremely popular. However, while there are clever tools developed to understand online customer’s behaviours in order to increase sales and profit, there is very little done to automatically discover access patterns to understand learners’ behaviour on webbased distance learning. Educators, using on-line learning environments and tools, have very little support to evaluate learners’ activities and discriminate between different learners’ on-line behaviours. In this paper, we discuss some data mining and machine learning techniques that could be used to enhance web-based learning environments for the educator to better evaluate the leaning process, as well as for the learners to help them in their learning endeavour.

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Journal ArticleDOI

Educational Data Mining: A Review of the State of the Art

TL;DR: The most relevant studies carried out in educational data mining to date are surveyed and the different groups of user, types of educational environments, and the data they provide are described.
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Educational data mining: A survey from 1995 to 2005

TL;DR: This paper surveys the application of data mining to traditional educational systems, particular web- based courses, well-known learning content management systems, and adaptive and intelligent web-based educational systems.
Proceedings ArticleDOI

The State of Educational Data Mining in 2009: A Review and Future Visions

TL;DR: This paper reviewed the history and current trends in the field of EDM and discussed trends and shifts in the research conducted by this community, and discussed the increased emphasis on prediction, the emergence of work using existing models to make scientific discoveries, and the reduction in the frequency of relationship mining within the EDM community.
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Data mining in course management systems: Moodle case study and tutorial

TL;DR: This work describes the full process for mining e-learning data step by step as well as how to apply the main data mining techniques used, such as statistics, visualization, classification, clustering and association rule mining of Moodle data.
References
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Book

Data Mining: Concepts and Techniques

TL;DR: This book presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects, and provides a comprehensive, practical look at the concepts and techniques you need to get the most out of real business data.
Journal ArticleDOI

Web usage mining: discovery and applications of usage patterns from Web data

TL;DR: Web usage mining is the application of data mining techniques to discover usage patterns from Web data, in order to understand and better serve the needs of Web-based applications as mentioned in this paper, where preprocessing, pattern discovery, and pattern analysis are described in detail.
Proceedings ArticleDOI

Web mining: information and pattern discovery on the World Wide Web

TL;DR: This paper defines Web mining and presents an overview of the various research issues, techniques, and development efforts, and briefly describes WEBMINER, a system for Web usage mining, and concludes the paper by listing research issues.
Proceedings ArticleDOI

FreeSpan: frequent pattern-projected sequential pattern mining

TL;DR: Permission to make digital or hard copies of part or all of this work or personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear the full citation on the first page.
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