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Business intelligence in e-learning: Case study on the Iran University of Science and Technology DataSet

Falakmasir, M. H ; Sharif University of Technology | 2010

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  1. Type of Document: Article
  2. Publisher: 2010
  3. Abstract:
  4. Nowadays, e-learning platforms are widely used by universities and other research-based and educational institutions. Despite lots of advantages these educational environments provide for organizations, yet there are many unresolved problems which cause instructors and training managers with some difficulties to get proper information about the students' learning behavior. On one hand, lack of tools to measure, assess, and evaluate the performance of learners in educational activities has led the educators to fail to guarantee the success of learning process. On the other hand, strict structure of learning materials prevents students to acquire knowledge based on their learning style. Consequently, developing tools monitor and analyze the learner's interaction with e-learning environment is necessary. Business intelligence (BI) and On Line Analytical Processing (OLAP) technologies can be used in order to monitor and analyze the learner's behavior and performance in e-learning environments. They can also be used to evaluate the structure of the course content and its effectiveness in the learning process. This article investigates the use of business intelligence and OLAP tools in e-learning environments and presents a case study of how to apply these technologies in the database of an e-learning system. The study shows that students spend little time with course courseware and prefer to use collaborative activities, such as virtual classroom and forums instead of just viewing the learning material
  5. Keywords:
  6. Business intelligence ; Collaborative activities ; Course contents ; Courseware ; Data sets ; E-learning environment ; E-learning platforms ; Educational activities ; Educational data mining ; Educational environment ; Educational institutions ; Intelligent data analysis ; Learning behavior ; Learning materials ; Learning process ; Learning Style ; OLAP ; On-line analytical processing ; Science and Technology ; Training managers ; Virtual Classroom ; Curricula ; Data mining ; Data reduction ; Data warehouses ; E-learning ; Hand tools ; Knowledge based systems ; Research ; Societies and institutions ; Software engineering ; Students ; Teaching ; Learning systems
  7. Source: 2nd International Conference on Software Engineering and Data Mining, SEDM 2010, 23 June 2010 through 25 June 2010 ; June , 2010 , Pages 473-477 ; 9788988678213 (ISBN)
  8. URL: http://ieeexplore.ieee.org/document/5542876