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ThinkMind // IMMM 2011, The First International Conference on Advances in Information Mining and Management // View article immm_2011_7_10_20190
Exploiting Student Intervention System Using Data Mining
 Authors:
Samia Oussena
Hyensook Kim
Tony Clark Keywords: data mining; intervention system; student drop-out; game metaphore Abstract:
With the proliferation of systems that are put for the student use, data related to activities undertaken by the student are on the increasing. However, these vast amounts of data on student and courses are not integrated and could therefore not easily queried or mined. Therefore, relatively little data is turned into knowledge that can be used by the institution learning. In the work presented here, different data sources such as student record system, virtual learning system are integrated and analysed with the intention of linking behaviour pattern to academic histories and other recorded information. These patterns built into data mining models can then be used to predict individual performance with high accuracy. The question addressed in the paper is: how can indicators of problems related to student retention produced by data mining be presented in a way that will be effective. A prototype system that integrates data mining with an intervention system based on game metaphor has been build and piloted in the computing school. Early evaluations of the system have shown that it has been well received at all levels of the institution and by the students. Pages: 131 to 137 Copyright: Copyright (c) IARIA, 2011 Publication date: October 23, 2011 Published in: conference ISSN: 2326-9332 ISBN: 978-1-61208-162-5 Location: Barcelona, Spain Dates: from October 23, 2011 to October 29, 2011
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