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Development of predictive model in education system: using Naïve Bayes classifier

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dc.contributor.author Mavani, Monali
dc.date.accessioned 2024-05-08T07:02:15Z
dc.date.available 2024-05-08T07:02:15Z
dc.date.issued 2011-02
dc.identifier.uri https://dl.acm.org/doi/abs/10.1145/1980022.1980064
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/14763
dc.description.abstract With the advent of ICT (Information and Communication Technologies) education sector is also experiencing change in teaching process. Different mode of delivery with the use of ICT and digital content has made concept of E-learning and Blended learning more acceptable. But all the available technologies are not used with full potential, sometimes even not introduced at all. Business Intelligence (BI) is one of them. Educational sector also has got vast amount of data scattered in different forms which can be reused to make more intelligent decisions. Various data mining techniques are available which can be used in order to get intelligent information from educational data. Furthermore with the increasing awareness of benefits due to use of Open Source technologies it has become possible for educational institutes to use various technologies with low cost or no cost. In this paper we have used Open Source software Knime for predicting student's results using Naïve Bayesian Learner and Naïve Bayesian predictor. We also have used Moodle logs data of student's activities as one of the attributes in order to predict results using Naïve Bayes theory. en_US
dc.language.iso en en_US
dc.publisher ACM Digital Library en_US
dc.subject Computer Science en_US
dc.subject Business Intelligence (BI) en_US
dc.subject ICT (Information and Communication Technologies) en_US
dc.title Development of predictive model in education system: using Naïve Bayes classifier en_US
dc.type Article en_US


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