A Novel Approach for Faculty Appraisal in Educational Data Mining using CLEMENTINE TOOL
Ramakrishna Gandi1, Prathimarani Palla2, Madhuri Thimmapuram3, Daniel Prasanth T4
1Ramakrishna Gandi, Department of CSE, Vignan’s Institute of Information Technology, Visakhapatnam (A.P), India.
2Prathimarani Palla, Department of CSE, Vignan’s Institute of Information Technology, Visakhapatnam (A.P), India.
3Madhuri Thimmapuram, Department of CSE, Vignan’s Institute of Information Technology, Visakhapatnam (A.P), India.
4Daniel Prasanth T, Department of CSE, Vignan’s Institute of Information Technology, Visakhapatnam (A.P), India.
Manuscript received on 15 April 2016 | Revised Manuscript received on 25 April 2016 | Manuscript Published on 30 April 2016 | PP: 200-206 | Volume-5 Issue-4, April 2016 | Retrieval Number: D4538045416/16©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Data mining, the concept of unseen predictive information from big databases is a powerful novel technology with great potential used in various commercial uses including banking, retail industry, e-commerce, telecommunication industry, DNA analysis remote sensing, bioinformatics etc. Education is a required element for the progress of nation. Mining in educational environment is called Educational Data Mining. Educational data mining is concerned with developing new methods to discover knowledge from educational database. In order to analyze opinion of students about their teachers in Professor Appraisal System, this paper surveys an application of data mining in Professor Appraisal System & also present result analysis using CLEMENTINE 12.0 tool. There are varieties of popular data mining task within the educational data mining e.g. classification, clustering, outlier detection, association rule, prediction etc. How each of data mining tasks can be applied to education system is explained. In this paper we analyze the performance of final Faculty Appraisal of a semester of a computer engineering department, Vignan Institute of Information Technology College of engineering & is presented the result which it is achieved using CLEMENTINE 12.0 tool. We have verified hidden patterns of Faculty Appraisal by students and is predicted that which Faculty will be invited to faculty classes and which Faculty will be refusing and department heads due to Appraisal reasons will ask explanations with them.
Keywords: Classification, Clustering, Association rule, Data mining, Appraisal, CLEMENTINE 12.0.
Scope of the Article: Classification