Discovering Enhanced Pedagogical Practice Using Data Mining Techniques for Evaluation of Programming Language Teaching

Authors(2) :-M. Ramla, M. Ramesh

Evaluating the performance of teachers is a crucial aspect in the effective running of an institution. Teachers are knowledge creators and should be knowledgeable too. Although there are several analytical tools that help in this assessment, this paper especially focuses on the teaching evaluation for programming courses for the computer science subjects. The primary objective is to apply classification techniques to the prediction of performance of teachers. A survey with 150 students of BCA degree of SRM Institute of Science and Technology was made. The various fitting attributes contributing to the performance are identified. A predictive classification model has been built using different classifiers in python and results are tabulated.

Authors and Affiliations

M. Ramla
Department of Computer Applications, SRM Institute of Science and Technology, Chennai, Tamil Nadu, India
M. Ramesh
Department of Computer Science, SRM Institute of Science and Technology, Chennai, Tamil Nadu, India

Teaching Evaluation, Predictive model, classification, Educational Data Mining

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Publication Details

Published in : Volume 2 | Issue 6 | November-December 2017
Date of Publication : 2017-12-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 869-871
Manuscript Number : CSEIT1726245
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

M. Ramla, M. Ramesh, "Discovering Enhanced Pedagogical Practice Using Data Mining Techniques for Evaluation of Programming Language Teaching", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 6, pp.869-871, November-December-2017.
Journal URL : http://ijsrcseit.com/CSEIT1726245

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