Publication Type : Conference Paper
Publisher : 2018 IEEE International Conference on Computational Intelligence and Computing Research
Source : 2018 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), IEEE, Coimbatore, India (2018)
Url : https://www.scopus.com/record/display.uri?eid=2-s2.0-85057960788&origin=resultslist
Keywords : Analysis, Data Mining, Educational Data Mining, Framework, Grit, Programming Language, Student performance
Campus : Mysuru
School : School of Arts and Sciences
Department : Computer Science
Year : 2018
Abstract : In the current era, the knowledge of programming language provides a greater fortune in the career of students'. This paper is on students' centric approach for analyzing their performance, improvisation in the programming language such as in C, C++, and Java. For the fetching knowledge extraction from the educational field, Educational Data Mining is used. Hence, the study helps in empowering grit level in students' to enrich themselves towards success based on their performance. The general survey, technical concepts based test, logical and reasoning based test is collected using Google forms. The model is framed based on the survey and test data set to know the slow learner student's in academic. The proposed model identifies the student's based on analyzing them better, than only considering internal marks and assessment conducted. The framework provides greater efficiency in identifying the right students' for analysis and validated based on entropy value. The model is beneficial to the students' to improvise their weaker concept with frequent faculty assistance and also provide greater advantage to the university.
Cite this Research Publication : Vinayak C. Hegde and Sushma Rao H., “A Framework to Analyze Performance of Student's in Programming Language Using Educational Data Mining”, in 2018 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), Coimbatore, India, 2018.