Pre FIC: Predict ability of Faculty Instructional Performance through Hybrid Prediction Model

1. L.Coburn,“StudentEvaluationofTeacherPerformance,”ERICClearinghouse on Tests Measurement and Evaluation Princeton NJ,1984.
[Online].Available:http://ericae.net/edo/ed289887.htm.
2. C. W. Tsai, C. F. Lai, H. C. Chao, and A. V. Vasilakos, “Big dataanalytics:asurvey,”J.BigData,vol.2, no.1,pp.1–32,2015.
3. A. Savaliya, A. Bhatia, and J. Bhatia, “Application of Data
MiningTechniquesinIoT:AShortReview,”Int.J.Sci.Res.Sci.Eng.Technol.,vol.4,no.2,pp.218–223,2018.
4. M.Brilliant,DwiHandoko,andSriyanto,“Implementationof DataMining Using Association Rules for Transactional Data Analysis,”
3rdInt. Conf.Inf.Technol.Bus.,pp.177–180,2017.
5. M. Zaffar, M. Ahmed, K. S. Savita, and S. Sajjad, “A Study of FeatureSelection Algorithms for Predicting Students Academic
Performance,”Int. J.Adv.Comput.Sci.Appl.,vol.9,no. 5,pp.541–549,2018.
6. L.Jing,“DataMiningandKnowledgeManagementinHigherEducation,”inAnnualForumfortheAssociationforInstitutionalResearch,2002,pp
.1–18.
7. P.N.P.Maya,J.R.Aguilar,R.A.Zamora,andJ.M.Barron,“Predictive Model Design applying Data Mining to identify causes ofDropout in
University Students,” Strateg. Technol. Soc., vol. 7, no. 2,pp.11–39,2018.