DALAN: A Course Recommender for Freshmen Students using a Multiple Regression Model

Abstract

It is challenging for the institution to provide students with ideas about courses or programs to pursue. This study aims to propose a tool that employs multiple regression to forecast incoming college students’ courses at Notre Dame of Midsayap College. The proponents developed a prediction model based on the identified predictors and Cumulative Semestral Grade Point Average of all College of Information Technology and Engineering students from the first semester of S.Y. 2013-2014 to S.Y. 2015-2016, using the ex post facto method. The necessary variables were Entrance Exam results, High School Grade Point Average, and Cumulative Semestral Grade Point Average. Also, Pearson’s R correlation was used to determine the relationship between EE and HSGPA to CSGPA. Conclusively, this study supported the notion that EE and HSGPA considerably impact CSGPA. Additionally, the developed predictive model was considered appropriate for course recommendation.