A Statistical Analysis for Predicting 2nd Year, 3rd Year and 4th Year College Grades Using Least Squares Linear Regression and Logistics Regression while Implementing and Iterative Error-Checking Framework

Abstract / Excerpt:

The College is one of the most important phases of a student. This phase, to some, is considered the final milestone in their education. A student in this phase naturally goes to a state-assessment from time to time, to check whether they are on the tight track. In this stage, self-assessment is one of the helpful ways in ensuring a smooth run in College. It cannot be stressed enough that decision-making in this stage is crucial. Some students are still undecided on what course or field of study they should take. This indecisiveness usually has bad consequences for them. Early dropout, forced to shift at the early years of college and dissatisfaction due to loss of interest within the field of study are among the common consequences they face. Aptitude tests are given to students in order to help them identify their strengths and weaknesses, but these kinds of tests give results on a shallow level. It does not test the knowledge acquired from a school setting. It does not relate to the past academic grades the student acquired. There needs to be another guide or process so that this indecisiveness will somehow alleviate or clear up. The study shows that with the student record of the Computer Science Division students of the Ateneo de Davao University, and accurate model for grades and passing rate is predictable through data mining concepts, statistical regression techniques and an iterative framework.

Source InstitutionAteneo de Davao University
UnitComputer Studies
AuthorsMark Jeo Doronila
Page Count6
Place of PublicationDavao City
Original Publication DateMarch 1, 2012