Likelihood Estimation Of Passing The Licensure Examination For Teachers (Let) Using Multivariate Method

Abstract

The main objective of the research was to determine the main components where BS Secondary Education Graduates (BSEG) should focus on their undergraduate academic subjects in preparation for the LET. The researchers used the Logistic Regression (LR) procedure in STATA using the grades of the 138 BSEG from 2010-2014. The dependent variable represents the result whether or not the BSEG has passed the LET. Five predictors were used; three were continuous and were transformed to be normally distributed. This was done so as to yield meaningful interpretations after the method. The transformed variables were the average grades in (1) basic non-mathematics subjects, (2) basic math subjects, and (3) Professional Education subjects. The other two were indicators of (4) the gender of the BSEG as well as (5) their majors, where math is in focus. The results showed that of the five predictors, only the education subjects and gender were significant. The outcome was then used to build an LR Model. It also implies that the education subjects, being a component in LET, must be given greater essence by the Teacher Education Institution, other stakeholders, and ultimately, future LET takers in order to have a better chance of becoming professional teachers especially on the first take. This paper can serve as a guide in remodeling curricula as well since notably, while the General Education Subjects provide aspiring teachers more knowledge in other fields, it is not tantamount to gaining higher probability of passing the professionalization.