Conducted by PIT
, Started on 2023 -
Completed on 2024
Completed
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Performance of each SUC in the licensure examination for teachers is one of the factors
for the program accreditation to be accredited as the center of development and
excellence and also may contribute to the overall performance of each university. This
study aimed to identify the relationship and predict the LET performance of PIT
Tabango Teacher Education graduates based on identified factors. Descriptive –
correlational was used and the intention of creating a linear model for predicting LET
performance. The respondents of the study were the 78 PIT Tabango the teacher
education graduates from 2015-2019. The results show that all three factors are
significant predictors of LET performance, as indicated by their extremely low p-values
(p < 0.001). Among these, Professional Education has the highest coefficient estimate
(0.40045), making it the most influential predictor of LET performance. Specialization
Subjects follows closely with a coefficient estimate of 0.39985, indicating that subject
matter expertise in either mathematics or science is also a critical factor in predicting
LET performance. The model's R2 value of 1.000 indicates that the regression model
perfectly explains the variability in LET performance. Professional Education is the most
significant predictor of LET performance, closely followed by Specialization Subjects,
with General Education playing a smaller but still important role. The linear regression
model, incorporating all three factors, provides a highly accurate prediction of
graduates' overall performance in the Licensure Examination for Teachers. It is highly
recommended that curriculum that curriculum planners and program chairs may
consider revisiting the curriculum and faculty development committee may develop
comprehensive plan to retool the BSED mathematics faculty for an updated knowledge
of the future trends and the education 5.0.