Admission Criteria as Predictors of Licensure Performances among Graduates of a State University in the Philippine Cordillera Administrative Region
DOI:
https://doi.org/10.36941/ajis-2022-0157Keywords:
Admission criteria, licensure performance, High School Grade Point Average, Entrance examination, State Universities and Colleges, Cordillera Administrative RegionAbstract
Proficiency in licensure examinations has emerged as a foundation of pride for graduates and an attraction for potential students to higher education institutions (HEIs). Therefore, the purpose of this study was to uncover the admission criteria that confidently predicted the licensure performance of graduates of a state institution in the Philippine Cordillera Administrative Region. This study used correlation research and 654 randomly selected graduates of Ifugao State University (IFSU) who took and eventually passed their licensure tests. The records of the university registrar and the Professional Regulations Commission (PRC) were the primary sources of data. To comply with research ethics and standards, written permission from university officials was obtained. The mean, standard deviation, and frequency were used to describe the descriptive variables. Multiple regression analysis was utilized to identify the significant set of predictors of license performance per licensure examination. A stepwise procedure was used to select the best model. The study concludes that the performance of graduates in the fields of agriculture, criminology, and teacher education in their respective licensure examinations can best be predicted by their high school grade point average and admission test scores, whereas the performance of graduates in the field of forestry in their licensing exam is best explained by their performance in their secondary education curriculum.
Received: 25 August 2022 / Accepted: 20 October 2022 / Published: 5 November 2022
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.