A COMPARATIVE STUDY OF ACADEMIC ACHIEVEMENT AMONG BACHELOR OF SCIENCE STUDENTS IN THE FACULTY OF ALLIED HEALTH SCIENCES, THAMMASAT UNIVERSITY, BY TCAS ADMISSION ROUND

Abstract

This retrospective comparative quantitative research aimed 1) To study and compare the cumulative grade point average (GPAX) of undergraduate students in the regular program at the Faculty of Allied Health Sciences, Thammasat University, classified by the Thai University Central Admission System (TCAS) rounds: Round 1 (Portfolio), Round 2 (Quota), and Round 3 (Admission), and 2) To utilize these empirical data for planning student admission policies, determining the admission quota for each round, and designing academic support measures tailored to the potential of each student group. The sample consisted of 695 active students from the academic years 2021 - 2024 majoring in Medical Technology, Physical Therapy, and Sports Science and Exercise. Secondary data were collected through the Office of the Registrar, Thammasat University, at the end of the second semester of the 2024 academic year. Data were analyzed using descriptive statistics, one-way analysis of variance (One-way ANOVA), and Scheffé's method for pairwise comparisons. The results revealed that the admission rounds were significantly related to academic achievement (p < 0.001). At the overall faculty level, students admitted through the Admission round had the highest average GPAX (3.36). When classified by major, Medical Technology students from the Portfolio round achieved the highest average GPAX (3.52). Meanwhile, Physical Therapy and Sports Science and Exercise students from the Admission round attained the highest average GPAX at 3.53 and 2.93, respectively. The policy recommendations suggest that the faculty should maintain the proportion of students admitted through the Admission round as the core structure to uphold academic standards, alongside revising the selection criteria for the Portfolio and Quota rounds to be more rigorous. Furthermore, the research data can serve as an early warning system to design targeted academic support measures to reduce academic disparities and effectively enhance educational success opportunities for all students in the future.