Efficiency Comparison of Two TCAS Minimum Mark Prediction Models: Top X% Model and Mean+N(s.d.) Model for Admission Round of TCAS in Year 2023

Abstract

Thai university Central Admission System (TCAS) is developed for all high school students in Thailand. There are four rounds of TCAS called, portfolio, quota, admission and direct admission. The admission round is the round that use the mark of each test subject to compute the total mark, and then apply to TCAS. The minimum mark that can qualify the admission is the main point. However, the last year minimum mark cannot be used directly because of changing of subject combination, changing of fraction of the subject combination and the difficulty of the tests in each year. Otherwise, in year 2022, there are major changes in test subjects of TCAS. These lead to the prediction is more difficulty. The used of last year minimum marks directly are not efficient method because of its low accuracy. The researchers have developed two models called “Top X% model” and “Mean + N(s.d.) model” to predict the minimum mark. This paper represents the concept and methodology of each model, each model efficiency and compare their efficiency. The results show clearly that “Top X% model” is better than “Mean + N(s.d.) model” in term of model accuracy and error prediction average. The results also show that the prediction accuracy of “Top X% model” and “Mean + N(s.d.) model” for all four universities in year 2023 are 78.6744% and 75.5043%, respectively, with acceptance of the prediction total mark error not exceed -5%.