Latent Profile Analysis of the Graduate Characteristics in the Education 4.0 of Rajabhat University in Thailand
Journal: International Journal of Science and Research (IJSR) (Vol.7, No. 10)Publication Date: 2018-10-05
Authors : Sunan Siphai; Ketkanok Wannawan;
Page : 931-936
Keywords : Latent Profile Analysis; indicators; exploratory analysis; confirmatory factor analysis; Graduate characteristics in Education 40;
Abstract
This research aimed to analyze the Latent Group Profile, hereafter (LPA) of the graduate characteristics in the Education 4.0. of 2, 148 students. The research instrument was a set of 24 items questionnaire focusing on the graduate characteristics in Education 4.0. The research findings indicated that the LPA had 3 models, and the numbers of the groups in each model were 2, 3 and 4, respectively. When considering the probability that the classification was the most accurate (E_k), it was the model with 3 groups (likelihood = -3883.156, AIC = 7794.312, BIC = 7873.718, ABIC = 7829.238, E_k = 0.816). The proportion of the students in the LPA group 1 was 243 (54.36 %). The LPA group 2 was 1, 167 (54.36 %) and the LPA group 3 was 737 (34.33 %). Overall of the 3 components were at the statistical significance at the level of.01 in every member in the LPA group that means every component can be used to characterize the graduates of Rajabhat University in the Education 4.0 in all profile groups. The forecast accuracy was at 81.60 % and in each LPA group, the Corporate Social Responsibility (CSR) was the important indicator.
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