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Title: Factors Supporting Southern Thailand Matayomsuksa 6 (High School) Students' Decisions to Further their Studies
Authors: Utayanwutigul, Napaporn 
Ngamcharoen, Sucheep 
Kaewnate, Kanokphan 
Akrawutpornpat, Suwaroj 
Issue Date: 2012
Publisher: Chulalongkorn University Printing House
University of the Thai Chamber of Commerce
Source: Napaporn Utayanwutigul, Sucheep Ngamcharoen, Kanokphan Kaewnate, Suwaroj Akrawutpornpat (2012) Factors Supporting Southern Thailand Matayomsuksa 6 (High School) Students' Decisions to Further their Studies. University of the Thai Chamber of Commerce Journal Vol.32 No.2.
Journal: University of the Thai Chamber of Commerce Journal 
Abstract: The status of students' admission/enrollment in government and private universities are highly competitive. This research aims to find out factors supporting Matayomsuksa 6 students in Southern Thailand in making their decision to select study in universities, and to incorporate their reasons for public relations planing to recruit the number of students required. The samples were selected by 2-staged sampling: random province in the first stage, and proportional random student selection from each province in the second stage. Eighteen hundred and eighty-eight students responded to a questionnaire rating four factors on the basis of 1-10 as follows:- 1. An individual inspired the student to further their studies. 2. The reasons for the decision. 3. Reasons for faculty selection. 4. Sources of information. These data were analyzed and found that:- (a) The average value of factors used in the study is high in all aspects. (b) Average grade in the 4 provinces is different. (c) Whether or not the students are dissatisfied with the faculty in which they enrolled. (d) Whether students are interested/disinterested in selecting a private university? (e) Factor analysis reveals the Southern Thailand Matayomsuksa 6 (High School) students' decision to continue their studies has six new factors. The six new factors, including gender, GPA, High school program, province and average family monthly income were analyzed by Logistic Regression. It was found that the variables in education can be grouped and correctly classified about 57.2%.
ISSN: 0125-2437
Rights: This work is protected by copyright. Reproduction or distribution of the work in any format is prohibited without written permission of the copyright owner.
Appears in Collections:JEO: Journal Articles

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