Factors Affecting Problem Solving Abilities of Mathayomsuksa 3 Students in the Mathayomsuksa Educational Service Area 24 : Multilevel Analysis
Main Article Content
Abstract
The objectives of this research were to study student-level factors and Classroomlevel factors affecting to Problem Solving Abilities and to construct predictive of Problem
Solving Abilities of Mathayomsuksa 3 Students under the Mathayomsuksa Educational Service
Area 24 by a multilevel analysis. The samples size consisted of 1,062 Mathayomsuksa 3 student
using two stage cluster random sampling. The research instruments comprised two types of
measures ; 1) a 4-multiple-choice test : a intelligence quotient test and a problem solving
abilities test and 2) a 5-scale-rating measure : a achievement Motivation, a emotional
quotient, a environment teaching support in household, a climate in classroom and a
efficiency teaching. Statistics for analyses of the collected data were basic statistical,
Multiple correlation Analysis and Multiple Multilevel Regression Analysis.
The results of this research were as follows :
1) The student-level factors affected to Problem Solving Abilities of Mathayomsuksa 3
Students under the Mathayomsuksa Educational Service Area 24 at the Statistical Significance
level of .05 were Intelligence Quotient (IQ), Emotional Quotient (EQ) and Achievement
Motivation (MOT). These student-level factors revealed the variance of Problem Solving
Abilities with 62.40 percent. (R2 = .624)
2) The classroom-level factors affected to Problem Solving Abilities of
Mathayomsuksa 3 Students under the Mathayomsuksa Educational Service Area 24 at the
Statistical Significance level of .05 were Climate in classroom (CLI). The Climate in classroom
(CLI) factors revealed the variance of Problem Solving Abilities with 99.80 percent. (R2 =
.998)
3) The predictive equations of the student-level factors and classroom-level
factors affecting to the Problem Solving Abilities of Mathayomsuksa 3 Students under the
Mathayomsuksa Educational Service Area 24 obtained by multilevel analysis could be
constructed in raw and standard score equations as below:
Micro-level Analysis
Y/ = 20.765 + 1.110IQ + .628MOT + .864EMO
ZY / = .730ZIQ + .062ZMOT + .077ZEMO
Macro-level Analysis
β0j = 20.765 + 3.944CLI
Zβ/ij = .673ZCLI
Article Details
The content and information contained in the published article in the Journal of Educational Measurement Mahasarakham University represent the opinions and responsibilities of the authors directly. The editorial board of the journal is not necessarily in agreement with or responsible for any of the content.
The articles, data, content, images, etc. that have been published in the Journal of Educational Measurement Mahasarakham University are copyrighted by the journal. If any individual or organization wishes to reproduce or perform any actions involving the entirety or any part of the content, they must obtain written permission from the Journal of Educational Measurement Mahasarakham University.