A Meta-Analysis of Instructional Management Model for Students’ Creative Thinking Development: An Application of Propensity Score Matching
Authors: Itsarangkul-Na-Ayutthaya Tanapat , Damrongpanit Suntonrapot 
Published: October 2022

<p style="text-align:justify">The research emphasized three main objectives: 1) to analyze the propensity score of the research effect size for developing students’ creative thinking, 2) to study the attribute variables effect of the research on the effect size of creative thinking before and after the propensity score adjustments, and 3) to compare the effect size between instructional methods to develop creative thinking before and after the propensity score adjustments. The data were obtained from 400 research studies on creative thinking development in Thailand. The research instrument for data collection included the research attribute record form. They were analyzed by calculating effect size, propensity score matching analysis, and fixed effect and random effect meta-regression analysis. The results indicated two research groups with propensity scores that develop students' creative thinking: the low effect size group of 256 research (<!--[if gte msEquation 12]><m:oMath><m:acc><m:accPr><m:chr
m:val="̅"/><span style='font-size:9.0pt;mso-ansi-font-size:9.0pt;
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mso-bidi-font-style:normal'><m:ctrlPr></m:ctrlPr></span></m:accPr><m:e><span
style='font-size:9.0pt;font-family:"Cambria Math",serif;mso-fareast-font-family:
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m:val="̅"/><span style='font-size:9.0pt;mso-ansi-font-size:9.0pt;
mso-bidi-font-size:9.0pt;font-family:"Cambria Math",serif;mso-ascii-font-family:
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mso-bidi-font-style:normal'><m:ctrlPr></m:ctrlPr></span></m:accPr><m:e><span
style='font-size:9.0pt;font-family:"Cambria Math",serif;mso-fareast-font-family:
"Times New Roman";mso-fareast-theme-font:minor-fareast;mso-bidi-font-family:
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EN-US;mso-bidi-language:AR-SA'><m:r><m:rPr><m:nor/></m:rPr>d</m:r></span></m:e></m:acc></m:oMath><![endif]--> =7.284) using 26 attribute variables of creative thinking development research. Moreover, the instructional methods with the creative activities had the highest effect size (<!--[if gte msEquation 12]><m:oMath><m:acc><m:accPr><m:chr m:val="̅"/><span
style='font-size:9.0pt;mso-ansi-font-size:9.0pt;mso-bidi-font-size:9.0pt;
font-family:"Cambria Math",serif;mso-ascii-font-family:"Cambria Math";
mso-hansi-font-family:"Cambria Math";font-style:italic;mso-bidi-font-style:
normal'><m:ctrlPr></m:ctrlPr></span></m:accPr><m:e><span style='font-size:
9.0pt;font-family:"Cambria Math",serif;mso-fareast-font-family:"Times New Roman";
mso-fareast-theme-font:minor-fareast;mso-bidi-font-family:Arial;mso-bidi-theme-font:
minor-bidi;mso-ansi-language:EN-US;mso-fareast-language:EN-US;mso-bidi-language:
AR-SA'><m:r><m:rPr><m:nor/></m:rPr>d</m:r></span></m:e></m:acc></m:oMath><![endif]--> =3.88). After the analysis of propensity score matching, the effect of 12 research attribute variables was eliminated as follows: manufacturing research institutions, year of publication, educational institutions, curriculum, creative thinking indicators, instructional materials, types of research, research objectives, research groups, research protocols, statistics used in research, quality of research and it was found that integrated instructional model of knowledge using media and technology had the highest effect size (<!--[if gte msEquation 12]><m:oMath><m:acc><m:accPr><m:chr
m:val="̅"/><span style='font-size:9.0pt;mso-ansi-font-size:9.0pt;
mso-bidi-font-size:9.0pt;font-family:"Cambria Math",serif;mso-ascii-font-family:
"Cambria Math";mso-hansi-font-family:"Cambria Math";font-style:italic;
mso-bidi-font-style:normal'><m:ctrlPr></m:ctrlPr></span></m:accPr><m:e><span
style='font-size:9.0pt;font-family:"Cambria Math",serif;mso-fareast-font-family:
"Times New Roman";mso-fareast-theme-font:minor-fareast;mso-bidi-font-family:
Arial;mso-bidi-theme-font:minor-bidi;mso-ansi-language:EN-US;mso-fareast-language:
EN-US;mso-bidi-language:AR-SA'><m:r><m:rPr><m:nor/></m:rPr>d</m:r></span></m:e></m:acc></m:oMath><![endif]--> =0.41).</p>