A Quality Assessment of Science Instructional Management in Basic Education Schools: An Application of a Value–added Model and Differential Item Functioning

Tuksino, Prakittiya; Kanjanawasee, Sirichai; Pasiphol, Shotiga

doi:10.18848/1447-9494/cgp/v17i05/47024

Cited by 3 publications

(3 citation statements)

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“…The results of factor loading of identified factors and their indicators in the growth mindset model imply that all the factors and indicators are important constructs to grow school administrators' positive mindset. Hence, all the key factors and their indicators are fit well with empirical data at a statistically significant level (Tuksino, 2009). In this line of reasoning, researchers concluded all the factors and indicators appear to be consistent with either growth mindset theory (Dweck, 2006) or previous research studies (DeWitt, 2020;Elmore, 2019;Meador, 2019).…”

Section: Discussionsupporting

confidence: 72%

Developing Factors and Indicators of Growth Mindset for School Administrators in Thailand

Masalee¹,

Ariratana²,

Sirisooksilp³

2021

IER

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The sustainability of educational administration is depending on school administrators’ growth mindset. A growth mindset is detected to have a direct relationship with school achievement and success. Despite being an integral part of school leadership, the growth mindset of school administrators has been ignored by past researchers. Hence, this research is designed to investigate the growth mindset’s significant factors and indicators of high school administrators in Thailand. The researchers employed a quantitative approach survey design. A total of 460 school administrators and teachers participated in a survey using a multi-stage sampling technique. The researchers intended to test whether the identified factors and indicators are fitting with empirical data as the ultimate research outcome. The results revealed that there are a total of 17 indicators derived from the six factors in a growth mindset model. The measurement model of growth mindset is corroborated to the empirical data, with χ2=64.875, df=50, χ2/df=1.2975, CFI=0.99, TLI=0.99, RMSEA=0.02, and SRMR=0.01. In conclusion, the developed growth mindset model for high school administrators has a goodness-of-fit with the attained data. Finally, the results of this research have successfully proposed a measurement model that would be guidelines for school administrators to grow their positive mindset as our major contribution to the educational administration field.

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Section: Discussionsupporting

confidence: 72%

Developing Factors and Indicators of Growth Mindset for School Administrators in Thailand

Masalee¹,

Ariratana²,

Sirisooksilp³

2021

IER

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“…The significant results of this study are related to the status of the standard factor loading of every factor in the PKM to enhance the effectiveness of the TLM model. These results were supported by Tuksino (2009) who revealed that all the recognized factors and indicators of the measurement model conformed perfectly at a significant level of 0.01 with the empirical data. As a result, researchers concluded that all the 10 vital factors and their 30 indicators are important variables and seem to be in corresponding to both theory and literature review.…”

Section: Discussionsupporting

confidence: 68%

Personal Knowledge Management to Enhance the Effectiveness of Teacher Learning Management in Lao PDR

Sayasane

Somprach

Ketchatturat

2021

IER

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This study was intended to search the vital factors and indicators of personal knowledge management and the effectiveness of teacher learning management for primary school teachers in Lao PDR. A survey research design was employed to 600 teachers with the purpose of testing the goodness-of-fit of the identified vital factors and indicators with the empirical data. The results revealed that an entire of 30 indicators were recognized from 10 vital factors. The structural relationship model of personal knowledge management to enhance the effectiveness of teacher learning management indicators was found to be in parallel to the empirical data, with χ2 =382.319, df=342, χ 2/df=1.117, CFI=0.997, TLI=0.996, RMSEA=0.030, and SRMR=0.030. The results contribute significantly to knowledge with orientation to recommending a measurement model which can be referred by primary school teachers in Lao PDR in particular on how to utilize personal knowledge management skills to enhance their learning management capabilities.

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“…The first one is assessing responsibility in educational institutions that can be auditable and the second one is assessing the relative effectiveness of teachers. Some models consider only students' existing knowledge or take other variables such as sex, religion, and economic status into consideration [4], [5], [6], [7]. The TIMSS 2015 assessment results reported Singapore achieved the highest mean score in mathematics (621 points), followed by South Korea (the average score of 606) while Thailand had the average score of 431 which was listed in a low-level group [8].…”

Section: Introductionmentioning

confidence: 99%

An Analysis Educational Guidelines of Mathematics Education Provision for Primary School from High Score Countries on Timss 2015

Sirikit¹,

Mahalawalert²,

Angganapattarakajorn³

2020

ujer

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The objectives of this research were 1) to study effects of student characteristic variables and educational institution characteristic variables on the quality assessment of mathematics study management at primary school of countries achieving high test scores, i.e. Singapore, South Korea, and the Hong Kong Special Administrative Region and 2) to compare similarities and differences of student characteristic variables and educational institution characteristic variables on the quality assessment of mathematics study management in Singapore, South Korea, and the Hong Kong Special Administrative Region. The data used in this research are secondary data from the 2015 Trends in International Mathematics and Science Study (TIMSS). The data were collected from 4,669 students across 100 schools in the Republic of Korea, 6,517 students across 100 schools in Singapore and 3,600 students across 100 schools in Hong Kong. The three steps taken for data analysis are as follows -1) To analyze descriptive statistics 2) To estimate the ability of students from the assessment of their mathematics proficiency using IRTPRO program; 3) To analyze variables affecting student and school with Hierarchical Linear Modeling (HLM) and two levels of analysis. The findings from the study revealed that 1. The proportion of all variances explained for variables or coefficient of prediction (R 2 ) indicated Singapore's coefficient of prediction at a student level was 0.2750 (27.50%) and at a school level was 0.7250 (72.50%).Republic of Korea's coefficient of prediction at a student level was 0.2183 (21.83%) and at an school level was 0.6288 (62.88%), the Hong Kong Special Administrative Region's coefficient of prediction at a student level was 0.1477 (14.77%) and at a school level was 0.4482 (44.82%). 2. Multi-level analysis of student-level variables found that 7 variables affecting the quality of mathematics study management. Namely, 3 countries had 2 variables, 2 countries had 4 variables, and 1 country had 1 variable. As for multi-level analysis of educational-level variables, it was found that 5 variables affecting the quality of mathematics study management. Namely, 2 countries had 1 variable and 1 country had 4 variables.

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A Quality Assessment of Science Instructional Management in Basic Education Schools: An Application of a Value–added Model and Differential Item Functioning

Cited by 3 publications

References 0 publications

Developing Factors and Indicators of Growth Mindset for School Administrators in Thailand

Developing Factors and Indicators of Growth Mindset for School Administrators in Thailand

Personal Knowledge Management to Enhance the Effectiveness of Teacher Learning Management in Lao PDR

An Analysis Educational Guidelines of Mathematics Education Provision for Primary School from High Score Countries on Timss 2015

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