Universal Journal of Educational Research Vol. 8(12A), pp. 7227 - 7232
DOI: 10.13189/ujer.2020.082504
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An Analysis Educational Guidelines of Mathematics Education Provision for Primary School from High Score Countries on Timss 2015


Ruangdech Sirikit 1,*, Panwasn Mahalawalert 1, Vetcharit Angganapattarakajorn 2
1 Educational and Psychological Test Bureau, Srinakharinwirot University, Bangkok, Thailand
2 Faculty of Education, Burapha University, Thailand

ABSTRACT

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 (R2) 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 a 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.

KEYWORDS
Mathematics, TIMSS 2015

Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Ruangdech Sirikit , Panwasn Mahalawalert , Vetcharit Angganapattarakajorn , "An Analysis Educational Guidelines of Mathematics Education Provision for Primary School from High Score Countries on Timss 2015," Universal Journal of Educational Research, Vol. 8, No. 12A, pp. 7227 - 7232, 2020. DOI: 10.13189/ujer.2020.082504.

(b). APA Format:
Ruangdech Sirikit , Panwasn Mahalawalert , Vetcharit Angganapattarakajorn (2020). An Analysis Educational Guidelines of Mathematics Education Provision for Primary School from High Score Countries on Timss 2015. Universal Journal of Educational Research, 8(12A), 7227 - 7232. DOI: 10.13189/ujer.2020.082504.