Introduction:

This research study was jointly funded by ACER and the Australian Government's Department of Foreign Affairs and Trade (DFAT) through the Global Education Monitoring (GEM) Centre.

The Southeast Asia Primary Learning Metrics (SEA-PLM) is a regional large-scale assessment that provides comparable data for Grade 5 students in 6 low- and middle-income countries in Southeast Asia – Cambodia, Lao PDR, Malaysia, Myanmar, the Philippines, and Viet Nam. The analyses presented here focus on socio-cultural factors found to be related to reading literacy of students (Zhang et al., 2023; Syamsuri & Bancong, 2022; Wang & Liu, 2021; Brandisauskiene et al., 2021; Alampay & Garcia, 2019; Cheung et al., 2017).

The analyses were carried out using data from the 6 countries participating in SEA-PLM 2019. Results of the analyses, which used the Partial Least Square Structural Equation Modelling approach, show the interconnections between the factors affecting reading literacy of Grade 5 students in the participating countries.

The interactive graph:

The interactive data visualisation below presents the effect of these socio-cultural factors on students’ reading literacy, holding the influence of family socio-economic status constant.

For each socio-cultural factor, the graph illustrates how a factor, for example, parental attitudes towards learning and homework, contributes to explaining the differences in students’ reading literacy. All effects shown in this graph are significant. Hovering over a factor highlights its significant effects on other factors with effect sizes displayed alongside it (in the country view). A legend for interpreting effect sizes is provided next to the illustration.

Broadly, this study is underpinned by the Education Prosperity Framework (Willms, 2018), which was developed with a focus on low- and middle-income countries. The factors included in the analyses are mapped to the relevant concepts of this framework. The legend indicates how the factors match the concepts in the framework.

Country:

Explanation of the graphical illustration:

Hovering over each factor shows the count (total number) of countries where the relationships are significant. As 6 countries participated in SEA-PLM, the maximum count can be 6, if an effect is significant in all countries.

The drop-down menu can be used to view the structural path model for a selected participating country, as opposed to the summary model which displays the inter-relationships between the factors for all 6 countries.

The total count of direct effects of the factors on students’ reading literacy is also shown in Table 1. In addition, Table 1 shows the size and directions of these direct effects for each country.

More information on each of the contributing factors can be found by clicking on each of the factors in the figure.

Discussion of key findings

Table 1 shows the size and directions of connections of the socio-cultural factors with reading literacy – that is the direct effects of the factors on reading literacy – for each country.

Key findings from the analyses suggest that family’s socio-economic status, and parental attitudes towards homework have a positive direct effect on reading literacy in all 6 countries.

Among the other key influences, the impact of preschool attendance on reading literacy has also been significant in 5 of the 6 countries. A positive value means that previously enrolling at a preschool and spending time during the early years on literacy related activities, such as reading, is related to higher performance in reading literacy.

Outside school activities at home have a weak positive (but significant) effect on reading literacy, as does more learning time spent on literacy at school, lower teacher absenteeism and greater student interest in school. Negative (weak) effects on reading literacy across all countries emerge for outside school activities outside the home, grade repetition and gender.

Interestingly, spending time on outside school activities - outside the home has a negative effect on reading literacy, whereas spending more time on outside school activities - at home has a positive effect on reading outcomes. Our analyses show that, when taking students’ gender into account, the effects are detrimental for boys who spent more of their outside school activities outside the home such as working at farms and in labour intensive jobs. On the other hand, for girls who spent their outside school activities at home helping with household chores and looking after younger children, this factor can positively influence their reading literacy scores.

Table 1. Direct effects of factors on reading literacy per country

Factors

Cambodia

Lao PDR

Myanmar

Malaysia

Philippines

Viet Nam

Summary*

Gender

-.10

-.04

NS

-.11

-.07

-.08

5

Family socio-economic status

.31

.32

.31

.19

.39

.33

6

Literacy resources at home

NS

.09

NS

.16

NS

.12

3

Parental attitudes towards homework

.10

.11

.14

.06

.22

.14

6

Preschool attendance

.05

.04

NS

.08

.08

.06

5

Outside school activities - at home

.05

.12

.10

.08

.04

-.04

6

Outside school activities - outside the home

-.19

-.16

-.12

-.24

-.17

-.14

6

Grade repetition

-.15

-.07

-.19

NS

-.10

-.13

5

Literacy time at school

.09

.06

.04

NS

.05

.03

5

Teacher absenteeism

.15

.10

.11

NS

.09

NS

4

Student interest in school

.16

.08

.22

.11

.22

NS

5

  • Table 1 notes:
  • * = Count of the significant effects;
  • Effect Size:
    • Strong negative: -1.0 to -0.75
    • Moderate negative: -0.75 to -0.25
    • Weak negative: -0.25 to 0
    • Weak positive: 0 to 0.25
    • Moderate positive: 0.25 to 0.75
    • Strong positive: 0.75 to 1
  • NS = not significant at 0.05 level;
  • The negative values for ‘Gender’ indicate girls are doing better in reading than the boys;
  • Results in bold highlight the key findings.
Country structural models:

Hovering over any of the factors in the graph shows the effect size of that factor on reading literacy and on the other factors. The sign of the relationship shows if it is influencing those factors positively (+) or negatively (-), except in the case of gender, where girls are indicated by a ‘0’ and hence negative values mean that girls perform better than boys.

The other key information displayed for the factors is the explained variance of the model or R² values. These suggest the strength of the relationship, for example, R² values of 0.25, 0.50 and 0.75 represent weak, moderate, and strong explanatory power of a model. Where R² values are not provided, the path is not significant. Overall, the country models explain between a quarter and more than half of the variance in students’ reading literacy in the participating countries.

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Additional information:

SEA-PLM website: https://www.seaplm.org/