SES-Achievement Gaps in East Asia: Evidence from PISA 2003–2018

Lam, Si Man; Zhou, Yisu

doi:10.1007/s40299-021-00620-7

Cited by 10 publications

(5 citation statements)

References 33 publications

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“…Family factors that relate to students' mathematics achievement include factors related to the family's socioeconomic background, which relates to parents' education and occupation, as well as the educational resources available in the home (Lam and Zhou 2021;Lombardi and Dearing 2021;Marks and Pokropek 2019). The types of parental support for the students' learning are also important predictors of students' achievement (Bernardo et al 2015;Soenens et al 2007); parental support also relates to the quality of parent-child relationship (Christenson and Havsy 2004), parental involvement in their children's learning in mathematics (Hyde et al 2006;Jay et al 2018) and expectations of their children's achievement (West et al 1998).…”

Section: Predictors Of Mathematics Learning and Achievementmentioning

confidence: 99%

Contrasting Profiles of Low-Performing Mathematics Students in Public and Private Schools in the Philippines: Insights from Machine Learning

et al. 2022

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Filipino students performed poorly in the 2018 Programme for International Student Assessment (PISA) mathematics assessment, with more than 50% obtaining scores below the lowest proficiency level. Students from public schools also performed worse compared to their private school counterparts. We used machine learning approaches, specifically binary classification methods, to model the variables that best identified the poor performing students (below Level 1) vs. better performing students (Levels 1 to 6) using the PISA data from a nationally representative sample of 15-year-old Filipino students. We analyzed data from students in private and public schools separately. Several binary classification methods were applied, and the best classification model for both private and public school groups was the Random Forest classifier. The ten variables with the highest impact on the model were identified for the private and public school groups. Five variables were similarly important in the private and public school models. However, there were other distinct variables that relate to students’ motivations, family and school experiences that were important in identifying the poor performing students in each school type. The results are discussed in relation to the social and social cognitive experiences of students that relate to socioeconomic contexts that differ between public and private schools.

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Section: Predictors Of Mathematics Learning and Achievementmentioning

confidence: 99%

Contrasting Profiles of Low-Performing Mathematics Students in Public and Private Schools in the Philippines: Insights from Machine Learning

et al. 2022

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“…Previous studies have shown that students’ families have an important influence on their growth [ 6 , 7 , 8 ] and that students from underprivileged family backgrounds tend to achieve poorer development than those from more advantaged family backgrounds [ 9 , 10 , 11 ]. Educational equity is a part of social equity, and educational equity in the modern sense should represent the separation of students’ achievements and their socio-economic background [ 12 , 13 ]. In China, the government attempts to ensure educational equity by providing students from underprivileged socio-economic backgrounds with more resources through reasonable allocation, thus counteracting the disadvantages brought by socio-economic factors for these students [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

How School Climate Affects the Development of the Social and Emotional Skills of Underprivileged-Background Students—An Empirical Study Based on the SSES2019 Data

Wang

Xiao

et al. 2022

Children

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Background: Promoting the development of the social and emotional skills of underprivileged-background students is an integral part of educational and social equity. To date, there has been a lack of relevant research in this field. Aims: This study investigated the impacts of cooperative school climate and competitive school climate on the development of the social and emotional skills of underprivileged-background students. Sample: This study used the data of Chinese underprivileged-background students (N = 1739) from the Study on Social and Emotional Skills conducted by the Organisation for Economic Cooperation and Development (OECD-SSES2019). Methods: This study selected the ordinary least squares (OLS) analysis method and the quantile regression (QR) analysis method. Results: The ordinary least squares (OLS) analysis results showed that cooperative school climates promoted the development of various dimensions of the social and emotional skills of underprivileged-background students, while competitive school climates had significant negative impacts on the collaboration and emotional regulation of underprivileged-background students and had no significant impact on the other three major domains, namely engagement with others, open-mindedness, and task performance. A quantile regression analysis further explored the heterogeneity in the impacts of cooperative school climate and competitive school climate on the development of the social and emotional skills of underprivileged-background students through quantile regression and found that the impacts of a competitive school climate on underprivileged-background students with different levels of social and emotional skills were homogeneous, while the impacts of a competitive school climate on underprivileged-background students with different levels of social and emotional skills were heterogeneous. Conclusions: These findings provide a greater insight into the roles of school cooperative climate and school competitive climate in the development process of the social and emotional skills of underprivileged-background students.

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“…In a comparative study of trends in socioeconomic achievement gaps, the authors (Lam & Zhou, 2021) investigated the strength of gaps and their development in seven East Asia systems using PISA data from 2003 to 2018. The authors compared the magnitude of gaps between highand low-, high-and medium-, and medium-and low-SES students in reading, math, and science, indicated by 90/10, 90/50 and 50/10 gaps, respectively.…”

Section: Weak Link Between Family Background and Academic Performancementioning

confidence: 99%

“…Further, Lam & Zhou (2021) looked at the performance at the lower tails of socioeconomic distribution and found that students from Macao scored higher than their peers with equivalent backgrounds elsewhere. The edge was most visible at the lowest tiers.…”

Section: Weak Link Between Family Background and Academic Performancementioning

confidence: 99%

Prioritizing Education: The Macao Experience Since the Millennium

Zhou¹,

Lam²

2022

International Handbook on Education Development in Asia-Pacific

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Macao is globally recognized as a high-performing system according to the latest releases of PISA results. Such recognition comprises two aspects: 1) average performance of all Macao fifteen-year-olds was among the highest in the world; and 2) there is a considerably weak link between socioeconomic status and learning outcomes in Macao compared with other participating economies. This chapter examines the systemic effort behind these phenomena. A brief history characterizes the special administrative region in two periods. Before 1999, the Macao system had long been criticized for its uncoordinated structure originating from the laissez faire regime under the historical Portuguese colonial bureaucracy. After 1999 and to this date, Macao went through a gradual transition from a loosely coupled system to a re-coupling one. The government's effort is most evident in elaborating an extant legal framework to regulate schools and teachers. Riding a booming economy, the government consistently prioritized educational development. Its expanding and targeted fiscal policy allowed Macao schools to reduce class sizes while maintaining an engaging variety of extra-curricular activities. Due to the absence of a central, standardized examination, the government also made use of international large-scale assessments to monitor school performances. The authors argue that both highand low-performing students benefited from these policies. The authors close the chapter by discussing the challenges ahead.

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SES-Achievement Gaps in East Asia: Evidence from PISA 2003–2018

Cited by 10 publications

References 33 publications

Contrasting Profiles of Low-Performing Mathematics Students in Public and Private Schools in the Philippines: Insights from Machine Learning

Contrasting Profiles of Low-Performing Mathematics Students in Public and Private Schools in the Philippines: Insights from Machine Learning

How School Climate Affects the Development of the Social and Emotional Skills of Underprivileged-Background Students—An Empirical Study Based on the SSES2019 Data

Prioritizing Education: The Macao Experience Since the Millennium

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