Inequality in the shadow? Cross-national comparisons of the effects of additional instruction on math and science performance based on PISA 2018 data Background Many educational systems worldwide are experiencing a growing demand for shadow education, which often takes the form of outside-school educational activities such as private tutoring dedicated to improving student achievement (Entrich, 2021; Stevenson & Baker, 1992). Ample evidence from individual social contexts suggests that shadow education is more accessible to families with high-socioeconomic status (SES) compared to low-SES families (Atalmis et al., 2016; Liu & Bray, 2017; Smyth, 2009; Zhang, 2020). As a result, there are growing concerns that shadow education may reproduce educational inequalities (Bray, 2009; Lynch & Moran, 2006; Zhang & Bray, 2020). However, studies using data from multiple countries have yielded mixed results regarding the association between student SES and access to shadow education as well as the association between private tutoring and student achievement (Entrich, 2021; Jansen et al., 2021; Song et al., 2021; Wiseman, 2021). Therefore, more research is needed to explore the role of outside-school learning activities in the SES achievement gaps. Research Question: To contribute to the discussion on the role of shadow education in the SES achievement gaps, this study asks two questions--(1) To what extent is students' SES associated with their use of different types of additional instruction remedial, enrichment, and instruction on study skills? (2) What are the effects of different types of additional instruction remedial, enrichment, and instruction on study skills on student math and science achievement? Setting: The study uses data from six countries that participated in PISA 2018, i.e., Thailand, Kazakhstan, Greece, Korea, Hong Kong, and Ireland. These six countries were purposively selected because they have been intensively studied in the shadow education literature and they exhibit disparities in terms of geographic distribution and GDP per capita. Figure 1 shows the math and science performance as well as GDP per capita of the six countries in relation to the OECD average. Participants: Participants are 15-year-old students from educational institutions in Thailand, Kazakhstan, Greece, Korea, Hong Kong, and Ireland in PISA 2018 (N=52,807). Table 1 summarizes the number of students and students' math and science performance in each country. Intervention PISA 2018 asks whether students participate in additional instruction in different school subjects. This study looks at additional instruction in the math and science subjects. Specifically, five types of additional instruction are of interest in this study: (1) remedial instruction on math, (2) enrichment instruction on math, (3) remedial instruction on science, (3) enrichment instruction on science, and (5) additional instruction on study skills. Research Design PISA uses a two-stage sampling process: first sampling the schools and then sampling students within the participating schools. Therefore, sampling weights are associated with each student because students and schools in each country may not have the same chance of being selected. This sampling approach may increase the standard errors of population estimates. This study therefore uses a Balanced Repeated Replication (BRR) procedure to account for the cluster structure of the data and generate unbiased standard errors. Data Collection and Analysis: The study uses data from the PISA 2018 performance tests in the mathematics and science domains. The tests include an item bank and each student is only presented with a fraction of those items. To account for the variability in scores due to the different sets of items available to each student, 10 plausible values were computed for each student as estimates for their performance in each domain. PISA 2018 also collects questionnaire data from students and their schools, which provides contextual information such as SES indicators at the student and school levels. Multiple regression analyses were performed for each country to examine the relationship between additional instruction and student performance in math and science. Outcome variables are student math and science performance. The independent variables are the five different types of additional instruction listed in the Intervention section. Covariates include student gender, student learning time in math/science classes, family socio-economic status, home educational resources, percentage of fully certified teachers at school, and student-teacher ratio. Results: Table 2 presents the correlations between different types of additional instruction and student- and school-level SES indicators. Participation in different types of additional instruction was differently associated with SES indicators. In general, SES indicators are positively associated with additional instruction, especially enrichment instruction, lending support to previous findings that high-SES families tend to access more additional educational resources than low-SES families. Tables 3 and 4 present the results of the multiple regression analyses for each country. Different types of additional instruction have different effects on student math and science achievement. Remedial instruction and instruction on study skills are negatively associated with both math and science performance. Enrichment instruction is positively associated with student performance in some countries (Thailand, Greece, Korea) but not the others (Kazakhstan, Hong Kong, and Ireland). Significant results were mainly found in student-level SES indicators, while school-level SES indicators yielded few significant results. Conclusions: Despite the small number of countries included in the study, the study contributes to the growing body of cross-national comparisons on the relationship between shadow education and the SES achievement gaps. The findings of this study provide more nuance on how different types of additional instruction can be differently associated with student achievement. This demonstrates the need for further work to differentiate various types of shadow education to better understand how shadow education might reproduce or close the SES achievement gaps. Moreover, the cross-national variation in the effects of additional instruction on student achievement highlights the need to account for characteristics of different educational contexts when interpreting the role of shadow education in educational inequality.