Peer Reviewed Articles on How Do Students Do on Standardtized Tests With Low Reading Scores

• Journal List
• Front end Sociol
• v.5; 2020
• PMC8022478

Front end Sociol. 2020; 5: 544628.

Standardized Testing, Use of Cess Data, and Low Reading Performance of Immigrant and Non-immigrant Students in OECD Countries

Janna Teltemann

¹Section of Social Sciences, University of Hildesheim, Hildesheim, Germany

Reinhard Schunck

^twoSchoolhouse of Man and Social Sciences, University of Wuppertal, Wuppertal, Germany

Received 2020 Mar 21; Accustomed 2020 Oct 23.

Abstract

This paper investigates the effects of standardized testing and publication of achievement information on low reading performance for immigrant and non-immigrant students in 30 OECD countries. The newspaper aims to exam hypotheses derived from a principal-agent framework. Co-ordinate to this theoretical perspective, standardized assessments alone should not be associated with reading performance. Instead, the model proposes that the provision of the results to the principle (parents and education authorities) is associated with college educatee operation, equally this reduces the information asymmetry betwixt principal (parents and educational authorities) and agent (teachers and schools). The results of our analyses of PISA 2009 and 2015 reading information from 422.172 students show that first, the use of standardized achievement tests alone was not associated with the risk of low performance. 2d, making the results of standardized tests available to the public was associated with a decreased risk of depression reading operation amidst all students, and, 3rd, particularly amid first generation immigrant students. These results were robust across various modeling approaches. In accordance with the predictions from the principal-amanuensis framework, our findings advise that the mere implementation of standardized assessments has no effects on low functioning. Testing forth with the public provision of the testing results, which decreases the information asymmetry between schools and teachers on the one hand and parents and teaching government on the other, was associated with a decreased risk of depression operation, with the event being stronger for immigrant students.

Keywords: immigration, instruction, standardization, PISA, educational inequality, principal-amanuensis model, fixed effects, longitudinal analyses

Introduction

Integrating growing immigrant populations is a challenge for receiving countries. Since instruction is a key resource in contemporary societies information technology is also a central to societal integration of immigrants and, in item, their descendants. International large scale assessments such equally the OECD PISA written report have drawn attention to countries' didactics systems and how they may contribute to educational inequalities and differences in integration processes. Every bit pressure level for quality and equity in teaching increased, policy making in education has been under shut monitoring during the last years. A major focus of educational reform in many countries has been the implementation of educational standards and, in particular, their regular assessment through nationwide standardized testing (Scheerens, 2007; Meyer and Benavot, 2013). Standardized testing is supposed to aid the definition of clear educational goals and serves as a measure of accountability (i.e., the enforcement of responsibilities to attain these goals), which, in plow, are believed to touch on incentives, restrictions, and opportunities of the actors involved in "producing" education. This rationale is drawn, in part, from principal-agent-models which are based in rational pick theories of private action (Wößmann, 2005; Levačić, 2009). While principal-agent-models are often referred to in empirical research using large calibration assessment data like PISA, their mechanisms are rarely put to a direct test. More often, these models are mentioned in society to explain a possible empirical clan between standardized testing and educational outcomes.

In this newspaper, we add together to the literature by, kickoff, testing mechanisms drawn from a principal-amanuensis model of pedagogy more straight. To do so, we investigate if the apply of nationwide standardized testing affects student performance, and, more importantly, if reporting the results of such assessments to the public or educational authorities does. From the perspective of primary-amanuensis models, we would expect that reporting of the results is particular important, since it reduces the data asymmetry between the agent (schools and teachers) and the master (parents and educational authorities). Second, we take a closer look at immigrant students. The number of immigrants has increased substantially in nearly Western receiving countries during the last years. Third, considering we focus on immigrant student, we exercise not examine average achievement as an result merely the risk of depression reading performance. This is defined as performance below the second proficiency level in reading in PISA. Reaching this level of reading proficiency is necessary to participate effectively in guild and tin can thus exist seen as a prerequisite for immigrant integration. Not reaching this level of proficiency is related to lower life chances: Follow-upwardly studies based on PISA have shown that operation below this level is related to a lower take a chance of transition to post-secondary instruction and a college risk of unemployment and income poverty (OECD, 2010; Shipley and Gluzynski, 2011). Fourth, we employ a longitudinal design at the land level by using data from the OECD Programme for International Student Assessment (PISA) 2009 and 2015 from 30 OECD countries. The longitudinal pattern allows usa to control for (time constant) unobserved country characteristics, making the estimates less decumbent to bias.

The residue of this paper is structured as follows: in the next department, nosotros elaborate our theoretical arguments on the effects of standardized testing based on the main-amanuensis model. Thereafter, we summarize findings from previous studies on the impact of testing practices on educational outcomes. In section "Data and Methods" we draw our database and methods. After presenting the results in section "Results", we discuss implications and limitations of our study in the final section.

How Standardized Testing Can Affect Functioning—Theory and Hypotheses

From a rational choice perspective, institutions of the teaching arrangement bear upon incentives, restrictions, and opportunities of the actors involved (i.east., students, parents, teachers, principals). Following this rationale, education policies aiming for quality education should be about constructive if they accept implemented institutional regulations which incentivize high effort of the actors involved (eastward.g., teachers). Rational pick models of pedagogy further presume that actors, in our case teachers, may non necessarily exist interested in loftier performance and may aim to avert all-encompassing effort. Parents and the country, yet, expect schools and teachers to invest endeavor in teaching in guild to realize quality education. This is a classic main-agent constellation (Laffont and Martimort, 2002): A primary, the parents and/or the administrative authorities, commissions an agent, the school, to do something on their behalf, i.e., to provide education to the students (Ferris, 1992; Wößmann, 2005; Levačić, 2009).

The principal-amanuensis framework draws attention to three possible problems (Jensen and Meckling, 1976): First, the agents' and principals' preferences may not align. Second, there is an disproportion in information—oftentimes the principal cannot observe the amanuensis's behavior directly. Third, the principal has to be able to evaluate the agent's behavior, i.e., he needs to assess how much effort the amanuensis puts into realizing the chief's goals. Therefore, for principal-agent constellations to piece of work in the principal's involvement, at least two conditions have to be met. First, the principal's goals take to exist conspicuously defined in order to be realized. This is one of the justifications for the specification of national standards in education. They are supposed to clarify the goals of education and function as a frame of reference and orientation for the actors involved (Klieme et al., 2003). Second, information technology is not sufficient to simply spell out the educational standards, they besides need regular assessment. Hence, a frequently used indicator of the standardization of an educational activity organization is the employ of regular (nation-wide) standardized tests.

A chief argument in the literature is that standardized tests meliorate overall performance (Wößmann et al., 2009; Bol et al., 2014). The theoretical mechanisms governing this outcome are withal often rather implicit; mostly, it is assumed that the mere being of such tests can either cause a class of "gentle force per unit area" on schools and teachers and their fashion of teaching or increase the signaling value of educational credentials (for a notable exception and an explicit theoretical model, see Bishop, 1995)^ane. Information technology is argued, for example, that if teachers do non know which tasks are assessed in tests—because the tests are conceptualized by a central say-so—they will be less probable to skip parts of the curriculum and the content taught volition be more comprehensive (Wößmann et al., 2007, p. 25f.).

Even so, from a theoretical point of view, this mechanism appears incomplete. The implementation of standardized testing itself is non sufficient to resolve the principal-amanuensis problem, every bit information technology does not bear upon the data disproportion between both parties. The principal needs to have information on the results of the standardized tests. The more than data the principal has, e.thousand., achievement data of other schools or national averages, the better volition the principal exist able to evaluate the amanuensis's behavior and sanction information technology, positively or negatively. Thus, only if the results of the standardized tests are bachelor to the primary, will there be a relevant subtract in the disproportionate relation. From the logic of the principal-agent model, this form of accountability increases the agents' incentives to deed according to the principals' preferences. Consequently, schools and teachers as agents are confronted with a higher pressure to improve their students' achievement. Nosotros therefore expect lower rates of low performing students in countries where assessment results are communicated to the public or administrative government (Hypothesis 1).

Furthermore, when it comes to the risk of depression performance, unlike students have unlike risks. Immigrant students, for example, are oftentimes in need of special individual (language) support. As their parents have less noesis nearly the rules of the education organisation, teachers, and schools have to invest more than time for consultation. The specific situation of immigrant students creates a college demand for teachers and, from the perspective of the principal-agent model, a higher run a risk for opportunistic behavior (east.g., negligence of the specific needs of immigrant students). If, however, achievement data is bachelor to the principals, this creates stronger incentives for schools to accept care of every student, regardless of their background. The beingness and publication of the results of standardized tests therefore should exist advantageous for immigrants.

Further, we contend that it is rational for schools to concentrate efforts on those student groups who are in particular demand for aid (such as immigrant students) (Motiejunaite et al., 2014), equally their functioning may have a strong impact on a school'due south mean functioning level. Findings from research on the effects of standardized assessments in the USA showed that for some tests and tasks, adaption of pedagogy strategies was more than prevalent in schools with larger shares of indigenous minorities and depression performing students (Mittleman and Jennings, 2018). Further, in some countries, standardized assessments are targeted toward minimum levels of education. Every bit a event, teachers may peculiarly focus on students who are at risk of not reaching this level (Booher-Jennings, 2005), which oft are immigrant or ethnic minority students. In the context of low educational operation, we thus await immigrant students to turn a profit more than from standardized testing and a publication of cess results than non-immigrant students (Hypothesis 2).

Furnishings of Standardized Testing on Achievement—Previous Results

Since the publication of the first PISA circular in 2000, a number of studies investigated how aspects of educational standardization are related to student achievement and inequality in student accomplishment (Schütz et al., 2007; Horn, 2009; Chmielewski and Reardon, 2016; Bodovski et al., 2017). These studies often focused on standardized testing, which is seen every bit 1 aspect of an education organization's degree of standardization (Bol and van de Werfhorst, 2013). Information technology has to be noted, withal, that standardized testing should not be used alone to evaluate the caste of standardization of a land'due south instruction arrangement. To appraise if an education system can be described as standardized, other dimensions of (de)standardization, such as curriculum standardization, school autonomy (in selecting teachers, allocating resources, etc.), and the modes of teacher education, have to be considered every bit well. Since our focus lies on standardized testing—and not standardization in full general—we concentrate the literature review on studies that either focus on this dimension or on immigrant students.

Several previous studies looked at the upshot of central schoolhouse exit exams, which are a special blazon of a standardized assessment, and mostly constitute that they are associated with higher average test scores (Bishop, 1997; Carnoy and Loeb, 2002; Wößmann, 2003; Fuchs and Wößmann, 2007). Bergbauer et al. (2018) compared the effects of standardized external comparisons and standardized monitoring to furnishings of more than internal adult testing procedures, using data from six unlike PISA studies (2000–2015). Their results testify that standardized external comparisons also as standardized monitoring are associated with higher levels of competence among students. Drawing on data from TIMSS 1995, Jürges et al. (2005) analyzed the result of central go out exams on accomplishment scores in lower secondary education in Federal republic of germany. They found that students in federal states with central exit examinations outperform students in states without cardinal school leaving assessments.

A small number of studies addresses the furnishings of testing on immigrant achievement and, to the all-time of our noesis, there are no existing studies that focus on assessments and on the educational inclusion of immigrant students in terms of performance below a certain threshold. Schneeweis (2011) establish pregnant (positive) effects of external student assessments on immigrants educational accomplishment simply for OECD countries. Cobb-Clark et al. (2012) found insignificant effects of external examinations on test score gaps between immigrants and natives, merely for one of 8 assessed groups they estimated a significant negative effect. Teltemann (2015) plant smaller achievement gaps in countries where accountability measures were implemented. Wößmann (2005) reported positive effects of central exams for low achieving students, suggesting that primal exams bring an advantage for immigrant student and students from less-educated backgrounds.

Data and Methods

We depict on information from the 2009 and 2015 OECD Plan for International Student Cess (PISA, OECD, 2016). Both PISA rounds contain information on testing procedures and the publication of the testing results. Since its beginning survey in 2000, PISA is the most regular and broad-ranging competence assessment of secondary schoolhouse students. In 2015, more than than 540,000 students in 72 countries have been tested. PISA assesses curriculum-independent competences in reading, mathematics and science. In addition, PISA collects a broad range of background data by administering context questionnaires to students, parents, and principals. The sampling design is targeted at a representative sample of the 15-years former school population in a country, independent of the respective grade they are attending. PISA is conducted every 3 years and the PISA datasets are publicly available via download from the OECD'southward websiteⁱⁱ. Since we pooled the data from 2009 and 2015, nosotros created a data structure with four levels: students, schools, state-years, and countries (see the department on Modeling beneath). All analyses were carried out using Stata 16.1. Lawmaking for reproducing the assay have been archived on the Open Scientific discipline Framework (https://osf.io/3ezxs/).

Dependent Variable

With regard to immigrant integration, the definition of competences in PISA, which does not target national curricula but seeks to mensurate "viability" in globalized economies, proves useful. The PISA competence scores "mensurate how far students budgeted the cease of compulsory education have acquired some of the knowledge and skills essential for full participation in the cognition society" (OECD, 2009b, p. 12). Thus, assessing differences between immigrant and non-immigrant students with PISA data can give insight not but into educational integration simply besides into hereafter societal integration. Competences in PISA are measured on a continuous scale which is standardized to an OECD hateful of 500 points. In addition, PISA distinguishes so-chosen proficiency levels, which stand for to actual abilities. For reading, proficiency level 2 is defined as a baseline level of competences, "at which students begin to demonstrate the reading skills that will enable them to participate effectively and productively in life" (OECD, 2016, p. 164). Performance below this baseline level thus indicates the adventure of failed societal integration for immigrant students, as has been shown by PISA follow-up studies (OECD, 2010; Shipley and Gluzynski, 2011). PISA provides several (v upwardly to 2012 and 10 since 2015) plausible competence scores per student (see OECD, 2009a for details). Nosotros used the (offset) five plausible values and created dummy variables that indicate performance below proficiency level 2 (a score below 408 points, run into OECD, 2009a, p. 117ff.). Consequently, the final coefficients correspond the average over five models (Macdonald, 2019).

Principal Independent Variable and Controls at the Student Level

In PISA, immigrant status is assigned according to the state of birth of a student and its parents. Students who indicated that they and their parents were born abroad are categorized as outset generation students. Second-generation students were born in the state of test with both parents built-in abroad. Since PISA does non collect comparable or complete information on students' or parents' countries of origin—the style this is inquired differs between the participating countries—nosotros cannot distinguish different immigrant groups. This is a major drawback, since the composition of immigrant groups may covary with the receiving countries' contextual conditions, including their educational institutions. To alleviate this problem partially, we command for language use at domicile with a dummy variable indicating whether students reported to mainly speak a foreign language and not the examination language at home. Furthermore, because migration into OECD countries may exist selective on socioeconomic status, we also control for several measures of parental socioeconomic groundwork. This includes parental education (measured through the ISCED scale), family wealth possessions (measured through the "wealth" index in PISA), cultural possessions (measured through the "cultposs" index in PISA), and home educational resources (measured through the "hedres" index in PISA) (see OECD, 2017, p. 339 for details). Lastly, we command for student gender (i = female).

Chief Contained Variables and Controls at the State-Yr Level

Following the arroyo described by the OECD (OECD, 2013, p. 28, 66, 166), we have aggregated school data within countries for 2009 and 2015 to draw the organisation level. This is possible since PISA draws a representative sample of schools and the schools' principals have been interviewed well-nigh organizational aspects of their schoolhouse. For each year we constructed three variables according to this procedure: first, the proportion of students in a country attending schools that regularly administer mandatory standardized tests. Second, the proportion of students attention schools that post aggregated achievement data publicly and, third, provide aggregated accomplishment data to educational authorities³.

A country's institutional arrangements are non independent of other country characteristics that might besides affect student achievement. Since we are employing a longitudinal approach at the country level and include state fixed furnishings (run across Modeling below), all time-constant country differences are accounted for. However, outcome estimates may still be biased past fourth dimension-varying differences between countries that covary with standardized testing and pupil performance. We therefore command country characteristics that may simultaneously bear on (immigrant) student performance and are related to the country's institutional arrangements. In social club to control for a full general effect of resource devoted to the educational system, we include annual educational expenditure equally a pct of a country'south Gross National Income in our models. Likewise, we control for effects of economic development of a country by including the annual growth of a land's GDP (in percent). The overall number of immigrants in a country may be related to institutions, such as integration policies, which might have an impact on educational performance of immigrants. We therefore control for the international migrant stock as a percentage of the overall population. Additionally, immigrant performance may be impacted past their labor market outlooks. Hence, nosotros control for the annual unemployment rate among foreign born persons in each country. Information for these annual country-yr control variables comes from the Globe Depository financial institution and the OECD (Fontenay, 2018). An overview on the distribution of these characteristics amidst the countries in our sample can be found in the Appendix (Table A1) besides as their pairwise correlations (Table A3).

Analyses Sample

Nosotros restricted our analyses to OECD countries in social club to increase comparability across countries. We excluded countries for which (country-level) information was unavailable and those with <40 immigrant students (either first or second generation) in the sample—this applied to Japan, Korea, Poland, and Turkey. Students were excluded if they had missing values on any variable (listwise deletion). Our final sample consists of 422.172 students in 12.255 schools in 54 state-years in 30 countries. Table 1 gives an overview over unweighted sample statistics.

Table 1

Sample statistics (unweighted).

	Hateful	Sd	Min	Max
Student level variables
Below reading level 2 (pv1)	0.18		0.00	i.00
Beneath reading level 2 (pv2)	0.xix		0.00	1.00
Beneath reading level ii (pv3)	0.18		0.00	one.00
Beneath reading level 2 (pv4)	0.18		0.00	1.00
Below reading level 2 (pv5)	0.18		0.00	1.00
Native	0.89		0.00	1.00
Outset generation	0.05		0.00	1.00
Second generation	0.06		0.00	1.00
Gender [ane = female]	0.51		0.00	one.00
Language of exam spoken at domicile	0.88		0.00	one.00
Parental education
None	0.01		0.00	ane.00
ISCED i	0.03		0.00	i.00
ISCED 2	0.x		0.00	one.00
ISCED 3b,c	0.08		0.00	1.00
ISCED 3a,4	0.24		0.00	1.00
ISCED 5b	0.17		0.00	1.00
ISCED 5a,six	0.37		0.00	ane.00
Alphabetize of family wealth possessions	−0.01	1.05	−7.44	4.44
Index of cultural possessions	−0.02	0.98	−1.92	two.63
Index of home educational resources	−0.05	1.00	−4.45	i.99
Country level variables (source WB)
International migrant stock (% of population)	12.79	8.14	0.82	43.96
Adjusted savings: education expenditure (% of GNI)	v.03	0.93	3.ten	8.34
Gross domestic product growth (annual, %)	−one.23	4.74	−14.43	25.16
Unemployment (%) among strange born	eleven.63	six.18	iv.30	32.00
Proportion of students attending schools that (PISA aggr.)
Regularly apply mandatory stand. tests	0.73	0.21	0.24	1.00
Post achievement data publicly	0.39	0.24	0.02	0.92
Provide adm. authorisation with accomplishment data	0.69	0.22	0.26	0.99
PISA round
PISA 2009	0.58
PISA 2015	0.42
Northward	422,172

Source: PISA 2009, 2015, World Bank.

Modeling

As our dependent variable is binary and our data construction is amassed hierarchically, we estimated iv level linear probability models (LPM). The private students (level 1) are clustered in schools (level ii), which are clustered in land-years (triennial country observations) (level 3), which are again clustered in countries (level iv). The standard approach to this information structure is a four-level random furnishings model

y i j k l = β 0 + β 1 x i j 1000 l + β 2 c thou l + β 3 x i j grand l × c k l + t + w l + v k l + u j k 50 + ε i j grand 50

(1)

where the dependent variable y _ijkl is the probability of an individual student i in school j in country-year chiliad in country l to fall below PISA reading level 2. w _l represents the country-level fault, five _kl the country-yr fault, u _jkl the school, and ε _ijkl the student-level error. 10 _ijkl exemplifies the individual-level variables (i.e., migration background, gender, linguistic communication ability, and parental socio-economic status) and t represents joint period (moving ridge) effects. The effects of involvement are those associated with the country-year–specific variables (β₂) and their interaction with immigration status (β₃).

Although nosotros focus on OECD countries, the country sample is still heterogenous with respect to clearing histories, institutional arrangements, educational policies, and economic conditions, all of which may exist correlated with aspects of the education system and, in particular, testing and accountability. Thus, the problem of unobserved heterogeneity at the state level is pressing and the probability of misspecifying the model is high. The standard strategy to avoid misspecification is to control for the relevant confounders. However, the ability to include relevant confounders is restricted for two reasons. First, with thirty countries (and 54 country-years), the degrees of freedom are limited. Second, many important confounders, eastward.m., which depict a state'due south immigration history, are not readily measured and bachelor. Therefore, we estimated (ane) every bit a first divergence (i.e., fixed furnishings) model (Wooldridge, 2010), including fixed furnishings for countries and years. The advantage of the fixed effects approach is that we exercise not have to brand whatsoever assumptions well-nigh possible confounders at the land level. The model thus produces unbiased estimates even if there are unobserved confounders at the country level—that is, Due east(due west _l |x _ijkl , c _kl ) ≠ 0. Therefore, the furnishings of the country-twelvemonth level variables are estimated solely by relying on within-country (co)variation.

The coefficients in the LPM are estimators of the absolute difference in the probability of depression reading achievement associated with a unit increase in the value of the corresponding predictor variable. We take called a linear probability model over a logistic model for the following reasons. First, the available non-linear iv level models in the statistical program used for the analyses (Stata) practise non accept weights. Weighting the data, still, is necessary in view of the complex and nationally diverging sampling procedures in PISA (OECD, 2009a; Lopez-Agudo et al., 2017). Second, non-linear models are notoriously hard to translate, in particular when dealing with interactions. One needs to gauge boilerplate marginal effects in club to understand the joint event of primary- and interaction effect (Brambor et al., 2006; Berry et al., 2012). While other statistical software packages (e.g., MLwiN) are able to estimate weighted four level logit models, they are unable to provide average marginal effects. Third, an important statement against the LPM is that information technology may provide predicted probabilities >i or <0 (Long, 1997). Notwithstanding, in many situations, the LPM is applicative (Hellevik, 2009) and, as the graphical analogy of the interaction furnishings beneath (Figures 2, iii) show, predictions outside the range of 0 and 1 do not announced to be an issue hither. Fourth, some other argument against the LPM is that heteroscedasticity is most inevitably nowadays. For this reason and to account for the sampling (see below), we estimate robust standard errors. Withal, to scrutinize the robustness of our analyses, we take additionally estimated standard logit models with cluster robust standard errors applying the same weights as for the LPMs (see Table A4 in the Appendix).

Clustering, Standard Errors, and Weighting

PISA usually recommends to employ balanced repeated replications (BRR) to estimate a coefficient'due south variance to have into account its complex sampling (OECD, 2009a; Lopez-Agudo et al., 2017). The detail variant used is known equally Fay's method (Rust and Rao, 1996; Wolter, 2007). BRR breaks up the sample into subsamples ("replicates") and the gauge of interest is commencement estimated for the full sample and so for each of the subsamples (Teltemann and Schunck, 2016). The calculator's variance is and then estimated as the differences betwixt the estimate from the total sample and each of the subsamples. We refrain from using BRR in this paper, because applying BRR may pb to a serious underestimation of the standard errors of state-level variables. Due to the resampling process, there will be no differences betwixt the estimates for a state level variable in the full sample and the subsamples, because all students from one state have the same values for their land level variables.

Since the data is hierarchically structured with three clusters, it is necessary to account for the 3-style clustering to estimate correct standard errors. Thus, we estimate cluster robust standard errors that account for the clustering at the country, the country-year, and the school level (Correia, 2017). Cluster-robust standard errors have shown to provide similar results for the lower level estimates when compared to BRR (Lopez-Agudo et al., 2017). To account for the complex sampling of PISA and the national differences in sampling, all analyses accept been weighted by normalized student weights. In contrast to the final educatee weight, which is recommended for within-country analyses, applying these weights ensures that each country contributes equally to the analysis regardless of its actual size or pupil population.

Results

Figure 1 shows the unadjusted risks for low performance amongst the different groups across the 30 countries in our sample averaged across 2009 and 2015. We run into that first generation immigrants accept a higher risk of performing below the baseline level of reading proficiency than non-immigrant students in most countries of our sample.

Proportion of students below baseline level in reading, PISA, 2009 and 2015.

First generation immigrant students too have a higher take chances of not reaching the baseline reading competence than second-generation immigrants in all countries except three (Chile, Czech Republic, New Zeeland). Second generation students mostly however have higher risks of low performance compared to non-immigrants students with five exceptions (Australia, Canada, State of israel, Republic of hungary, Portugal), in which they show similar or lower risks than their fellow non-immigrant students.

Table 2 gives the results of our multivariate analyses. Model 1 includes simply immigrant status and the state-level controls. Information technology shows that start generation immigrants have a xvi.ane percent points higher probability of performing below the baseline level of proficiency than non-immigrants. 2nd generation immigrants have a 8.5 percentage points higher probability of depression-performance than non-immigrants. After controlling for the individual-level characteristics (Model ii), the relatively higher take chances for immigrants is reduced: Second generation immigrants only have about two percentage points higher run a risk of performing beneath the baseline level than non-immigrants, first generation immigrants notwithstanding take about 9 pct points higher take chances. Model 3 includes the time-varying measure for the proportion of students attending schools that regularly utilize standardized tests. While the estimated association is negative, statistical uncertainty is too high—the effect is not statistically significant. We too practise not find statistically pregnant associations between the use of regular standardized tests and students' migration background (Model four).

Table 2

Iv level linear probability models predicting not reaching reading level ii.

	1	2	3	4	5	6	vii	viii
	b/se	b/se	b/se	b/se	b/se	b/se	b/se	b/se
Student level
Native	ref.	ref.	ref.	ref.	ref.	ref.	ref.	ref.
First generation	0.161***	0.089***	0.089***	0.153***	0.089***	0.154***	0.089***	0.212***
	(0.021)	(0.017)	(0.017)	(0.037)	(0.017)	(0.019)	(0.017)	(0.039)
Second generation	0.085***	0.020	0.020	0.060	0.020	0.071***	0.020	0.107**
	(0.015)	(0.014)	(0.014)	(0.035)	(0.014)	(0.017)	(0.014)	(0.034)
Gender [one = female]		−0.092***	−0.092***	−0.092***	−0.092***	−0.092***	−0.092***	−0.092***
		(0.005)	(0.005)	(0.005)	(0.005)	(0.005)	(0.005)	(0.005)
Linguistic communication of test spoken at habitation		−0.094***	−0.094***	−0.093***	−0.093***	−0.095***	−0.094***	−0.094***
		(0.013)	(0.013)	(0.013)	(0.013)	(0.012)	(0.013)	(0.012)
Parental education
None		0.056**	0.055**	0.055**	0.058**	0.058**	0.055**	0.055**
		(0.021)	(0.021)	(0.021)	(0.022)	(0.022)	(0.021)	(0.021)
ISCED 1		ref.	ref.	ref.	ref.	ref.	ref.	ref.
ISCED two		−0.038	−0.039	−0.040	−0.038	−0.039	−0.040	−0.040
		(0.023)	(0.023)	(0.023)	(0.024)	(0.023)	(0.023)	(0.023)
ISCED 3b,c		−0.111***	−0.112***	−0.113***	−0.110***	−0.111***	−0.113***	−0.112***
		(0.025)	(0.025)	(0.025)	(0.026)	(0.025)	(0.025)	(0.025)
ISCED 3a,iv		−0.152***	−0.153***	−0.154***	−0.151***	−0.152***	−0.153***	−0.153***
		(0.023)	(0.023)	(0.023)	(0.024)	(0.024)	(0.023)	(0.023)
ISCED 5b		−0.161***	−0.162***	−0.163***	−0.159***	−0.160***	−0.162***	−0.161***
		(0.023)	(0.023)	(0.022)	(0.023)	(0.023)	(0.023)	(0.023)
ISCED 5a,6		−0.176***	−0.177***	−0.177***	−0.175***	−0.175***	−0.177***	−0.176***
		(0.023)	(0.023)	(0.023)	(0.024)	(0.024)	(0.023)	(0.023)
Index of family wealth possessions		0.001	0.002	0.002	0.001	0.001	0.002	0.002
		(0.004)	(0.004)	(0.004)	(0.004)	(0.004)	(0.004)	(0.004)
Index of cultural possessions		−0.040***	−0.040***	−0.040***	−0.040***	−0.040***	−0.040***	−0.040***
		(0.004)	(0.004)	(0.004)	(0.004)	(0.004)	(0.004)	(0.004)
Alphabetize of home educational resources		−0.042***	−0.042***	−0.042***	−0.042***	−0.042***	−0.042***	−0.042***
		(0.004)	(0.004)	(0.004)	(0.004)	(0.004)	(0.004)	(0.004)
Country-year level
GDP growth (almanac, %)	−0.000	−0.001	−0.001	−0.001	−0.002	−0.002	−0.001	−0.001
	(0.002)	(0.001)	(0.001)	(0.001)	(0.001)	(0.001)	(0.002)	(0.002)
Education expenditure (% of GNI)	0.016	−0.008	−0.009	−0.009	−0.017	−0.016	−0.005	−0.003
	(0.015)	(0.012)	(0.012)	(0.012)	(0.012)	(0.012)	(0.019)	(0.019)
Migrant stock (% of population)	0.000	0.003	0.003	0.003	0.002	0.001	0.003	0.002
	(0.002)	(0.002)	(0.002)	(0.002)	(0.002)	(0.002)	(0.002)	(0.002)
Unemployment (%) among foreign born	0.001	0.000	0.000	0.000	0.001	0.001	0.000	0.000
	(0.001)	(0.001)	(0.001)	(0.001)	(0.001)	(0.001)	(0.001)	(0.001)
Proportion of educatee attention schools that			ref.	ref.	ref.	ref.	ref.	ref.
Regularly use mandatory stand. tests			−0.038	−0.033	−0.040	−0.041	−0.036	−0.036
			(0.036)	(0.035)	(0.033)	(0.034)	(0.035)	(0.035)
Prop. of schools X starting time gen.				−0.085
				(0.056)
Prop. of schools 10 second gen.				−0.053
				(0.055)
Post achievement information publicly					−0.158*	−0.144*
					(0.067)	(0.069)
Achievement data publicly 10 first gen.						−0.160***
						(0.036)
Accomplishment information publicly X second gen.						−0.124***
						(0.029)
Provide adm. authority with achievement information							0.029	0.051
							(0.101)	(0.099)
Accomplishment data adm. dominance X beginning gen.								−0.179**
								(0.055)
Achievement data adm. dominance X second gen.								−0.125*
								(0.049)
Country and twelvemonth fixed effects	Yeah	Yep	Yes	Yes	Yes	Yes	Aye	Yes
Constant	0.065	0.453***	0.488***	0.481***	0.600***	0.593***	0.443*	0.437*
	(0.067)	(0.070)	(0.081)	(0.081)	(0.087)	(0.088)	(0.174)	(0.172)
N countries	30	30	30	30	30	thirty	30	30
N country–years	54	54	54	54	54	54	54	54
N schools	12,255	12,255	12,255	12,255	12,255	12,255	12,255	12,255
N students	422,172	422,172	422,172	422,172	422,172	422,172	422,172	422,172

In Models 5 and 7, accountability in terms of the provision of aggregated achievement data of schools to the general public (Model 5) or to administrative government (Model vii) is tested. Making achievement data available to the public is associated with a reduced probability of low reading performance amidst all students (b = −0.158, due south.e. = 0.067, Model five), while providing achievement data to administrative authorities is not associated with low reading operation (b = 0.029, s.e. = 0.101, Model 7). These findings thus just partly confirm the first hypothesis derived from the master-agent framework.

Models vi and 8 exam the 2nd hypothesis, which states that the communication of exam results is expected to be associated with a reduced take chances of low performance particularly among immigrant students. To facilitate interpretation, the Figures 2, ​ 3 graphically display the interaction effects. The left y-axis shows the predicted probability of low operation based on the respective regression model. The scale of the left y-centrality for each figure runs from 0.0 to 0.five; the figures thus encompass a range of fifty% points. The x-centrality displays the proportion of students attending schools within a country which provide accomplishment information to the general public (or an administrative authority). The background of each figure additionally shows a histogram of the empirical distribution of the country-year level variable, that is the proportion of students that nourish schools which provide information about achievement information to the respective recipient; this relates to the right y-centrality. Nosotros express the predicted values to an empirically reasonable range on the ten-axis, i.east., for which we have observations in the data.

Probability of low operation according to accountability (data posted publicly).

Probability of depression performance according to accountability (information provided to administrative regime).

Figures 2, ​ iii show a like blueprint: The more prevalent accountability is in a state, the lower is the risk of low performance among immigrant students. Figure ii shows a negative clan between the public provision of aggregated achievement information and the risk of low reading performance for all students. The association is strongest for beginning generation immigrant students, reducing the risk of low performance by nigh twenty percentage points beyond the range of x. Figure 3 displays the estimated associations betwixt the provision of aggregated accomplishment data to administrative authorities and the chance of depression reading performance. There is a comparatively small effect for first generation immigrant students, about 9 percent points across the range of x. While the clan is also negative for 2d generation immigrant students, statistical uncertainty is high, as indicated past the large confidence intervals. The association for non-immigrant students appears slightly positive, but is far from statistical significance. Thus, the results are generally compatible with our second hypothesis.

Robustness Check

To see if the results of the analyses are sensitive to the modeling approach, we have estimated two sets of boosted models. First, nosotros have re-estimated all models as logit models with state and wave fixed effects and cluster robust standard errors, using the same weights every bit in the LPMs (see Table A4 in the Appendix). The results of the logit models support the conclusions drawn from the LPMs, with regard to the management of the relevant coefficients and their statistical incertitude. The logit models, too, estimate statistically significant, negative interaction furnishings, indicating that the provision of aggregated achievement data to the general public or to administrative authorities is associated with a reduced probability of low reading achievement amidst immigrant, in detail first generation, students. Equally in the LPMs, standardized testing lone is not statistically significantly associated with the risk of low reading performance—neither for immigrant nor for non-immigrant students. 2d, we have re-estimated the models with the cross-level interaction as random issue models (with time fixed effect) and included random slopes for the interaction term. This may be necessary as leaving out a random slope for a cross-level interaction may crusade the standard errors to be biased down (Heisig and Schaeffer, 2019). The results (come across Table A5 in the Appendix) also back up the conclusions drawn from the LPM. The provision of aggregated accomplishment information to the public or to administrative authorities is associated with lower probability of depression reading achievement for immigrant students. However, statistical uncertainty for the latter association is also high, i.eastward., the interaction furnishings are not statistically significant.

Word and Outlook

In this paper, we examined the effects of standardized testing and the publication of schoolhouse accomplishment data on low reading functioning for immigrant and not-immigrant students in xxx OECD countries using a longitudinal design at the country level by combining OECD PISA data from 2009 and 2015. We conceptualized low functioning as the risk of performing below the so-called baseline level of reading proficiency in the PISA study (OECD, 2016, p. 164). With respect to immigrant students and their prospects for societal integration, functioning higher up this baseline level is crucial, every bit it measures 1's ability to fully participate in a guild (OECD, 2009b, p. 2). We aimed at providing a more directly test for arguments fatigued from the principal-amanuensis models (William and Michael, 1976; Ferris, 1992; Laffont and Martimort, 2002), which are often mentioned in research on standardized testing and educational performance (Wößmann, 2005) merely rarely direct tested.

Drawing on arguments from said principal-agent models, we hypothesized that standardized testing itself should not exist sufficient to forbid low operation of students. We argued that an outcome would only emerge if the principal, i.e., the administrative regime or parents, had access to results of such testing. This would alleviate the information asymmetry between principal and amanuensis, creating incentives for the amanuensis (i.e., the schoolhouse or the educatee) to forbid low performance. We furthermore expected immigrant students to profit more from this form of accountability than non-immigrant students, as they are often in need of special back up.

The results of our analyses of PISA 2009 and 2015 reading information show that first, the utilise of standardized achievement tests alone was not associated with the risk of low functioning. Second, making the results of standardized tests available to the public was associated with a decreased risk of low reading performance amongst all students, and tertiary, particularly amidst starting time generation immigrant students. While the analyses also tended to ostend this relationship if the testing results were fabricated available to an administrative say-so, the estimated associations were smaller and non equally robust. In a nutshell, the higher the share of schools that provide achievement data to the public, the lower is the adventure for students, in detail for outset generation immigrant students, to perform below reading level 2. These results were robust across the iii modeling approaches nosotros used: linear probability multilevel models with country and yr effects and adjusted standard errors for multiple clustering (Wooldridge, 2010; Correia, 2017), linear probability models with yr fixed furnishings and random slopes for the cross-level interactions (Heisig and Schaeffer, 2019) and cluster robust standard errors, as well equally logit models with country and yr fixed effects and cluster robust standard errors.

Overall, the results supported the hypotheses drawn from the main-agent-model, as they showed that the mere existence of regular assessments is non sufficient to mitigate the information asymmetry betwixt principal and agent if information from these assessments is not attainable. Assessments thus accept to exist combined with adequate measures of accountability in gild to incentivize the actors to align their efforts with the principal's goals. The effects of assessments and accountability become particularly apparent in the context of low operation and in detail for a specific group: immigrant students. We argued that assessments, which are often geared toward ensuring minimal levels of teaching, increase the incentives to support students at take chances. Every bit sufficient pedagogy is primal for immigrant integration, education policies which lower the take chances of low performance gain in importance.

Limitations

Our study has several limitations that should be considered. Outset, the strength of international comparisons as we conducted it, is the variation in institutional characteristics. Even so, although all countries belong to the OECD, they are notwithstanding heterogenous not the to the lowest degree with respect to their immigration history, which may be confounded with both educational institutions and (immigrant) pupil performance. We tried to approach this problem with a longitudinal approach at the land level, effectively controlling for all time-abiding differences between countries, by focusing only on changes in the institutional arrangements within countries over time. Nevertheless, we only have two measurements over time. What is more, although nosotros have tried to include the near relevant time-varying confounders at the country-year level, the estimated results are nonetheless prone to bias due to unobserved heterogeneity. Larger time-spans and boosted meaningful controls at the state-year level would strengthen the belittling blueprint. Second, it is unfortunate that PISA does not allow for a systematic and comparable differentiation of immigrant origin. We accept attempted to alleviate this problem partially by decision-making for different aspects of parental socio-economic condition and language utilise at home. Still, nosotros have to wait that the overall effect that we observed will vary across different countries of origin. All the same, the clan is clearly nowadays, fifty-fifty if the effect may exist heterogenous across immigrant groups. Third, we have chosen a four-level linear probability model to analyze the data for the reasons outlined in the Data and Methods department, since the potentially improve suited model (four level logit) could not be used. Nevertheless, comparisons of the LPMs' results with other modeling approaches (single level logit models and random intercept random gradient models) showed very similar results. This increases our confidence that the results are not artifacts of the modeling approach. Fourth, the main proportion of variance in educational operation, including the gamble of low performance, lies at the private level. If we inspect empty random effect models, the intra-class correlations for the country and the land-year level are estimated to being only around 0.03. This has to be taken into consideration, when evaluating the results. The depression intra-class correlation could be seen as an argument against investigating characteristics at the country(-yr) level. Clearly, individual factors are responsible for the larger share of variation in educational functioning. All the same, nosotros think that information technology is still relevant to clarify the role of institutional characteristics. From a policy perspective, institutional regulations are easier to adjust than students' characteristics. In a curt term perspective, the latter has to exist seen given. Profound noesis about the furnishings—albeit small—of institutional characteristics of education system is crucial if i is interested in shaping institutions which facilitate sustainable development and system integration of contemporary societies. Fifth, although we tried to put the propositions of the principlal-agent framework to a straight test, we still face a black-box. With the information at hand, we do not know for certain if the mechanisms that create the association between (immigrant) student accomplishment and the public provision of cess data stand for to those outlined in the principal agent framework. Further research could attempt to out fifty-fifty more specific hypotheses to the test. Our analyses fail to falsify predictions from the model, but should not be seen equally a proof that the model is correct.

In summary, our results show that the mere implementation of standardized assessments has no effects on low reading performance, neither for immigrant nor for non-immigrant students. In line with the predications from a principal-amanuensis framework, nosotros exercise find a general association betwixt provision of assessment information to the public and the chance for low reading operation. First generation immigrant students in detail have a reduced probability for low reading performance in countries that make cess data bachelor publicly.

Author Contributions

JT and RS accept jointly conceptualized and drafted the manuscript, approved information technology for publication, conceptualized the inquiry question, and the theoretical arroyo. JT has conducted the literature review. RS conducted the empirical analyses. All authors contributed to the commodity and canonical the submitted version.

Disharmonize of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

Nosotros thank Katja Pomianowicz for helpful comments on an before version of this manuscript.

Footnotes

¹1 might argue that the signaling mechanism that is often referred to in the literature is very specific (Bishop, 1995). Notwithstanding, we do non know of any study using large calibration cess data, like PISA, which explicitly tests the machinery, that is investigating if students really attach more value or importance to their education in the presence of standardized get out exams.

²https://world wide web.oecd.org/pisa/data/

³As the sampling design of PISA targets the student population, not the schools in a state, computation of country level variables by aggregation has to be done with the (weighted) student level information. Since the sampling frames in PISA aim to provide representative information on all eligible students within a land, the resulting variables measure the proportion of students in a state attending schools with a respective characteristic (e.grand., schools that make cess data publicly available).

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