interactions between cultural values and academic...

Interactions between Cultural Values and

Academic Achievement

Matthew Kendall

Northwestern University

MMSS Senior Thesis 2015

Advised by Professor Jim Spillane

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Table of Contents

Acknowledgements ..........................................................................................................................2

Abstract ............................................................................................................................................3

Introduction ......................................................................................................................................4

Literature Review.............................................................................................................................6

Ecological Model of Human Development .........................................................................6

Cultural Values ....................................................................................................................8

Culture and Context in Education ........................................................................................9

Research Questions ........................................................................................................................16

Methodology ..................................................................................................................................16

Data ....................................................................................................................................16

Regressions ........................................................................................................................18

Limitations .........................................................................................................................19

Results ............................................................................................................................................20

Simple OLS regressions .....................................................................................................20

Stepwise regressions ..........................................................................................................24

Discussion ......................................................................................................................................26

Religion ..............................................................................................................................26

Trust ...................................................................................................................................27

Independence .....................................................................................................................29

Work ..................................................................................................................................31

Comparing and Contrasting Subjects.................................................................................32

Conclusion ....................................................................................................................................33

Appendices .....................................................................................................................................35

Appendix I .........................................................................................................................35

Appendix II ........................................................................................................................38

References ......................................................................................................................................40

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Acknowledgements

I’d like to thank my advisor, Professor Jim Spillane for providing me guidance and

advice throughout this year. Moreover, I’d like to thank all the professors in the MMSS, LOC,

and mathematics departments that I’ve had over the past four years that have given me the

knowledge to complete this project.

I’d like to thank Professor Rogerson and Sarah Muir Ferrer for developing, leading, and

supporting the MMSS program and its students.

Finally, I’d like to thank my friends and family that have listened to and supported my

academic interests, edited my papers, and been there for me throughout my undergraduate career.

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Abstract

The literature on comparative education emphasizes the importance of cultural factors in

the performance of school systems. Yet, major cross national studies of the performance of

school systems do not consider cultural variables. This paper addresses this omission using data

from OECD’s most recent Program for International Student Assessment (PISA) together the

most recent wave of data from the World Values Survey (WVS) to examine patterns between the

cultural values and academic achievement. We conclude that cultures that promote independence

and trust in school-aged children perform better academically. Religious cultures perform worse,

and the tendency of a culture to promote hard work is independent of academic achievement.

Future research in this area should test some of the hypotheses we present and continue to

explore the relationship between cultural and contextual variables.

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Introduction

The performance of school systems is affected by a complex web of interconnected

factors, ranging from obvious factors such as classroom environment (Doyle, 1977) to less

obvious ones such as teacher expectations (Rosenthal & Jacobson, 1968). Because of this

complexity, any research conducted seeking to uncover causes of educational success must make

assumptions about the factors they are studying and the relationships between them. The

assumptions made by the researchers affect the methodology that they use, the results they

receive, and the recommendations and conclusions they create.

Over the past half century, comparative education research has emphasized the context of

educational performance. By context, we mean the factors at the student, school, and school

system levels that attempt to account for differences in performance across school systems. This

focus is understandable, as it is not helpful to know which school systems are successful without

knowing the factors that contributed to that success. Socioeconomic status, parents’ education,

school climate, school leadership, and school resources are all examples of contextual factors

that impact the outcome of a child’s education (Thapa, Cohen, Guffey, & Higgins-D’Alessandro,

2013; Robinson, 2007; Fensham, 2007). This tradition stretches as far back as George Bereday’s

(1964) model for comparative education. Two large cross national education assessments, the

Trends in International Mathematics and Science Study (TIMSS) and the Program for

International Student Assessment (PISA), both use conceptual frameworks that include many of

these contextual factors (OECD, 2013a; Mullis, Martin, Ruddock, O’Sullivan, & Preuschoff,

2009). Because these two studies have been influential in the field over the past two decades,

much of the research that builds off of PISA and TIMSS results attempts to further explore the

effect of one or more of the factors that plays a role in the one of the studies’ conceptual

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framework (Baker, 1997). Additionally, many reform efforts focus on altering one of the

contextual factors to improve student performance (Wang & Lin, 2005).

This popular conception is not the only way to think about the backdrop of education.

There is a rich tradition of literature that acknowledges that researchers should look beyond

contextual factors as discussed above and include broader societal factors, particularly cultural

factors (Alexander, 2001; Stevenson, 1998; Leung, 2006). While intuitive, cultural factors are

difficult to measure and investigate. Studies that emphasize cultural factors are either qualitative

and rely on data collected using ethnographic methods, or quantitative and use primarily survey

data. It seems that the prior methodology is more common. We often see cultural studies that are

case studies at the national level that seek to examine a small number of education systems in

detail, drawing connections between cultural and historical information and current practices and

structures (Alexander, 2001; Stevenson, 1998). However, despite the tradition of quantitative

work in the sociology of education, cultural factors are not included in the framework of either

the PISA or the TIMSS. Efforts such as the TIMSS Video Study indicate recognition that

understanding culture is important to understanding educational outcomes (Stigler, Gallimore,

and Hiebert, 2000). However, culture’s exclusion from the PISA and TIMSS conceptual

frameworks prevents culture from being integrated with some of the main results in comparative

education.

The relative treatment of culture and context is an open question and subject of active

debate (Fensham, 2007). To reiterate, context includes student, school, and school system factors

that influence academic achievement, while culture consists of the cultural values that a society

holds, which are notably absent from the frameworks of the PISA and the TIMSS. While it is

widely accepted that both play a role, it seems that contextual factors are favored because they

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are easier to identify and measure. However, there is alternative viewpoint which hypothesizes

that cultural factors have an overarching impact, interacting with everything from students’ self-

concept to assessment strategy (Fensham, 2007).

This paper attempts to reconceptualize the way that culture is treated in comparative

education research. Urie Bronfenbrenner’s ecological model will be used as a framework to

understand how context and culture work together to impact a student’s learning. Cultural values

will be employed to explore various dimensions of culture. Data from the most recent World

Values Survey (WVS) and PISA studies will be analyzed and discussed to support this

reconceptualization. The goal of this paper is to determine whether certain cultural values are

associated with academic achievement and what patterns exist among these values.

Literature Review

Ecological Model of Human Development

The ecological model of human

development is a methodology for the study of

human development that was developed by Urie

Bronfenbrenner in the 1970s. Generally, it is the

“the scientific study of the progressive, mutual

accommodation, throughout the life span, between

the growing human and the changing immediate

environments in which it lives” (pg. 514,

Bronfenbrenner, 1977). Furthermore, it is

“conceived topologically as a nested arrangement

of structures, each contained within the next” (pg. 514, Bronfenbrenner, 1977). The model relies

Figure 1: Ecological model diagram (Bronfenbrenner, 1977))

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on the principles of systems thinking. Therefore, researchers should consider not only how an

environment affects an individual, but as how an individual affects his or her environment.

Bronfenbrenner (1977) further encourages researchers to avoid thinking of variables as isolated,

but rather treat them as interconnected.

In Bronfenbrenner’s model, the individual lies at the center, with individual

characteristics that exist independently from the environment. Moving outward, the

microsystems are the next level in the environment. These are the settings of the environment

that an individual is immediately in. The home and school are two of the most commonly cited

examples for microsystems. Continuing, we find the mesosystem. This level contains the

relationships between the microsystems. For instance, when researchers investigate the effect of

family background on student’s academic achievement, they are looking at development from

the perspective of a mesosystem. The exosystem is composed of institutions that do not

necessarily contain the individual, but affect the settings that an individual is in. Public policy,

the media, and neighborhoods are all found at this level. Finally, the last level is termed the

macrosystem. This differs from the other levels in that it contains the overarching ideological

patterns and attitudes in which the other levels are situated. This includes the culture and history

underlying an individual’s environment (Bronfenbrenner, 1977). See Figure 1 for an illustration

of the model.

For this study, we will reconceptualize the constructs of culture and context using

Bronfenbrenner’s (1976) model. Context lies within and between the micro-, meso-, and exo-

systems, and the individual student at the center of the model. Self-esteem, for example, is an

individual characteristic that is related to educational achievement. Factors of the school, family,

and peer groups are aspects of microsystems that influence academic achievement. The

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relationships and interactions of variables in these settings are found in the mesosystem. This

includes factors like socioeconomic status and family background. The exosystem includes the

larger policy landscape and structure that schooling occurs in. This includes education policy at

the local and national level as well as the structure of the education systems. Cultural values lie

in the primarily macrosystem. However, the environments of Bronfenbrenner’s model are nested

and interrelated, so the presence of cultural values in the macrosystem influences factors in the

other environments. This paper will focus primarily on how cultural values impact the student at

the center of the model.

Cultural Values

One critical issue when doing quantitative research with culture is choosing a method to

operationalize the concept. For this paper, we will turn to cultural value theory as advocated by

Geert Hofstede in the 1980s. A review of the literature on cultural value theory demonstrates that

“values have been the dominant construct guiding cross-cultural research at the national level”

(pg. 552, Bond et al., 2004). Hofstede defines a value as “a broad tendency to prefer certain

states of affair over others” (pg. 19, Hofstede, 1980). A value may be held by individual or as a

collective society. Following this definition, we will conceptualize a society’s values as the

aggregate of its individuals’ values. Hofstede defined four dimensions of culture: Individualism-

Collectivism, Power Distance, Uncertainty Avoidance, and Masculinity-Femininity (Hofstede,

1980). This was a groundbreaking work that kicked off an era of researchers using values as a

way to measure culture. Others tried to build on Hofstede’s work by developing their own

dimensions of culture. Schwartz (1994) developed a system that used 7 dimensions, and Smith,

Dugan, and Trompenaars (1996) developed a two dimensional map for culture within

organizations. Despite the development of various frameworks in this vein, later studies have

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demonstrated that most of the dimensions researchers propose correlate to one or more of

Hofstede’s original dimensions (Bond et al., 2004). As a result, Hofstede’s work is often used to

validate comparative research.

The model of cultural

values used in this paper is the one

proposed by Inglehart and Welzel,

because it comes from a direct

analysis from the WVS data. They

identified two dimensions of

cultural variation: traditional versus

secular-rational orientation and

survival versus self-expression

orientation (Inglehart & Baker, 2000).

Participating countries were placed on a coordinate plane, and Inglehart created groupings based

on common features (see Figure 2). While these dimensions were developed primarily with

historical and political implications in mind, we hypothesize that similar groupings and patterns

will be uncovered when considering the educational performance of different nations.

Culture and Context in Education

Now that we have introduced the ecological theory and the theoretical basis for cultural

values, we will return to the literature on how culture and context are used in comparative

education research. Because both the PISA and the TIMSS have been two of the largest and most

influential projects in the field, we begin with an overview of each of their conceptual

frameworks.

Figure 2: Inglehart-Welzel culture value plot

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TIMSS publishes their framework in order to “collect information about the important

factors that foster improved teaching and learning” because “learning takes place within a

context and not in isolation” (pg. 93, Mullis et al., 2009). Their framework covers four broad

areas: national and community contexts, school contexts, classroom contexts, and student

characteristics and attitudes. Although the framework states that the values system of a

population and the culture surrounding an education system are among these important factors,

they build national and community context based on demographics, resources, structure of the

education system, and curriculum. School context is similarly developed. School size, location,

demographics, and resources are all considered. Finally, TIMSS includes school climate, or

organizational culture at the school level. The classroom context is built from teacher

characteristics and includes factors like class size, resources available, curriculum, instructional

activities, and assessment strategies. Student characteristics include the well-documented effects

of home background and family life as well as student attitudes and beliefs towards the subject

matter (Mullis et al., 2009). Note that while TIMSS recognizes that generally culture has an

impact, they do not attempt to measure it. They instead make the assumption that it is captured in

factors of their framework.

Similarly to their TIMSS counterpart, the PISA publishes a framework supporting the

design of their background questionnaires. The questionnaire must “cover the most important

antecedents and processes of student learning at the individual, school, and system level” in

order to better understand how and why students achieve academically (pg. 48, OECD, 2013a).

The PISA framework is similar to the TIMSS framework, in that it treats context at the same four

levels and includes many of the same factors. A table demonstrating the contextual factors

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deemed important is shown below. Again, there is limited consideration of culture at the system

level.

Figure 3: Description of PISA contextual framework (OECD, 2013b)

PISA’s results reflect their conceptual framework. After their most recent study, they

published three volumes that identify what factors best help students perform. The first details

how socioeconomic factors, the structure of education systems, and the distribution of resources

throughout the system can create or reduce inequality in educational access and outcomes

(OECD, 2013c). The second looks more closely at individual student factors and the patterns in

their effects (OECD, 2013d). Lastly, the third takes a broad policy-focused approach when trying

to identify important factors (OECD, 2013e). Beyond this, PISA publishes a number of country-

specific summaries designed to concisely present important results for a country. All of these

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reports draw heavily on the PISA framework, and are accordingly light on their inclusion of

broader cultural factors.

TIMSS published similar reports after their last wave of data collection, although results

were largely separated by academic subject before specific factors were discussed. The effects of

home environment, school resources, school climate, teacher preparation, and classroom

instruction were discussed in detail for both math and science (Mullis et al., 2012a; Mullis et al.,

2012b). Again, cultural factors are largely ignored these analyses.

Many other studies adopt similar frameworks. Niemi, Toom, and Kallioniemi (2012)

discuss in detail the factors that led to Finnish success on the PISA assessment. They first present

the PISA results, discuss contextual aspects of the Finnish education system and how they relate

to those results, and then analyze how some of those aspect, namely teacher quality and between-

school equity, are rooted in the history and culture of the Finnish education system. Similar

analyses have been performed for other nations.

Another study seeking to evaluate cultural differences was conducted by Wang and Lin

(2005). They investigate the causes of the differences in performance between Chinese and

American students in mathematics. While they start with a discussion of previously researched

differences in contextual factors like teacher education programs and national curriculum

policies, they look more closely into cultural factors as well. This is primarily because there is a

body of literature that notes that Chinese students outperform American students in mathematics

even before formal schooling has started (Geary, Bow-Thomas, Liu, & Siegler, 1996). However,

despite treating culture generally, the authors return back to PISA contextual variables and

examine how student-teacher relations, school climate, and language differences create some of

the effects. While these factors are certainly related to cultural values, by using these contextual

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factors the authors ignore the interaction between the cultural values and their more tangible

manifestations like student-teacher relations.

Other studies have looked to explain school climate (Thapa et al., 2013) or school

leadership patterns (Robinson, 2007; Leithwood, Harris, & Hopkins, 2008). Many have

attempted to investigate country-level PISA or TIMSS results in greater detail (Wiberg,

Rolfsman, & Laukaityte, 2013). Even papers that attempt to research cultural effects tend to limit

their results so that fit nicely into a contextual factor like teacher or parental expectations, school

climate, student attitudes, or school system structure (Chen & Uttal, 1988; Wang & Lin, 2005;

Leung, 2006).

Over-reliance on the contextual framework used by PISA and TIMSS has faced criticism

in the research community. Some researchers point out inconsistencies in the effects of

contextual variables. For example, it was noted that “it is naïve to argue that the higher degree of

focus in the curriculum in Japanese schools compared with those in USA schools is a reason for

Japan’s higher performances, when the same relative difference in curricular focus occurs

between the USA and other countries that have achieved lower scores than the USA” (pg. 156,

Fensham, 2008). Others, primarily Americans, questioned the validity of the study designs and

sampling methods, partly in an effort to explain their country’s relatively weak performance

(Fensham, 2008). Yet other researchers sought to isolate a small number of contextual variables

that explained most of the differences (Fensham, 2008).

However, perhaps the strongest voice in the criticism is from David Baker (1997). In a

response to the first wave of the TIMSS study, he urged a mediated response. He cited A Nation

at Risk, a famous response to less-than-ideal American performance on international

comparisons in the 1980s, as an example of an overreaction to more recent international

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assessment results. While Baker believes that valid international comparisons are possible, he

also thinks that they encourage overreactions in both academia and in education policy. He sees

results of international education assessments as an opportunity to investigate the systems that

education occurs in broadly. He further claims that this does not occur, as often the media and

policymakers tend to identify and isolate a small number of factors instead.

One of the primary reasons supporting a more moderate response, as recommended by

Baker, is the difficult in transplanting policy from one culture to another. Robin Alexander

devoted most of his life’s work to the theory that teaching is a cultural activity. He argues that

“the central educational activity, pedagogy, … is a window on the culture of which it is a part,

and on that culture’s underlying tensions and contradictions as well as its publicly declared

educational policies and purposes” (pg. 168, as cited in Fensham, 2008). Furthermore, Fensham

believes that efforts to transplant one piece of the pedagogical process from one culture to

another demonstrate a failure “to understand the complexity of the processes of

teaching/learning, and how deeply embedded they are in cultures of education, defined in quite

unique ways by national histories” (pg. 168, Fensham, 2008). Hargreaves (2012) also discusses

the cultural embeddedness of public policy. He cites the example of selective enrollment.

Hungary and Finland both have successful educational systems, despite the fact that they lie on

opposite ends of the selective enrollment spectrum. It is clear that policies aimed to improve

certain aspects of education context need to consider cultural factors, rather than simply

mirroring exactly the policies and structural features of other, more successful countries.

Partially in response to this criticism, there has been an effort to investigate different

paradigms of education, including many frameworks that look into the effect of culture on

education. The TIMSS Video Study sought to add to the datasets generated by the TIMSS

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assessments and questionnaires by videotaping classrooms in Japan, Germany, and the United

States and qualitatively analyze them. It revealed a number of interesting results, including that

that “the educational systems of different countries are embedded within the culture of each

country” (pg. 529, Stevenson, 1998). Much of the research that investigates the culture of

education system uses similar qualitative methodologies. Tweed and Lehman (2002) use this

method in his thesis explaining the different educational outcomes of the Socratic and Confucian

tradition. Robin Alexander’s (2001) book Culture and Pedagogy: Comparisons in Primary

Education also relies heavily on ethnographic methodology.

Others tried to bypass the heavy time and resources commitments necessitated by

ethnographic methodology and explored culture by digging deeper into the TIMSS, PISA, and

other similar assessment data. Leung (2006) reviews assessment results of East Asian countries,

and concludes that their shared culture must be a leading factor. Grønmo, Kjærnsli, and Lie

(2004) identify patterns in TIMSS responses, group nations based on these patterns, and then

explain the groupings using linguistic and cultural information. Uttal and Chen (1988) look at

how certain cultural values, particularly those explicitly related to the education system, affect

the context of education of students in China and the U.S.

While there is certainly plenty of literature indicating a wide consensus that culture plays

a key role in determining the success of education systems, there is little research examining the

overall effect of different cultural values. Most prefer to use values that are either directly related

to the education system (i.e. how much teachers are valued in a society) or ones that are clearly

related to certain contextual variables (i.e. parental expectations). The data from theWVS, which

has yet to be used to analyze the performance of educational systems, could be analyzed

alongside PISA data to uncover these effects.

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Research Questions

Our literature review leads to the following research questions: Does strength of cultural

values affect academic achievement in a country? Which values are most important for academic

achievement? What patterns exist?

Methodology

Data

Two datasets were used to answer some of the questions posited above: the PISA 2012

dataset and the WVS Wave 6 dataset.

Both the complete PISA 2012 dataset (OECD, 2012f) and all relevant documentation are

available online to the public. The dataset contains the results of the 5th PISA study. The dataset

is quite large. It contains the assessment results of more than 500,000 students aged either 15 or

16 from more than 60 different countries across the globe. The assessment was paper-based and

two hours long. It contained a combination of multiple choice and open-ended response

questions designed to test the student’s competencies in reading, mathematics, and science. In

addition, students and their principals submitted background questionnaires to better describe

and the background of a student or school and thus the context of their results. Furthermore, a

smaller number of students participated in problem-solving skill assessments and an even smaller

number participated in a financial literacy assessment.

Despite the wealth of information available in the dataset, this paper will utilize just a

small portion of it. The data to be analyzed from the 2012 PISA survey are the national average

scores for reading, mathematics, and science. These results are widely published (OECD, 2014).

This selection was made for several reasons. The first and foremost is the exploratory nature of

this paper. We are attempting to uncover wider trends and interactions between cultural values

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and academic achievement. Further research will be able to dig deeper into the PISA set and

attempt to augment the results of this paper. The second reason is sample size. Because we are

analyzing data on a national level, sample size is a concern. Attempting to analyze the smaller

datasets on problem solving and financial literacy becomes potentially problematic because there

are only a handful of nations that fall in this group and are among the respondents of the most

recent WVS. Finally, much of the data available in PISA relates to the context of education

rather than the culture surrounding education. There will be opportunity for further research to

examine how culture interacts with contextual factors, but that is beyond the scope of this paper.

In addition to the PISA dataset, the WVS Wave 6 dataset was also used. It is also

available online to the public (World Values Survey, 2014). Surveys were administered over 5

years, from 2010 to 2014. More than 85,000 people from more than 50 countries responded to

the survey. Previous research using the WVS data has shown a number of interesting patterns

regarding aspirations for democracy, empowerment of citizens, globalization and convergent

culture, gender values, religion, and happiness and life satisfaction. However, it has yet to be

applied to education. The WVS survey consists of nearly 200 multiple choice questions designed

to give information on respondents’ cultural values. Examples of these questions include “How

important is family in your life?” and “Is determination and perseverance an important quality

that children should be encouraged to learn at home?” While most cultural values of interest

have several questions associated with them, not all do. This is a notable weakness in the dataset.

Similar to the PISA dataset, only certain variables from the WVS Wave 6 data were

selected. While there was no systematic or rigorous method to describe the selection, choices

were made to reflect how previous literature describes the effect of culture on education.

Generally, because the marginal cost of analyzing an additional variable was small, decisions to

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include a variable were generous. 64 of the variables in the WVS dataset were included in our

regressions. A full description of the variables that were selected can be found in Appendix I.

Once the relevant variables from the WVS dataset were identified, they needed to be

transformed from individual responses to national averages. This work was done primarily in

Microsoft Excel and SPSS. This reduced the number of observations in the WVS dataset from

more than 85,000 to roughly 60. The final step in preparing the data for analysis is to combine

the variables from the two datasets into one file. This was a straightforward process, except that

only observations that appeared in both datasets were permitted to be included. There were 32

nations that fell in this intersection. Thus our final dataset included 32 observations and 67

variables, 3 from the PISA study and 64 from the WVS study. While the low number of

observations is a potential problem from a statistical perspective, the simplicity of our

methodology prevents major issues. Issues that are present will be discussed as they arise later.

Regressions

Analysis of this data proceeded in two ways. The first was a series of simple ordinary

least squares (OLS) regressions, and the second was a series of stepwise regressions. Both were

carried out with the goal of uncovering patterns in the relationships between the cultural

variables and the academic variables.

A total of 192 simple OLS regressions were performed. An example of one such

regression using the standard model is shown below:

𝑠𝑐𝑜𝑟𝑒_𝑚𝑎𝑡ℎ𝑖 = 𝛼 + 𝛽(𝑣4𝑖) + 𝜀𝑖

In each of the regressions, one of the three PISA scores (math, reading, or science) is

used as the dependent variables. In the above example, that variable is 𝑠𝑐𝑜𝑟𝑒_𝑚𝑎𝑡ℎ𝑖. One of the

64 variables from the WVS data is used as an independent variable. In the above example, that

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would be 𝑣4𝑖 . This method was used because it required fewer assumptions than specifying a

larger and more complicated model. While, these regressions helped uncover which variables are

potentially relevant, the results from this method should be treated carefully. Namely, the

simplicity of two-variable OLS regressions prevents us from making claims of causation.

In addition to the simple OLS regressions, 12 stepwise regressions were performed. The

procedure for stepwise regressions using the options that we selected in STATA is as follows:

1) Create a standard OLS model using the specified dependent and independent variables.

2) Find the independent variable that is “least” significant.

3) If this variable has a significance level greater than 0.20, drop this variable and repeat

the procedure. Otherwise, end the procedure.

In each of these regressions, the dependent variable is again one of the three PISA scores,

and a series of variables from the WVS are the independent variables. Four groups of WVS

variables were used.

Stepwise regression was used because there several runs of variables in the WVS data

that were very similar to each other. For instance, participants were presented a list of 11

different qualities and asked which, if any, were important for children to learn. While stepwise

regressions are not ideal for determining the overall significance of a particular model, they are

useful in identifying which subgroup of a group of similar independent variables are most

predictive of the given dependent variable.

Limitations

There are a few notable limitations to our methodology. The first being that culture is a

concept that is difficult to define, and by using quantitative data to operationalize it we are

necessarily leaving some information behind. As explored in the literature review above, most

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researchers of culture avoid this limitation by completing qualitative analyses. However, given

the history of using cultural variables in quantitative studies, we maintain that this methodology

can lead to valuable information.

Secondly, culture interacts with the learner via a complex system. Therefore, we stress

that correlation between the cultural and academic variables should not necessarily imply

causation. However, the patterns that exist between these two data sets add another perspective

which can be valuable to the field and to future researchers.

Keeping these limitations in mind, we proceed to present our results and discuss their

implications.

Results

OLS Regressions

The majority of our dataset had 31 or 32 observations for each variable. Table 1 below

summarizes the data. Regressions with slope coefficients that were significant at the 5 percent

level were shaded either red or green, while those that were not are shaded grey. Green shading

indicates that the coefficient had a positive value, while red indicates a negative value. In

addition to this, a table that displays the coefficient value, the p-value, and the R2 value for each

of the regressions is included as Appendix II.

Notice that 36 of the WVS variables was significant for at least one of math, reading,

and science. Generally, a variable was either significant in all three subjects or significant in no

subject. The only two exceptions are variable V14, which was significant only for math, and

variable V17, which was significant for math and science but not for reading. Also, keep in mind

that a positive or negative coefficient does not indicate a positive or negative relationship with

academic achievement. For instance, consider variable V5. It has a negative slope coefficient,

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but lower responses indicate that friends are more important to your life. It is interpreted as

societies that value friendship more highly tend to have better academic performance.

Table 1: Significant slope coefficients (α = .05)

Variable score_math score_reading score_sci

Variable score_math score_reading score_sci

V4

V74 + + +

V5 - - -

V75 + + +

V6

V76

V7

V77 + + +

V8 + + +

V78 + + +

V9 + + +

V79 + + +

V10

V95

V11

V96

V12 - - -

V100

V13

V102

V14 -

V103

V15

V104 - - -

V16

V105 - - -

V17 - -

V106 - - -

V18 - - -

V107 - - -

V19 + + +

V119

V20 + + +

V140

V21 + + +

V143 + + +

V22

V145 + + +

V23

V146 + + +

V24 - - -

V147 + + +

V49 + + +

v148 + + +

V52

V149 + + +

V55 - - -

V152 - - -

V56

V157 - - -

V57

V158

V58 - - -

V159

V59

V248 + + +

V70 + + +

V249

V71

Y001

V72 + + +

Y002

V73 + + +

Y003 + + +

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In order to gain additional insight on the structure of the data and the statistics produced

from the regressions, two-way scatterplots were created. The scatterplots allowed us to easily

visualize outliers and how well a linear regression fits the data. To save space, we will simply

show a couple of examples here. The remaining scatterplots will be referenced as needed in the

discussion.

Finally, we will conclude the OLS results with a few of tables. The first highlights the

magnitude of some of the significant regressions. This reflects the magnitude of the effect of

certain variables without having to include the scale, which varies from variable to variable.

Notice that, as with the table above, variables that appear on this table tend to appear on it

multiple times. For instance we have only 14 unique variables filling the available 36 slots.

However, it is interesting to consider the various positioning of different variables. For instance,

the regression on variable V12 has an 𝑅2 value of .444, meaning that nearly half of the variation in

mathematics performance can be accounted for by considering this variable. However it ranks lower in

reading, with a value of .337. Because V12 reflects a society’s tendency to encourage

independence in a child, does this imply that independence is more important for achievement

for mathematics than it is for reading? We will discuss implications such as this below.

Figure 4: Example scatterplots with regression line and confidence interval

23

Other important variables to consider are Y003, which stands at the top of the list for all

three categories, and V152, V19, and V147, which are all variables that reflect the importance of

religion in a society.

Table 2: Regressions with the highest R2

Math Reading Science

Variable

𝑅2 Variable

𝑅2 Variable 𝑅2

Y003 0.691 Y003 0.608 Y003 0.683

V19 0.498 V79 0.490 V152 0.551

V152 0.488 V8 0.475 V8 0.522

V79 0.486 V152 0.472 V79 0.511

V147 0.460 V19 0.465 V19 0.491

V12 0.444 V147 0.427 V147 0.468

V8 0.439 V24 0.413 V9 0.465

V21 0.439 V74 0.401 V24 0.453

V74 0.436 V9 0.393 V74 0.443

V24 0.414 V21 0.387 V12 0.424

V70 0.411 V77 0.365 V146 0.394

V9 0.402 V12 0.337 V77 0.379

To get a complete perspective on the patterns between the cultural variables and the

academic variables, it was also necessary to examine the variables that were not significant in the

regressions. Table 3 shows the variables that had the highest p-values for each category below.

Again, this table allows us to explore some of the similarities that exist between the

subjects. There are 9 variables appearing on the list for all three subjects and variable V59 is at

the top of each column. This table is notable for some of the variables that we wouldn’t expect to

see in this category, based on previous literature. For instance, V100 and V13 relate to the

importance of hard work. We would expect to find a positive trend for these variables, but that is

not the case.

24

Table 3: Regressions with the highest p-value

Math

Reading

Science

Variable p-value Variable p-value Variable p-value

V59 0.904 V59 0.926 V59 0.801

V15 0.870 V140 0.859 V140 0.769

V16 0.813 V13 0.772 V249 0.646

V140 0.772 V249 0.734 V13 0.621

V249 0.618 V15 0.590 V119 0.619

V119 0.604 V16 0.581 V15 0.555

V13 0.591 V119 0.578 V16 0.531

V96 0.583 V76 0.513 V102 0.473

V102 0.470 V103 0.442 V7 0.457

Y002 0.470 V100 0.400 V76 0.395

V100 0.413 V96 0.387 V103 0.332

V7 0.410 V102 0.354 V96 0.319

Stepwise regressions

Table 4 below shows the results from each of the stepwise regressions. The leftmost

column contains the set of variables that were initially included in the model. The three right-

hand columns show the variables that remained after the stepwise analysis was performed. Refer

to Appendix I for descriptions of the variables used.

The outcomes of these regressions help give us an idea of what variables are most

important in predicting educational achievement. The first regression includes the variables

related to how important certain aspects of life are in a particular society. The results indicate

that including the variables that reflect the importance of politics, work, and religion are better

able to predict academic achievement. The importance of family, friends, and leisure time were

dropped by the regression procedure.

The second stepwise regression is run on variables that concern what qualities are

important to encourage in children at home. Academic achievement could be best predicted

25

based on the importance of teaching independence, religious faith, and unselfishness. The

importance of teaching children about hard work is notably dropped by the procedure.

The third regression explores how trustworthiness and academic achievement interact.

For each subject, trust in your neighborhood, friends and acquaintances, people that you’ve just

met, and people of foreign background are the best predictors of academic achievement. It’s

interesting that the variable that measures how much trust you have in your family and your

neighborhood are not as predictive as the other trust variables.

The final regression begins with a handful of religion variables. This was included to get

an idea if certain aspects of religion were more predictive of academic achievement or not. The

results indicate that once self-reported answers to the question “Would you say that you are a

religious person?” were included in a regression model, the other religious variables (V145,

V146, V148, and V149) did little to improve the fit of the regression.

Table 4: Results of the stepwise regressions


Initial Variables

Final

Variables

Final

Variables

Final

Variables

V4, V5, V6, V7, V8, V9 V7, V8, V9 V7, V8, V9 V7, V8, V9

V12, V13, V14, V15, V16, V17, V18, V19, V20, V21, V22

V12, V17, V19,

V20 V12, V19, V20

V12, V18, V19,

V20

V102, V103, V104, V105, V106, V107

V103, V104,

V105, V107

V103, V104,

V105, V107

V103, V104,

V105, V107

V145, V146, V147, V148, V149 V147 V147 V146, V147

In general, the results presented above present some significant and surprising ways that

cultural values interact with academic achievement. Much of the results confirm some of the

results in previous literature, while others seem to call into question some of it.

26

Discussion

Religion

Variables V9, V19, V145, V146, V147, V148, V149, and V152 all ask explicitly about

various aspects of religious beliefs and practices. Each of their full descriptions is given in Table

5 below.

Table 5: Overview of religion variables

Variable Label Questions Scale

V9 Important in life: Religion

For each of the following, indicate how important it is in your life.

Would you say it is:

Religion

1 = Very important

4 = Not at all important

V19 Important child qualities: Religious faith

Here is a list of qualities that children can be encouraged to learn at

home. Which, if any, do you consider to be especially important?:

Religious faith

1 = Mentioned

2 = Not mentioned

V145 How often do you attend religious services Apart from weddings and funerals, about how often do you attend

religious services these days?

1 = More than once a week

6 = Less than once a year

V146 How often to you pray Apart from weddings and funerals, about how often do you pray? 1 = Several times a day

8 = Never, practically never

V147 Religious person Independently of whether you attend religious services or not,

would you say you are:

1 = A religious person

3 = An atheist

V148 Believe in: God Do you believe in God? 1 = Yes

2 = No

V149 Believe in: hell Do you believe in hell? 1 = Yes

2 = No

V152 How important is God in your life How important is God in your life?. Please use this scale to indicate.

10 means “very important” and 1 means “not at all important.”:


10 = Very important

Each of these variables has a significant regression coefficient, and each suggests that the

stronger a culture encourages religious faith, the worse that culture performs academically. These

results are shown in the table below. Notice that we see the same direction in the effects among

each of the variables, suggesting that together they measure some underlying cultural value. The

exception is V152, which has a scale that is opposite of the other variables.

27

Table 6: Religion variables regression results


Variable �̂� p-value 𝑅2 �̂� p-value 𝑅2 �̂� p-value 𝑅2

V9 59.1 0.000 0.402 50.5 0.000 0.393 58.4 0.000 0.47

V19 184.7 0.000 0.498 154.2 0.000 0.465 168.5 0.000 0.49

V145 31.1 0.008 0.217 26.0 0.011 0.204 30.1 0.005 0.24

V146 24.7 0.000 0.353 20.3 0.001 0.321 23.8 0.000 0.39

V147 146.6 0.000 0.460 122.1 0.000 0.427 136.0 0.000 0.47

v148 162.8 0.002 0.291 146.0 0.001 0.312 165.0 0.001 0.36

V149 94.0 0.040 0.142 87.0 0.028 0.162 102.1 0.013 0.20

V152 -21.5 0.000 0.488 -18.3 0.000 0.472 -21.0 0.000 0.55

Furthermore, a stepwise regression was performed on variables V145 through V149. The

results of this regression indicated that you merely needed one of the religion variables, namely

V147, to predict academic performance. This supports the idea that the effect of each of the

religion variables are similar, in that adding additional variables to a model already containing a

religious variable will not add much explanatory value to the model.

While the relationship between a country’s propensity for religion and academic

performance seems consistent in our analysis, this is where the simplicity of our model is a

weakness. While this result fits the narrative that religion is in conflict with widely accepted

scientific theories (i.e. evolution, the Big Bang), it would be overstepping to say that this

demonstrates that religion and education are fundamentally at odds. Rather, it seems likely that

there are third variable problems in these regressions. Despite this, they do provide some

interesting directions for potential research. For instance, future research might try to determine

how significant these religion variables are while controlling for the usual contextual variables.

Trust

The connection between trusting others and academic achievement was clear throughout

our results. A full description of the variables that relate to trust are included in Table 7 below.

28

Table 7: Overview of trust variables

Variable Label Question Scale V24 Most people can be

trusted

Generally speaking, would you say that most people can be trusted or that you need

to be very careful in dealing with people?

1 = Most people can be

trusted

2 = Need to be very careful

V102 How much you trust:

Your family

I‘d like to ask you how much you trust people from various groups. Could you tell

me for each whether you trust people from this group completely, somewhat, not

very much or not at all? Your family

1 = Trust completely

4 = Do not trust at all


Your neighborhood



very much or not at all? Your neighborhood




People you know

personally



very much or not at all? People you know personally




People you meet for the

first time



very much or not at all? People you meet for the first time




People of another

religion



very much or not at all? People of another religion




People of another

nationality



very much or not at all? People of another nationality



Variable V24 had a significant regression coefficient for all three subjects, indicating that

societies with cultures that promote trust between its citizens tend to perform better

academically. The scatterplots for these regressions are below.

In addition, while variables V102 and V103 resulted in insignificant regressions, while

V104, V105, V106, and V107 resulted in significant regressions. These variables had had the

same direction of correlation as did V24. Moreover, these six variables were run through a

stepwise regression. These regressions indicated that restricted to these variables, V103, V104,

V105, and V107 would be best for predicting academic achievement.

These results seem to further the idea that learning is less of an individual activity and

more of a social one. If not, whether or not students and teachers can trust those around them

Figure 5: Scatter plots for V24

29

would be irrelevant to academic outcomes. This supports the Bronfenbrenner model, in that the

various systems of a student’s environment are connected. Moreover, it strengthens the claim

that cultural variables are important to consider when studying education.

A final aspect of these results is that trust in family and neighbors is much less important

than trust in those that are less similar to oneself and less connected with one’s life. We

hypothesize that this occurs for two reasons. The first is that there might not be enough variation

in trust of family and neighbors between the countries in the sample to get an accurate idea of the

relationship between these variables and academic achievement. The second is that trust of those

that think differently than oneself is more important for learning than those that think similarly.

Being able to respect and consider different ideas, especially those that are different than your

one, is a critical skill for academic achievement.

Independence

Another trait that stood out in terms of positive connection to academic achievement was

independence. A description of three variables that capture this value is given in Table 8 below.

Table 8: Overview of independence variables

Variable Label Question Scale V12 Important child

qualities: independence

Here is a list of qualities that children can be encouraged to learn at home.

Which, if any, do you consider to be especially important?:

Independence

1 = Mentioned

2 = Not mentioned

V18 Important child

qualities:

Determination,

perseverance



Determination and perseverance

1 = Mentioned

2 = Not mentioned

V19 Important child

qualities: Religious faith



Religious faith

1 = Mentioned

2 = Not mentioned

V21 Important child

qualities: Obedience



Obedience

1 = Mentioned

2 = Not mentioned

Y003* Autonomy Index Autonomy Index is a computed variable based on the Children qualities battery. -2 = Religion/obedience

2 = Independence/determination

The strongest evidence for the claim that independence among children supports

educational achievement comes from variable Y003. This is an index of four other variables,

namely V12, V18, V19, V21, and is computed as follows:

30

𝑌003 = (𝑉19 + 𝑉21) − (𝑉12 + 𝑉18)

This encompasses two variables already discussed in this section, as well as V18 and

V19, which have been mentioned in previously and reflect the importance of encouraging

determination and religious faith in children. The regressions on Y003 have the largest R2 of our

regressions by a large margin (see Table 2 above). The scatterplots for each of the three subjects

are below.

This result was expected, and aligns with some of the previous literature. As discussed

above, student motivation, self-concept, and self-belief are all concepts that have been used to

predict educational achievement. The development of independence is certainly related to those.

Moreover, Finland is often lauded for its encouragement of independence in its students.

The idea of play-based learning has often been connected to developing independence in

students (Hyvonen, 2011), and recently the nation has been making headlines for their decision

to teach “topics” based on student interests rather than the traditional subjects (Garner, 2015).

This recalls issues presented above regarding policy transfer. Is independence in Finnish children

developed due to the structure of their school system, or because it is a part of the culture that

they grew up in? Questions like this can be answered with future research applying cultural

values to education.

Figure 6: Variable Y003 scatterplots

31

Finally, it is worth noting that while most studies on concepts related to independence

consider their respective measure on the student level, while this study considers it from a

societal perspective. The difference is asking “What about that student’s cultural background

encourage him or her to be independent?” rather than “What is encouraging that particular

student to be independent?” While subtle, it can be important is guiding how we think about

improving academic achievement.

Work

Two variables, V13 and V100, which target the various aspects of hard work fail to be

significant and another, V8, has a correlation opposite to our intuition. Table 9 has descriptions

for these variables.

Table 9: Overview of work variables

Variable Label Questions Scale

V8

Important in life:

Work

For each of the following, indicate how important it is in your life.

Would you say it is:

Work

1 = Very important


V13

Important child

qualities: Hard work



Hard work

1 = Mentioned

2 = Not mentioned

V100

Hard work brings

success

Now I'd like you to tell me your views on various issues. How

would you place your views on this scale? 1 means you agree

completely with the statement on the left; 10 means you agree

completely with the statement on the right; and if your views fall

somewhere in between, you can choose any number in between.

"In the long run, hard work usually brings a better life" vs. "Hard

work doesn’t generally bring success—it’s more a matter of luck

and connections"

1 = In the long run, hard work usually brings a

better life

10 = Hard work doesn’t generally bring success

– it’s more a matter of luck and connections

Both V13 and V100 are among the variables that are insignificant with notably high p-

values, as seen in Table 3. Previously, we would have hypothesized both of these to have

positive effects on academic outcomes. Moreover, V8, is significant, but indicates that the more

value that a nation’s citizens place on work, the worse that nation’s academic achievement.

A potential explanation for this is that academics is often disassociated with the value of

hard work, and that work towards one’s vocation or career competes with one’s academic work.

The results for the regression on V8 would support the second part of that hypothesis, as the

32

wording in the question is more ambiguous than for the other two variables. The question seems

more likely to be interpreted as “How important is your career in your life?” than “How

important is working hard in your life?” V13 and V100 ask more explicitly about the value of

hard work, and thus support the idea that the value of hard work is disassociated with academic

work. Further research will need to be completed to support this hypothesis.

Comparing and Contrasting Subjects

In general, the results for the regressions varied little across subjects. Cultural variables

that were either significant in all three subjects or insignificant in all three subjects. Furthermore,

the p-value, R2 value, and coefficient value were very similar across the subjects (see Appendix

II).

A reasonable explanation of this is that cultural influences affect the teaching and

learning process is a manner that is consistent across subjects. This further confirms the view that

knowledge is culturally rooted regardless of subject. Additionally, it follows that efforts to

reform the way certain subjects are taught might not be as effective as efforts to change how

students and teachers interact in the teaching-learning process in general. However, this same

effect seems to be largely true regardless of whether we consider cultural variables or contextual

variables. Consider the rankings of various countries’ PISA scores across subjects. Nations that

score well in one area also tend to score well in others.

In discussing the differences between subjects, we will limit ourselves to discussing one

variable that failed to be either significant for all three subjects or insignificant for all three

subjects, V17. Many of the other differences are matters of degree and not overly informative

given our model. For example, consider variable V14. The regression of math scores on this

33

variable was significant with a p-value of 0.04, but the regressions of science scores and readings

were only narrowly insignificant at the 5 percent level, with p-values of 0.055 and 0.052.

Table 10: Description of V14 and V17

Variable Label Questions Scale V14 Important child qualities: Feeling of responsibility Here is a list of qualities that children can be encouraged to learn at


Feeling of responsibility

1 = Mentioned

2 = Not

mentioned

V17 Important child qualities: Thrift saving money and

things



Thrift, saving money and things

1 = Mentioned

2 = Not

mentioned

However, variable V17, described in Table 10 above, had some interesting differences

between subjects. It was significant for the math and science regressions with a p-value of 0.035

and 0.041, but failed to be significant for the reading regression with a p-value of 0.136. One

potential explanation for this is that learning to save and handle money requires the development

of arithmetic skills, which would be important for success in mathematics and science, but less

so in reading. Again, further research would need to be conducted to confirm or deny that

hypothesis.

Conclusion

Based on our analyses, we can conclude that the strength of certain cultural values is

related to patterns of students’ academic achievement in society. Values that relate positively to

academic achievement include propensity to place trust in others and the encouragement of

independence in children. Conversely, the strength of religious beliefs related negatively to

academic achievement. Hard work is a notable values that did not result in any patterns. While

this project does not go as far as to discover the means by which these cultural values effect

education, the potential hypothesis that we established in the discussion have some implications

for future research and practice.

34

One implication is that future research should look into the connection between cultural

variables discussed here and the contextual variables already present in quantitative research.

Understanding the connection between them will add much to our results here. For instance, how

closely related are the ideas of trust and school climate? If the two are closely linked, reform

efforts targeting improving school climate might be misplaced, as poor school climate would

stem from larger cultural issues. Is student self-esteem and self-belief a result of the student’s

independence, or the other way around? There is a wide field of questions that have not been

asked because culture has not been included in the PISA or the TIMSS framework. However, as

the idea of quantifying cultural values has been accepted in the research community, examining

datasets like the one produced by the WVS can lead to further hypotheses and analysis.

Once some of these connections are established, quantitative cultural variables should be

included alongside contextual variables in large multinational educational assessments like the

PISA and the TIMSS. The addition of these variables to the framework that researchers use to

evaluate academic achievement will make the resulting data more useful to practitioners.

Consider the policy transfer issue discussed in this paper. Why might one policy work extremely

successfully in some countries but fail elsewhere? If it is due to wider cultural issues, the

frameworks that we currently use will not be able to answer that question.

While traditionally culture and context have been considered using different research

methodologies, researchers can leverage quantitative data from studies like the WVS to bring

together the two traditions in ways that have not been done before. We envision this leading to a

number of insights that would not occur if the two traditions remain separate. Understanding

how culture interacts with education is important for those seeking to improve educational

outcomes, and adopting the perspective presented here can help illuminate this interaction.

35

Appendices

Appendix I: List of variable names and descriptions

Variable Label Question Scale V4 Important in life: Family For each of the following, indicate how important it is in your life. Would you say it is:

Family

1 = Very important


V5 Important in life: Friends For each of the following, indicate how important it is in your life. Would you say it is:

Friends

1 = Very important


V6 Important in life: Leisure

time

For each of the following, indicate how important it is in your life. Would you say it is:

Leisure time

1 = Very important


V7 Important in life: Politics For each of the following, indicate how important it is in your life. Would you say it is:

Politics

1 = Very important


V8 Important in life: Work For each of the following, indicate how important it is in your life. Would you say it is:

Work

1 = Very important


V9 Important in life:

Religion

For each of the following, indicate how important it is in your life. Would you say it is:

Religion

1 = Very important


V10 Feeling of happiness Taking all things together, would you say you are: 1 = Very happy

4 = Not at all happy

V11 State of health

(subjective)

All in all, how would you describe your state of health these days?. Would you say it

is:

1 = Very good

4 = Poor

V12 Important child qualities:

independence

Here is a list of qualities that children can be encouraged to learn at home. Which, if

any, do you consider to be especially important?:

Independence

1 = Mentioned

2 = Not mentioned


Hard work



Hard work

1 = Mentioned

2 = Not mentioned






1 = Mentioned

2 = Not mentioned


Imagination



Imagination

1 = Mentioned

2 = Not mentioned


Tolerance and respect for

other people



Tolerance and respect for other people

1 = Mentioned

2 = Not mentioned


Thrift saving money and

things



Thrift, saving money and things

1 = Mentioned

2 = Not mentioned


Determination,

perseverance



Determination and perseverance

1 = Mentioned

2 = Not mentioned


Religious faith



Religious faith

1 = Mentioned

2 = Not mentioned


Unselfishness



Unselfishness (* In Spanish "generosity")

1 = Mentioned

2 = Not mentioned


Obedience



Obedience

1 = Mentioned

2 = Not mentioned


Self-expression



Self-expression

1 = Mentioned

2 = Not mentioned

V23 Satisfaction with your life All things considered, how satisfied are you with your life as a whole these days?

Using this card on which 1 means you are “completely dissatisfied” and 10 means you

are “completely satisfied” where would you put your satisfaction with your life as a

whole?:

1 = Completely dissatisfied

10 = Completely satisfied

V24 Most people can be

trusted

Generally speaking, would you say that most people can be trusted or that you need to

be very careful in dealing with people?

1 = Most people can be trusted

2 = Need to be very careful

V49 One of my main goals in

life has been to make my

parents proud

For each of the following statements I read out, can you tell me how strongly you

agree or disagree with each. Do you strongly agree, agree, disagree, or strongly

disagree?:

"One of my main goals in life has been to make my parents proud"

1 = Agree strongly

4 = Strongly disagree

V52 A university education is

more important for a boy

than for a girl

For each of the following statements I read out, can you tell me how strongly you

agree or disagree with each. Do you strongly agree, agree, disagree, or strongly

disagree?:

"A university education is more important for a boy than for a girl"

1 = Agree strongly

4 = Strongly disagree

V55 How much freedom of

choice and control over

own life

Some people feel they have completely free choice and control over their lives, while

other people feel that what they do has no real effect on what happens to them. Please

use this scale where 1 means "no choice at all" and 10 means "a great deal of choice"

to indicate how much freedom of choice and control you feel you have over the way

your life turns out:

1 = No choice at all

10 = Great deal of choice

36

V56 Do you think most people

would try to take

advantage of you if they

got a chance, or would

they try to be fair?

Do you think most people would try to take advantage of you if they got a chance, or

would they try to be fair? Please show your response on this card, where 1 means that

“people would try to take advantage of you,” and 10 means that “people would try to

be fair”:

1 = People would try to take

advantage of you

10 = People would try to be

fair

V57 Marital status Are you currently: 1 = Married

2 = Living together as married

3 = Divorced

4 = Separated

5 = Widowed

6 = Single

V58 How many children do

you have

Have you had any children? 0 = No children

8 = 8 or more children

V59 Satisfaction with financial

situation of household

How satisfied are you with the financial situation of your household? 1 = Completely dissatisfied

10 = Completely satisfied

V70 Schwartz: It is important

to this person to think up

new ideas and be

creative; to do things

one’s own way

Now I will briefly describe some people. Using this card, would you please indicate

for each description whether that person is very much like you, like you, somewhat

like you, not like you, or not at all like you?

"It is important to this person to think up new ideas and be creative; to do things one’s

own way."

1 = Very much like me

5 = Not at all like me


to this person to be rich;

to have a lot of money

and expensive things




"It is important to this person to be rich; to have a lot of money and expensive things"



V72 Schwartz: Living in

secure surroundings is

important to this person;

to avoid anything that

might be dangerous




"Living in secure surroundings is important to this person; to avoid anything that

might be dangerous"




to this person to have a

good time; to “spoil”

oneself




"It is important to this person to have a good time; to “spoil” oneself"




to this person to do

something for the good of

society




"It is important to this person to do something for the good of society"



V74B Schwartz: It is important

to help people living

nearby; to care for their

needs




"It is important to help people living nearby; to care for their needs"



V75 Schwartz: Being very

successful is important to

this person; to have

people recognize one’s

achievements




"Being very successful is important to this person; to have people recognize one’s

achievements"



V76 Schwartz: Adventure and

taking risks are important

to this person; to have an

exciting life



like you, not like you, or not at all like you? :

"Adventure and taking risks are important to this person; to have an exciting life"




to this person to always

behave properly; to avoid

doing anything people

would say is wrong



like you, not like you, or not at all like you?:

"It is important to this person to always behave properly; to avoid doing anything

people would say is wrong"



V78 Schwartz: Looking after

the environment is


to care for nature and

save life resources



like you, not like you, or not at all like you? :

"Looking after the environment is important to this person; to care for nature and save

life resources"



V79 Schwartz: Tradition is


to follow the customs

handed down by one’s

religion or family



like you, not like you, or not at all like you?:

"Tradition is important to this person; to follow the customs handed down by one’s

religion or family"



V95 Self positioning in

political scale

In political matters, people talk of "the left" and "the right." How would you place

your views on this scale, generally speaking?

1 = Left

10 = Right

V96 Income equality Now I'd like you to tell me your views on various issues. How would you place your

views on this scale? 1 means you agree completely with the statement on the left; 10

means you agree completely with the statement on the right; and if your views fall


"Incomes should be made more equal" vs. "We need larger income differences as

incentives for individual effort"

1 = Incomes should be made

more equal

10 = We need larger income

differences as incentive for

individual effort

V100 Hard work brings success Now I'd like you to tell me your views on various issues. How would you place your

views on this scale? 1 means you agree completely with the statement on the left; 10

means you agree completely with the statement on the right; and if your views fall


"In the long run, hard work usually brings a better life" vs. "Hard work doesn’t

generally bring success—it’s more a matter of luck and connections"

1 = In the long run, hard work

usually brings a better life

10 = Hard work doesn’t

generally bring success – it’s

more a matter of luck and

connections

37


Your family

I ‘d like to ask you how much you trust people from various groups. Could you tell me

for each whether you trust people from this group completely, somewhat, not very

much or not at all?

Your family




Your neighborhood



much or not at all?

Your neighborhood




People you know

personally



much or not at all?

People you know personally




People you meet for the

first time



much or not at all?

People you meet for the first time




People of another religion



much or not at all? :

People of another religion




People of another

nationality



much or not at all?

People of another nationality



V119 Confidence: Universities I am going to name a number of organizations. For each one, could you tell me how

much confidence you have in them: is it a great deal of confidence, quite a lot of

confidence, not very much confidence or none at all?:

Universities

1 = A great deal

4 = None at all

V140 Importance of democracy How important is it for you to live in a country that is governed democratically? On

this scale where 1 means it is “not at all important” and 10 means “absolutely

important” what position would you choose?

1 = Not important at all

10 = Absolutely important

V143 Thinking about meaning

and purpose of life

Now let’s turn to another topic. How often, if at all, do you think about the meaning

and purpose of life?

1 = Often

4 = Never

V145 How often do you attend

religious services

Apart from weddings and funerals, about how often do you attend religious services

these days?

1 = More than once a week

6 = Less than once a year

V146 How often to you pray Apart from weddings and funerals, about how often do you pray? 1 = Several times a day

8 = Never, practically never

V147 Religious person Independently of whether you attend religious services or not, would you say you are: 1 = A religious person

3 = An atheist

V148 Believe in: God Do you believe in God? 1 = Yes

2 = No

V149 Believe in: hell Do you believe in hell? 1 = Yes

2 = No

V152 How important is God in

your life

How important is God in your life?. Please use this scale to indicate. 10 means “very

important” and 1 means “not at all important.”:


10 = Very important

V157 Social position: People in

their 20s

I’m interested in how you think most people in this country view the position in

society of people in their 20s, people in their 40s and people over 70.* Using this card,

please tell me where most people would place the social position of …

…people in their 20’s?

1 = Extremely low position in

society

10 = Extremely high position

in society


their 40s




…people in their 40’s?


society


in society


their 70s




…people over 70?


society


in society

V248 Highest educational level

attained

What is the highest educational level that you have attained? 1 = No formal education

9 = University-level

education, with degree

V249 What age did you

complete your education

At what age did you (or will you) complete your full time education, either at school or

at an institution of higher education?. Please exclude apprenticeships.

n/a (Numerical response)

Y001 Materialist/postmaterialist

12-item index

0 = Materialist

5 = Post-materialist

Y002 Post-materialist index (4-

item)

Post-materialist index (4-item) 1 = Materialist

3 = Post-materialist

Y003 Autonomy Index Autonomy Index is a computed variable based on the Children qualities battery. -2 = Religion/obedience

2 =

Independence/determination

Adapted from the complete WVS Wave 6 Codebook, which can be found at

http://www.worldvaluessurvey.org/WVSDocumentationWV6.jsp.

38

Appendix II: Complete simple OLS regression results


Variable p-value 𝑅2 �̂� p-value 𝑅2 �̂� p-value 𝑅2 �̂�

V4 0.141 0.071 315.7 0.132 0.074 279.3 0.093 0.09 329.2

V5 0.028 0.150 -114.3 0.023 0.161 -102.3 0.019 0.17 -111.5

V6 0.271 0.002 -90.6 0.142 0.071 -103.8 0.211 0.05 -94.4

V7 0.410 0.040 -30.6 0.329 0.032 -31.2 0.457 0.02 -25.4

V8 0.000 0.439 181.1 0.000 0.475 162.7 0.000 0.52 181.5

V9 0.000 0.402 59.1 0.000 0.393 50.5 0.000 0.47 58.4

V10 0.267 0.041 64.6 0.296 0.036 52.6 0.226 0.05 64.5

V11 0.197 0.057 66.8 0.206 0.053 55.4 0.136 0.07 69.2

V12 0.000 0.444 -276.1 0.001 0.337 -207.9 0.000 0.42 -248.1

V13 0.591 0.010 -27.6 0.772 0.003 -12.9 0.621 0.01 -23.3

V14 0.040 0.133 -226.0 0.055 0.118 -183.7 0.052 0.12 -197.1

V15 0.870 0.001 -16.7 0.590 0.010 -47.4 0.555 0.01 -55.1

V16 0.813 0.002 -22.6 0.581 0.010 -45.5 0.531 0.01 -54.9

V17 0.035 0.140 -152.4 0.136 0.073 -94.9 0.041 0.13 -136.1

V18 0.025 0.157 -169.1 0.031 0.146 -141.1 0.006 0.22 -185.5

V19 0.000 0.498 184.7 0.000 0.465 154.2 0.000 0.49 168.5

V20 0.008 0.212 232.2 0.024 0.158 173.3 0.031 0.15 177.3

V21 0.000 0.439 238.7 0.000 0.387 193.5 0.000 0.36 199.7

V22 0.363 0.028 -64.4 0.352 0.029 -56.9 0.255 0.04 -73.8

V23 0.105 0.085 -29.9 0.176 0.060 -21.7 0.130 0.07 -25.7

V24 0.000 0.414 -227.5 0.000 0.413 -196.3 0.000 0.45 -218.7

V49 0.014 0.191 70.3 0.028 0.155 54.7 0.016 0.18 63.8

V52 0.225 0.049 37.3 0.115 0.081 41.4 0.152 0.07 40.3

V55 0.007 0.220 -47.3 0.011 0.198 -38.8 0.005 0.24 -45.0

V56 0.076 0.105 31.5 0.140 0.074 22.6 0.128 0.08 24.8

V57 0.100 0.088 -62.4 0.093 0.092 -55.1 0.058 0.11 -65.7

V58 0.001 0.312 -76.7 0.002 0.291 -64.3 0.002 0.29 -68.6

V59 0.904 0.001 -2.2 0.926 0.000 -1.5 0.801 0.00 -4.3

V70 0.000 0.411 109.3 0.001 0.306 81.4 0.000 0.38 96.3

V71 0.319 0.033 19.2 0.195 0.055 21.5 0.273 0.04 19.4

V72 0.002 0.281 68.0 0.003 0.266 57.2 0.001 0.32 66.4

V73 0.003 0.256 54.7 0.005 0.236 45.3 0.003 0.27 51.1

V74 0.000 0.436 85.1 0.000 0.401 70.4 0.000 0.44 78.7

V75 0.003 0.261 48.7 0.004 0.243 40.6 0.003 0.27 45.1

V76 0.373 0.027 25.2 0.513 0.014 16.0 0.395 0.02 22.1

V77 0.001 0.337 86.8 0.000 0.365 78.0 0.000 0.38 84.5

V78 0.001 0.304 81.0 0.002 0.270 66.1 0.001 0.30 73.5

39

V79 0.000 0.486 69.5 0.000 0.490 60.3 0.000 0.51 65.5

V95 0.062 0.123 -42.6 0.070 0.116 -36.6 0.076 0.11 -38.3

V96 0.583 0.010 -6.3 0.387 0.025 -8.5 0.319 0.03 -10.4

V100 0.413 0.022 15.1 0.400 0.024 13.4 0.306 0.03 17.3

V102 0.470 0.018 87.3 0.354 0.030 95.7 0.473 0.02 79.4

V103 0.406 0.024 -40.9 0.442 0.021 -32.5 0.332 0.03 -43.6

V104 0.005 0.241 -120.3 0.005 0.242 -103.3 0.003 0.27 -117.6

V105 0.002 0.284 -128.3 0.001 0.316 -116.0 0.001 0.33 -125.9

V106 0.021 0.171 -83.5 0.024 0.164 -70.1 0.017 0.18 -78.7

V107 0.014 0.189 -76.9 0.015 0.187 -65.5 0.008 0.22 -75.7

V119 0.604 0.009 -29.6 0.578 0.010 -27.4 0.619 0.01 -26.1

V140 0.772 0.003 -8.1 0.859 0.001 -4.3 0.769 0.00 -7.6

V143 0.021 0.165 121.8 0.039 0.134 94.7 0.013 0.19 119.9

V145 0.008 0.217 31.1 0.011 0.204 26.0 0.005 0.24 30.1

V146 0.000 0.353 24.7 0.001 0.321 20.3 0.000 0.39 23.8

V147 0.000 0.460 146.6 0.000 0.427 122.1 0.000 0.47 136.0

V148 0.002 0.291 162.8 0.001 0.312 146.0 0.001 0.36 165.0

V149 0.040 0.142 94.0 0.028 0.162 87.0 0.013 0.20 102.1

V152 0.000 0.488 -21.5 0.000 0.472 -18.3 0.000 0.55 -21.0

V157 0.002 0.273 -45.4 0.003 0.257 -38.1 0.002 0.28 -42.0

V158 0.235 0.047 29.8 0.240 0.046 25.5 0.203 0.05 29.3

V159 0.271 0.040 -13.4 0.256 0.043 -11.9 0.209 0.05 -14.0

V248 0.008 0.212 32.0 0.009 0.206 27.3 0.011 0.20 28.3

V249 0.618 0.008 -1.0 0.734 0.004 -0.6 0.646 0.01 -0.9

Y001 0.165 0.063 41.0 0.079 0.099 44.3 0.092 0.09 45.3

Y002 0.470 0.018 39.6 0.181 0.059 62.7 0.260 0.04 56.4

Y003 0.000 0.691 97.8 0.000 0.608 79.2 0.000 0.68 89.4

40

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