Interplay of factors contributing to ESL at the levels of the individual, the family and social background

Wednesday 11 February 2015, by Maša Vidmar

Individual cognitive factors, especially low-achievement patterns, increase the risk for ESL, but non-cognitive factors (e.g. personality traits, problem behaviour) also play a role. At the level of the family and social background, the most prominent risk factor is low socio-economic status. However, it is noted that ESLers comprise a heterogeneous group.

Keywords : early school leaving 

ESL is a process rather than a one-off event (European Commission, 2011) and the route to ESL frequently begins before the child goes to school (NESSE, 2010). ESL risk and protective factors have to be understood within a multiple-level framework: the individual, the microsystem (e.g. family, peers, school), the mesosystem (relations between the microsystems), the exosystem (e.g. health, social, education system, media, neighbours), the macrosystem (e.g. the culture in which individuals live) and the chronosystem (e.g. sociohistorical circumstances) (see Bronfenbrenner, 1996. ESLers are generally more likely to be exposed to multiple disadvantages at different levels, which usually interact (European Commission, 2011). This article aims to review the literature on several different individual factors and factors related to the family and social background that may contribute or prevent ESL.

The present scientific review on one hand confirms that already demonstrated in many studies and literature reviews: at the level of individual, cognitive factors it is especially low-achievement patterns which are the most potent for increasing the risk for ESL. Being male and having a migrant/minority status are also risk factors; however, the relationships are less straightforward. On the other hand, the article draws attention to a series of non-cognitive factors and highlights the complex interplay between the cognitive and non-cognitive factors. Conscientiousness plays the role of a protective ESL factor (more strongly for low achievers), while problem behaviour seems to be a risk factor. ESLers typically exert a lower level of achievement motivation and have a history of disengagement from school (e.g. truancy). On a similar note, engagement was shown to reduce the risk of ESL. Among the family and social background factors, low SES is the most consistent and strongest predictor of ESL. In addition, the family’s social capital (e.g. parental education support, their involvement, parenting practices, but also family structure) impact the risk of ESL.

The review of factors that contribute to ESL helps understand how highly versatile and individualised interventions, measures and initiatives tackling ESL must be to address the different needs of (potential) ESLers.


Along with the European Union’s (European Commission, 2002; Council of the EU, 2009) recognition of ESL as an important political issue with long-lasting consequences for the individual and society, scientific and research attention to the matter has grown, noting that the topic also received some attention earlier, particularly in the USA (see e.g. Barclay & Doll, 2001 who examined ESL studies conducted between 1950 and 1970). Today, an abundance of publications aims to understand (and prevent) ESL, including numerous scientific studies examining possible ESL risk or protective factors and reviewing the evidence available in existing studies.

Some authors have proposed theoretical models of ESL (e.g. Battin-Pearson et al., 2000; Fall & Roberts, 2012; Finn, 1989; Clycq, Nouwen, & Timmerman, 2014; for a review of such models, see Rumberger, 2011). However, ESL can also be viewed within more general theories of human development. For example, Bronfenbrenner’s theory (1996) distinguishes several levels of ecological systems that all interact with each other and with the characteristics of the individual: the microsystem (e.g. family, peers, school – most immediate and direct impact), the mesosystem (relationships between the microsystems – e.g. relationships between the family and teachers), the exosystem (e.g. health, social, education system, media, neighbours – indirect impact), the macrosystem (e.g. the culture in which individuals live: attitudes, ideologies) and the chronosystem (e.g. sociohistorical circumstances) (see Figure 1). ESL risk and protective factors can be understood within this multiple-level framework.

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Figure 1. Bronfenbrenner’s model of human development (adapted from Pinterest). The black rectangles constitute the focus of the article.

This means that ESL is both a process and a complex phenomenon (e.g. Clandinin et al., 2010; Lyche, 2010). Causes (trajectories resulting in ESL) vary from student to student (NESEE, 2010) and may begin very early in one’s life (e.g. Jimerson, Egeland, Sroufe, & Carlson, 2000; McGarr, 2010). However, where several risk factors from multiple levels co-exist, the incidence of ESL is greater (Beekhoven & Dekkers, 2005; European Commission, 2011; McGarr, 2010). Understanding the interplay of factors (i.e. that ESL does not result from interpersonal factors alone) and levels is essential. Several studies have attempted to model this complexity and map the underlying processes that influence ESL (e.g. Traag & van der Velden, 2008).

In the present article, we focus on the ESL factors lying within the individual and the microsystem (focusing on the family level) and review relevant scientific evidence. [1] Many authors have developed own classifications of ESL microsystem factors that more or less overlap (e.g. students and institutional characteristics, Rumberger & Lim, 2008; individual, family and school characteristics, Traag & van der Velden, 2008; school-based and individual, family and social background-related; Thibert, 2013; individual, family, peer, community effects, Audas & Willms, 2001). These categories can be further sub-divided, e.g. individual characteristics are: educational performance, behaviours, attitudes and background (Rumberger & Lim, 2008); cognitive and non-cognitive (Traag & van der Velden, 2008). In this article, we classify factors as: (1) those related to an individual (further divided into structural, cognitive and non-cognitive); and (2) those related to the family and social background.

As mentioned, a wealth of publications can already be found covering ESL individual and family factors: Yet this article tries to bring together what has already been done by way of a structured and coherent presentation. Some factors highlighted in the article are discussed and reviewed in greater depth in separate articles (e.g. low motivation, poor academic achievement, behavioural problems and home environment).


The scientific review article is based on computerised literature searches in the Arizona State University Library search engine coupled with other online resources (e.g. Google Scholar). We used the following key words “early school leaving”, “drop out” AND “individual factors/precursors/determinants”, “motivation”, “academic achievement”, “engagement”, “personality”, “non-cognitive factors”, “family factors”, “family characteristics”, “parental involvement”, “parental aspirations”, “parental support”, “metaanalysis”. In the next step, we examined references cited in the articles (i.e., “backward search” procedures). Original scientific articles and monographs as well as reports by or for the European Commission and the OECD are considered.

Factors related to the individual

This group of ESL factors has been very extensively studied. A considerable body of research also deals with factors not specifically related to ESL, but to academic achievement (mostly not covered in this article due to its focus on ESL, albeit the precursors of low academic achievement often overlap with those of ESL; simultaneously, low achievement is itself a strong risk factor for ESL). Individual-level factors can be classified in three groups: structural (i.e. demographic, e.g. gender, minority/migrant background), cognitive (e.g. academic achievement, intelligence) and non-cognitive (e.g. personality traits, social competence, emotional competence/intelligence, problem behaviour, motivation, engagement, self-concept, anxiety).

Structural factors: gender

With regard to gender, a consistent pattern is found – young males are at greater risk for ESL than their female counterparts. According to Eurostat, the ESL rate in 2016 was 3.0 percentage points higher for young men (12.2%) than for young women (9.2%) in the EU-28 (Eurostat, n.d. a). Thus, the proportion of early leavers among young men is about 30% higher than among young women, a ratio that has been stable over the last decade (ibid.). In almost all EU countries, the rates were higher for males than females, in some countries even by up to 5%. Similar findings were reported in international and national research (e.g. Audas & Willms, 2001; Brock, 2011; Houses of the Oireachtas, 2010; Marks & McMillian, 2001; NESSE, 2010; Traag & van der Velden, 2008). Several tentative explanations are provided for this: boys have lower achievement in reading than girls; boys have more difficulties adapting to the school environment than girls; gender is more likely to play a role for boys from a poor neighbourhood, while the gender difference for students from a better situated neighbourhood seems to be non-significant (see European Commission/EACEA/Eurydice/Cedefop, 2014 for details). Thus, the relationship between ESL and gender seems to be less straightforward than the relationship with social economic status (SES), indicating that gender alone is not a determining factor.

Structural factors: migrant and minority background

 [2]Eurostat data show that students born abroad are largely over-represented among those who leave formal education prematurely in many EU countries – the share of early leavers among migrants in 2015 was almost twice the level for natives (19.0% compared with 10.1%) (Eurostat, n.d. b), and can be up to five times more in some countries (European Commission/EACEA/Eurydice/Cedefop, 2014). There are several possible reasons for this, including low SES and language difficulties that may lead to low achievement and low motivation. Indeed, the European Commission (2014) as well as the OECD (2013) consistently report lower levels of academic performance for migrant compared to native students, although the difference shrinks (but remains significant) when controlling for SES.

On the contrary, in a study by Traag and van der Velden (2008) students from a migrant background were less at risk for ESL when controlling for social background (family resources) than their native counterparts. According to the authors, this means that the larger numbers of migrant students found among ESLers is not due to cultural differences and language proficiency, but due to the lack of family resources (they more often have low SES). Interestingly, in Australia having an Australian-born parent (i.e. a native background) increased the risk for ESL compared to students whose parents were born in non-English-speaking countries (Marks & McMillian, 2001).
Among the students with a minority background, it is Roma students who have been most widely studied. The ESL rates among young Roma are extremely high – in the examined 11 EU member states only 15% of young Roma adults surveyed complete upper-secondary general or vocational education (FRA/UNDP, 2012). A combination of factors (e.g. parental choice, poverty, language barriers, ethnic discrimination in institutions) is likely to underlie this (European Commission/EACEA/Eurydice/Cedefop, 2014; Eurostat, n.d. b).

Despite the data shown above, it is important to note that students with a migrant/minority background constitute a heterogeneous group (e.g. different ethnic backgrounds, second-generation migrants versus new arrivals), thus it seems that other factors play a more critical role in educational outcomes than migrant background per se (European Commission/EACEA/Eurydice/Cedefop, 2014).

Cognitive factors

Low abilities (e.g. intelligence), low academic achievement, low knowledge gained in primary education are identified as the most potent risk factors for ESL (see the reviews in Barclay & Doll, 2001; Battin-Pearson et al., 2000; Jugović & Doolan, 2013; Lyche, 2010; NESEE, 2010; McCarthy Voss, 2015; for an exception, see Brock, 2011). ESLers also tend to be less intelligent and have lower scholastic achievement (see the review in Traag & van der Velden, 2008). Traag (2012) found significant differences between ESLers and their counterparts finishing secondary education on cognitive factors, like text comprehension, arithmetic and information processing. Moreover, a logistic regression showed that the higher a student scored on the cognitive test, the lower was the risk of becoming an ESLer. The impact of cognitive factors remained significant, but was reduced after including the control variables (e.g. SES, migrant background). On a similar note, Marks and McMillian (2001) found cognitive factors like literacy and numeracy in middle school had a strong influence on subsequent ESL. Janosz, LeBlanc, Boulerice and Tremblay (1997) found school achievement to be the best screening variable for potential ESLers. In a review by Rumberger and Lim (2008), a majority of 200 studies found that academic achievement had a statistically significant effect on the likelihood of ESL. Further, not doing well at school was an important reason for over 40% of Australian ESLers (Marks & McMillian, 2001). Similar findings were reported for ESLers in Europe: when interviewed, students listed having poor results or not feeling smart enough as one of the reasons for ESL (GHK Consulting, 2011).

Non-cognitive factors

Even though SES and academic achievement have been shown to be the strongest and most consistent precursors of ESL, one should not neglect the role of non-cognitive factors (e.g. personality traits, motivational, affective, social and behavioural characteristics, attitudes). For example, Traag (2012) cited studies highlighting the importance of non-cognitive skills for labour market outcomes (e.g. wage) as well as for the individual’s trajectories after ESL (also see Entwisle, Alexander, & Olson, 2004).

Personality traits are defined within the Five Factor Model (FFM; McCrae & Costa, 1997) as extraversion, agreeableness, emotional stability/neuroticism, conscientiousness, and openness to experience. [3] Personality traits are usually not examined relative to ESL, but to academic achievement (for exceptions, see Rosenthal, 1998; Traag, 2012). Conscientiousness was found to be protective factor against ESL, while openness to experience, on the contrary to the author’s expectations, increased the risk of ESL (other personality traits were not significant predictors after controls were added to the models; Traag, 2012). In relation to academic achievement, conscientiousness (in some studies in combination with openness) was the most consistent predictor (e.g. Poropat, 2009; Lamb, Chuang, Wessels, Broberg, & Hwang, 2002; Zupančič & Kavčič, 2007) while research results about openness to experience, emotional stability, and agreeableness are inconclusive (for a review, see Traag, 2012; Vidmar, 2010). Extraversion was a positive predictor for both young children and young adolescents (e.g. Anthony, 1983; Eysenck & Cookson, 1969; Mervielde, Buyst & De Fruyt, 1995), but a negative one in older age groups (e.g. Eysenck, 1994; Mervielde et al., 1995; Puklek Levpušček & Zupančič, 2009; Smrtnik Vitulić, 2008; Wolf & Ackerman, 2004).

Student engagement is one of the most important precursors to ESL in conceptual models of ESL (Finn, 1989; Rogers, 2016; Rumberger & Lim, 2008). Disengagement from education lies along a continuum that at the most extreme end refers to ESL (Rogers, 2016; Rumberger, 2011). It comprises multiple dimensions: an emotional (e.g. affective reactions) and behavioural dimension (e.g. absenteeism, participation in learning and academic tasks) and in some models also a cognitive one (e.g. willingness to exert effort; for details, see Archambault, Janosz, Fallu, & Pagani, 2009; Rogers, 2016). Indeed, in high school stronger levels of engagement reduced the ESL risk in the majority of studies (77%, non-significant in the remaining studies), while the impact of engagement was less obvious in middle school (Rumberger & Lim, 2008). Audas and Willms’ (2001) and Lyche’s (2010) literature review (2001), McCarthy Voss’ study (2015) and the study by Henry, Knight and Thornberry (2012) confirm the importance of engagement for ESL as ESLers had a history of disengagement from school (e.g. absence, truancy, expulsion; NESSE, 2010). In a study by Janosz, Archambault, Morizot and Pagani (2008), ESLers demonstrated unstable pathways of school engagement (transitory increasing, transitory decreasing, decreasing, and increasing trajectories). Archambault et al. (2009) found that global engagement and its behavioural dimension were significant predictors of ESL (also see Janosz et al., 1997). In Wang and Fredricks’ study (2014), lower behavioural and emotional engagement was predictive of a higher ESL rate. The perceived fit between students and the school’s social environment plays a central role in school engagement (Järvinen, Soini, Pyhältö, & Pietarinen, 2012).

Closely linked to student engagement, another important non-cognitive factor is motivation (European Commission, 2014). To some extent, motivational differences are partly reflected by differences in conscientiousness, but these differences are more general across contexts and situations; thus, in this section we focus specifically on motivation in a learning and achievement-related setting. Motivation to perform well in school was significantly lower for ESLers compared to regular school leavers, but the differences were quite small compared to the differences in cognitive skills; regardless of this, a high score on achievement motivation decreased the risk of becoming an ESLer (Traag, 2012). The size of the impact remained unchanged even when including background variables (SES, migrant status). Bridgeland, DiIulio and Morison (2006) surveyed actual ESLers and 69% of the respondents identified a lack of motivation as a reason for dropping out and a similar share was confident they would have graduated if they had tried. Lack of motivation in ESLers was also found by Beekhoven and Dekkers (2005).

Negative attitudes to school (e.g. not liking school, disconnectedness from school) are a non-cognitive factor that occurs at higher rates in ESLers. For example, not liking school was cited as a reason for ESL by 50% of ESLers in Australia; although wanting to get a job/ apprenticeship was more frequent and more important (Marks & McMillian, 2001). Similarly, ESLers in Europe experience school rules and regulations in a negative way and list this as a reason for ESL (GHK Consulting, 2011). The literature review by Audas and Willms (2001) supports this – ESLers feel disconnected from school, believe their teachers do not care about them, and think the ‘cards are stacked against them’.

Social competence and problem behaviour are also considered non-cognitive factors of ESL (European Commission, 2014). Behavioural problems lead to poor school performance or may be a consequence of frustrations due to keeping up with school work or maintaining an interest in school work or an unsupportive environment more generally (ibid.). Based on a review of studies, Rumberger and Lim (2008) concluded that any of the deviant behaviours (e.g. misbehaving in school, delinquent behaviour outside of school, drug and alcohol use, and sexual activity and teen childbearing) increased the risk for ESL. Literature reviews by Audas and Willms (2001), Barclay and Doll (2001), Lyche (2010) and Hymel and Ford (2014) support this. Ensminger and Slusarcick (1992) found that aggressive behaviour as early as first-grade increased the risk of ESL for boys, Brock (2011) found a similar effect for hyperactive and inattentive behaviours of 12-year-olds (also see Janosz et al., 1997; Jimerson et al., 2000; Vitaro, Brendgen, & Tremblay, 1999). Carter (1998) demonstrated that ESLers have lower social competence than those who persist in school.

Another set of non-cognitive factors was examined by Bradshaw, O’Brennan, & McNeely (2008). In their literature review study, they highlighted the following protective factors against ESL: a positive sense of self, self-control (e.g. impulse control, and delay of gratification locus of control), decision-making skills (e.g. responsible decisions about studying and completing assignments, social and emotional problem solving, relationship skills), empathy and perspective taking, and connectedness to parents, teachers.

The findings of a comprehensive study by Wang, Haertel, & Walberg (1993) which dealt more widely with factors supporting students’ school learning (not specifically ESL factors) are in line with the examined studies. They identified the importance of psychological factors, including motivational, affective, social and behavioural (in addition to cognitive and metacognitive) student characteristics.

Interplay of cognitive and non-cognitive factors

Based on the scientific evidence presented above, it seems that cognitive factors have a strong and direct effect on the risk of ESL, and that this effect remains after adding non-cognitive factors. However, non-cognitive skills also explain part of the individual differences in ESL risk (Traag, 2012). Traag (2012) found that non-cognitive factors play an important role in understanding why some students leave school even though their cognitive skills are at an adequate level (e.g. high openness to experience was a risk factor for those with high cognitive skills, and a protective factor for those with low cognitive skills). She also found that conscientiousness was a strong protective factor for those with low cognitive skills, but was not significant for students with above-average cognitive skills. The results indicate that non-cognitive skills play a role after controlling for cognitive factors, yet the effects are not merely additive – there is a complex interplay between the two factors. Another way of explaining the interplay is that cognitive and some non-cognitive characteristics develop along mutually related lines; e.g. successful performance in certain tasks increases interest and thus increases motivation (ibid.).

Factors related to the family and social background

Traag and van der Velden (2008) categorised family factors into four groups that also cover social background: economic capital (i.e. financial resources), human capital (parental education levels), social capital and cultural capital. The first two can be combined into what is operationalised in many studies as social and economic status (SES) – SES is also used in this article. Social capital refers to the relationship between parents and children (e.g. parental involvement, parental educational aspirations, parental educational support, domestic violence, parenting style), including family composition (single-parent or two-parent) and number of children. The cultural capital refers to cultural participation (e.g. visits to museums, concerts and the theatre).


Among ESL factors, low SES (i.e. low household income, unemployed parents, low level of parental education) seems to be the most consistent risk factor. As indicated in the European Commission/EACEA/Eurydice/Cedefop (2014) and NESSE (2010) reports, many studies have found low SES to entail key factors that increase the risk of ESL (also see Audas & Willms, 2001; Brock, 2011; Jugović & Doolan, 2013; Houses of the Oireachtas, 2010; Janosz et al., 1997; Jimerson et al., 2000; Marks & McMillan, 2001; Rosenthal, 1998; Traag, 2012). ESLers are much more likely to come from families with low SES. For example, the majority (over 70%) of ESLers have parents with a low level of education (compulsory or below) (GHK Consulting, 2011). The importance of parental education for student attainment is consistently shown in the PISA study (e.g. OECD, 2012, 2013, 2016). The role of SES in ESL was also highlighted in a review for the European Commission (2014). Boudon’s theory of social stratification (Boudon, 1974) can explain these findings – for individuals from a lower social class the cost of staying at school is relatively large while at the same time less importance is attributed to education than among those from high social classes – this makes education less worthwhile for students from low SES groups and increases their chances of ESL.

Social capital

Parental education support (e.g. parents have discussions about school and school performance and give compliments about school performance) is an important predictor of ESL; having highly supportive parents cuts the risk of ESL by more than 50% compared to a very unsupportive parent (Traag & van der Velden, 2008). Brock (2011) also found parental support to be an important ESL predictor. Home educational support of students in schools of a similar socioeconomic composition was important for ESL; students with more educational resources at home were less likely to intend to leave school than students with fewer home resources in schools with a similar socioeconomic composition (Houses of the Oireachtas, 2010).

Parental attitudes in the first grade (i.e. conduct expected, mark expected, education expected) predicted ESL, while the prediction of parenting socialisation practices was not significant (Alexander, Entwisle, & Horsey, 1997). In relation to parental involvement, a metaanalysis (Jeynes, 2005) found a considerable and consistent relationship between parental involvement and academic achievement (regardless of the measure of achievement). The relationship held across race and gender. Very interesting findings included that some of the most powerful aspects of parental involvement were the more subtle ones – those that create the general atmosphere. Parental high expectations of school performance and parenting style and not particular actions (e.g. checking homework, attending school functions) were significant predictors (ibid.). The European Commission (2014) in its literature review also found a violent family atmosphere to be related to an increased risk of ESL. Similarly, Tiko’s study (2008) showed that the family’s inability to support the child and enable the conditions for learning (e.g. lack of interest in the child, alcoholism) is one of the key reasons for students’ underachievement and non-compliance with compulsory schooling. Based on their literature review, Bradshaw et al. (2008) concluded that the connection to one’s parents has a positive influence on multiple aspects of youth development, including ESL. Jimerson et al. (2000) demonstrated the importance of the early home environment in the toddler years (e.g. parental emotional and verbal responsivity, acceptance of the child’s behaviour, provision of appropriate play material) and parental involvement in primary school for subsequent ESL.

Moreover, other indicators of social capital were found to play a role in ESL. Children from single-parent families and children in families with four or more children were at a higher risk for ESL (Audas & Willms, 2001; Traag & van der Velden, 2008). In other studies, family composition was linked to a student’s academic achievements; children from single-parent families had lower school performance than their two-parent counterparts (Babarović, Burušić, & Šakić, 2009). Similarly, on average across the OECD, students from single-parent families have lower scores in PISA than students from other types of families after accounting for socio-economic background (OECD, 2010).

Cultural capital

Cultural participation (parent reports visiting museums, concerts and theatre) decreases the chances of ESL (Traag & van der Velden, 2008). Cultural capital is also integrated in PISA’s measure of SES. It is called economic, social and cultural status and derives from four variables (i.e. parent’s highest level of education, parent’s highest occupation status, home possessions and books in the home), one of them tapping cultural capital. A clear link to student academic achievement was demonstrated in all cycles of the PISA study (e.g. OECD, 2016). The role of the cultural participation is that it potentially leads to a close link between a student’s behaviour and views on the dominant school culture and decreasing the ESL risk (Traag & van der Velden, 2008). The issue of cultural capital as necessarily resembling the dominant culture seems problematic; it seems that a culturally-sensitive curriculum is also warranted.


The present scientific review on one hand confirms that already demonstrated in many studies: at the level of the individual, cognitive factors especially low achievement patterns, most consistently and strongly increase the risk for ESL (although academic performance does not account for all of the variance between students who persist in school and ESLers). Being male and having a migrant/minority status are also risk factors: however, the relationships are not straightforward. On the other hand, the article draws attention to a series of non-cognitive factors and highlights the complex interplay of the cognitive and non-cognitive factors. Conscientiousness plays the role of a protective ESL factor (more strongly for low achievers), while problem behaviour seems to be a risk factor. Achievement motivation is also important. Within family and social background factors, SES is the most consistent and strongest predictor. In addition, the family’s social capital (e.g. parental education support, their involvement, parenting practices, but also family structure) impacted the risk of ESL.

When planning interventions or policy changes targeting ESL, it is important to note what Wand et al. (1993) observed: in general, proximal variables (e.g., psychological, instructional) were more important for students’ learning than distal variables (e.g., policy and organisation). This implies that introducing new policies (at the state or school level) will not necessarily enhance student learning. Thus, whenever introducing policies aimed at the protective or risk factors of ESL, it should be ensured that distal variables become translated into changes for the student.

Finally, interventions to combat ESL need to be based on an understanding of its complex determinants and the factors that operate at multiple levels and vary from one student to another – ESLers are a very heterogeneous group (no single ’profile’ can be established). The impact of factors related to ESL may vary for different subgroups. Interventions therefore need to address issues pertaining to the individual, the microsystem (family, school, teachers and other educators) and the exosystem (education system) in a co-ordinated way. Attention to the mesosystem should not be overlooked; e.g. developing a home-school mesosystem that is supportive of the student and his/her school attendance. Moreover, the fact the developmental pathway to ESL may already begin in elementary school or even before then is important.


[1School-level factors (also a microsystem) and factors from the exosystem are examined in two separate articles.

[2As indicated in the European Commission/EACEA/Eurydice/Cedefop report (2014) different countries have different conceptualization of what it means to have a migrant to minority background, making comparison difficult; however, some conclusions can still be made.

[3Extraversion is conceptualized in terms of sociability, activity, positive mood, assertiveness; agreeableness in terms of prosocialness, kindness, courtesy, empathy, compliance, cooperation; neuroticism in terms of general negative emotionality, high sensitivity, high arousal, the presence of fears, tension, anxiety; conscientiousness in terms of controlling impulses, maintaining attention, accuracy, orderliness, determination, competitiveness; and openness in terms of curiosity, creativity, interest in new things, cleverness, ingenuity, and speed of learning (Ehrler, Evans, & McGhee, 1999; Zupančič & Kavčič, 2007).

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