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Migration flows have contributed to the growing diversity of the European population and have considerably changed its dynamics in recent years. Different countries have different concepts of what it means to have a 'foreign background'; likewise all countries have their own ways of collecting information, which makes it difficult to gather comparable data (European Commission/ EACEA/Eurydice, 2014). The data in Figure 2.2 relate to the country of birth of students leaving education and training early: those born abroad (defined as foreign-born) and those born in the country of residence (defined as native-born). However, much of the literature discussed here refers to

Chapter 2: Fac tors Contributing to Students Leav ing the Educ ation and Training Sy stem Early

Figure 2.2: Percentage of early leavers from education and training by origin (foreign-born and native), 2013

% % Foreign-born Native-born % EU-28 BE BG CZ DK DE EE IE EL ES FR HR IT CY LV LT LU Foreign-born 22.6 21.7 : 9.1 8.8 : : 10.4 35.7 38.3 17.8 11.5 34.4 16.4 : : 8.1 Native-born 11.0 9.5 12.6 5.4 8.0 8.6 9.7 8.0 7.5 20.6 9.1 4.0 14.8 7.2 9.8 6.3 5.3 HU MT NL AT PL PT RO SI SK FI SE UK CH IS LI NO TR Foreign-born : 25.6 11.2 18.5 : 20.1 : 16.4 : 17.4 12.2 9.9 14.0 26.5 : 18.4 : Native-born 11.8 20.7 9.0 5.7 5.6 18.8 17.4 3.5 6.4 8.9 6.3 12.8 3.7 19.7 : 13.2 :

Source: Eurostat. EU-LFS [edat_lfse_02] (data extracted October 2014).

Explanatory note

Foreign-born (1_{) is a person whose place of birth (or usual residence of the mother at the time of the birth) is outside the}

country of his/her usual residence.

Native-born is a person whose place of birth (or usual residence of the mother at the time of the birth) is the country of his/her usual residence.

Country specific note

Czech Republic, Denmark, Estonia, Croatia, Latvia, Luxembourg, Hungary, Malta, Poland, Slovenia, Slovakia and

Finland: Low reliability ofdata for foreign-born.

The proportion of foreign-born compared to those born in the reporting country is nearly three to five times as high in Greece, Slovenia, Croatia, Austria and Switzerland. In Belgium, Spain, France, Italy, Cyprus, Finland and Sweden, the rates of early leavers among foreign-born students are still around twice as high. The latter is comparable with the EU-28 average of 22.6 % amongst foreign-born students versus 11.0 % for the native student population. In Denmark, Ireland, Malta, the Netherlands and Portugal, the differences between the two groups are relatively lower, even though in some of these countries, high rates of migrants exist. Finally, one country stands out as an exception: the United Kingdom has a slightly higher rate of students leaving education and training early among those born in the country.

According to a study carried out in Spain, being of foreign origin increases the probability of leaving education early by 16 % (IVIE, 2013). In 2013, the ELET rate of students with foreign nationality was nearly twice the rate of Spanish students. However, this does not seem to wholly explain the early leaving trend in Spain, as the percentage of migrant students alone does not account for the differences in the ELET rates between the Autonomous Communities (Ministry of Education, Social Policy and Sport, 2008). Furthermore, the study carried out by Afsa (2012) in France, reveals that children of migrants are no more prone to early leaving than other (non-migrant) children.

Traag and van der Velden (2011), who carried out a study in the Netherlands, suggest that students from ethnic minorities are more at risk of leaving school prematurely than the rest of the student population because they may lack what they refer to as 'human capital' that provides a cognitively stimulating learning environment in which the child develops. This 'human capital' is measured in terms of parental educational attainment levels; the higher parents' educational level is, the less likely the child is to drop out of school (see also previous section on socio-economic background). They state that in the context of the Netherlands, second generation migrants generally have lower educational levels than the rest of the student population and this may have an impact on their employment prospects. Furthermore, children from migrant backgrounds are less likely to attend early childhood education, which proves beneficial in developing the language skills of their host country and is a key factor for students' success at school.

Non-participation in ECEC, difficulties in accessing high quality education, not least as a result of socio-economic segregation (as explained in the following section), lack of parental support and insufficient skills in the language of instruction, all have an impact on the attainment of migrant students (European Commission, 2013b). Educational approaches and teaching methods that do not pay sufficient attention to the needs of migrant students, as well as ethnic discrimination in some educational institutions may further impede students’ chances of success in school (Luciak, 2004). In terms of ethno-cultural minority groups, Roma and Irish Travellers have often been identified as being among the most disadvantaged groups in education and consequently at greater risk of leaving school early (Luciak, 2006; Jugović and Doolan, 2013). According to research results presented in a Hungarian study by Kertesi-Kézdi (2010), for example, about 50 % of the total Roma population finishes upper secondary school, which is still very low compared to the 85 % of the non-Roma population. As Roma and traveller communities are a particularly vulnerable group in terms of participation in education and achieving success, they are therefore at greater risk of leaving school early. A number of countries (2_{) have implemented targeted policies and measures to reduce ELET} rates amongst this group (see Chapter 3, Section 3.3).

Although some common problems among students from migrant/minority backgrounds, such as language and cultural barriers, can lead to educational disadvantage and potential risk of early leaving, they can also be quite easily identified and tackled. Students with a migrant background constitute a rather heterogeneous group and diversity prevails over common characteristics. For instance, differences exist between newly arrived migrant children and second generation migrants. The latter group usually experiences greater success at school than the recent arrivals (Luciak, 2004). Furthermore, although differences within and between ethnic minority groups are difficult to trace, data on school completion rates in the United Kingdom (England), for instance, show that students from certain ethnic backgrounds, for example, those of Chinese and Indian origin perform better in education than students of African Caribbean, Pakistani and Bangladeshi origin, or Roma and Traveller students (Luciak, 2006). Statistical data from the United Kingdom shows that if appropriate support is given to these groups, they can achieve higher attainment levels than the average student attainment (3).

In fact, it is the socio-economic/family background and having adequate learning support that seems to play a more critical role in successful educational outcomes rather than the 'migrant' or 'non-migrant'

Chapter 2: Fac tors Contributing to Students Leav ing the Educ ation and Training Sy stem Early

Gender

According to Traag and van der Velden (2011), in comparison to girls, boys are almost twice as likely to leave school with low or no qualifications. International and national research confirms that male students are more likely to be early leavers than female students (European Commission, 2009; EACEA/Eurydice, 2009; ROA 2013; de Witte et al., 2013; see Chapter 6 for more information on the impact of gender on ELVET).

In Greece, boys in lower secondary, general upper secondary and in technical vocational education, throughout all geographical areas (urban, suburban, rural) present higher ELET rates compared to girls. This difference is even higher in rural areas (Rousseas and Vretakou/Hellenic Pedagogical Institute, 2006).

Data collected by the Ministry of Education in Italy in 2013 through the students’ register also confirmed that males are more at risk of leaving school than female students.

The most recent rates for male and female early leavers from education and training across Europe corroborate this finding as they demonstrate a consistent gender pattern (see Figure 2.3). The EU-28 average of males aged 18-24 with lower secondary education at most and who are not in further education or training is 13.6 %, versus 10.2 % for females. Although there are some discrepancies between European countries, in almost all countries, the rates of male early leavers are higher than the rates for females. For Cyprus the difference is more than 10 percentage points. Other countries with high disparities between male and female rates are Estonia, Spain, Italy, Latvia, Portugal and Iceland, with differences varying from 6.5 to 9.1 percentage points. In only a few countries (Slovakia, Austria and Switzerland), the difference in rates between male and female early leavers is below 1.0 percentage point.

Two countries (Bulgaria and Turkey) reveal the opposite trend. The figures show slightly higher rates of early leaving for females than for male students, with differences of 0.4 for Bulgaria and 4.9 for Turkey. Cemalcilar and Goksen (2012) explain that girls in Turkey either do not attend any school or they leave very early. According to these authors, persisting gender differences in educational outcomes in Turkey are due to the interrelated effects of macro-structures (e.g. limited labour market participation of women), family factors and cultural expectations towards girls.

Figure 2.3: Percentage of early leavers from education and training by sex, 2013

% %

Males Females

Data (Figure 2.3) % EU-28 BE BG CZ DK DE EE IE EL ES FR HR IT CY LV LT LU Males 13.6 13.2 12.3 5.4 9.9 10.4 13.6 9.8 12.7 27.2 10.7 5.5 20.2 14.8 13.6 7.8 8.4 Females 10.2 8.7 12.7 5.5 6.2 9.3 5.8 6.9 7.5 19.8 8.7 3.4 13.7 4.2 5.8 4.7 3.7 HU MT NL AT PL PT RO SI SK FI SE UK CH IS LI NO TR Males 12.5 23.2 10.9 7.7 7.9 23.4 18.6 5.0 6.7 10.4 7.9 13.7 5.6 24.4 : 15.7 35.0 Females 11.1 18.4 7.4 7.0 3.2 14.3 16.0 2.6 6.1 8.3 6.2 11.2 5.2 16.4 : 11.6 39.9

Source: Eurostat, EU_LFS [edat_lfse_14] (data extracted October 2014).

Country specific notes

Croatia: Low reliability of data.

Lithuania, Luxembourg and Slovenia: Low reliability of data for female early leavers.

The fact that males are over-represented among the students leaving education and training early also suggests a strong link between gender and educational achievement. Indeed, girls tend to outperform boys at school, and more girls than boys receive upper secondary education (OECD, 2012). This may generally arise from the different experiences of boys and girls in compulsory education. It is believed, for instance, that boys are prone to more difficulties than girls in adapting to the school environment (Nevala et al., 2011).

International assessments of student achievement reveal that girls have a visible advantage over boys in reading. Boys on the other hand perform better in mathematics and science than girls. However, both boys and girls can equally be affected by socio-economic disadvantage, which in turn increases the risk of low attainment. Gender, therefore, constitutes only one of numerous factors accounting for the variations in educational achievement in different subject fields. In fact, socio-economic background and status seems to be a stronger predictor of educational achievement than gender alone (EACEA/Eurydice, 2010).

Dumais (2002) considers that students with a higher socio-economic status tend to do better at school and the higher the socio-economic status of an individual, the less likely gender comes in to play. Along similar lines, Flouri and Ereky-Stevens (2008) put forward the premise that although boys from 'poor' or 'average' neighbourhoods are more likely to leave school after compulsory education than girls living in the same neighbourhood, the gender difference in 'well-to-do' neighbourhoods seems to be insignificant.

In their analysis, Beekhoven and Dekkers (2005) conclude that parents of children from a higher socio-economic background have the knowledge and financial resources to give their children better help throughout their education than parents with limited cultural, social and economic capital. Furthermore, the lack of certain resources (i.e. cultural and social capital) seems to be more significant in explaining early leaving from education and training when it comes to boys. Beekhoven and

Chapter 2: Fac tors Contributing to Students Leav ing the Educ ation and Training Sy stem Early

2.2. Education system related factors

Education policies that encourage a stimulating learning environment for all learners, and especially for those who are struggling in school as a result of their individual circumstances and/or family background, can contribute to preventing early leaving. Education and training systems can create this type of learning environment if students are placed at the centre of the learning process and if teaching, learning and support is personalised in order to respond to students’ individual needs and talents.

Some school-related factors that have an impact on early leaving are not discussed in detail here. These concern the school climate, including conflicts with teachers, violence in school, bullying, etc. Furthermore, individuals’ school-related problems are not elaborated here; however, they often play a role in students' decision to leave school early. In Croatia, for example, some of the most commonly reported reasons for early leaving are: low educational achievement, lack of motivation and discipline problems (Feric et al., 2010). Similarly, in France, student achievement has been reported as one of the main predictive factors of early leaving, after controlling for the effects of socio-economic background and grade retention (Afsa, 2012).

The features of education systems discussed below, which can have a negative impact on ELET rates include grade retention, the socio-economic segregation of schools and early tracking. In contrast, other highlighted features, which have a positive effect on preventing or reducing early leaving, are high quality early childhood education and care and well-designed primary and secondary education.