Data Collection on and Monitoring of Early School Leaving (ESL)

Transcription

1 Data Collection on and Monitoring of Early School Leaving (ESL) Draft analysis of the results from the mapping exercise on data collection and monitoring of ESL Contents Introduction... 2 Definition of Early School Leaving... 3 Type of data collected... 3 Data collection methods... 6 Local and regional data collection systems... 8 Future data monitoring needs... 9 Conclusions

2 Introduction At their first meeting in December 2011, members of the Thematic Working Group (TWG) on Early School Leaving discussed the importance of data collection on early school leaving (ESL). Good quality data allow for the identification of groups of pupils, regions, municipalities or schools which are especially affected by ESL. Strong disparities in rates of early school leaving can indicate specific structural problems in certain geographical areas or educational tracks. It was also recognised by the TWG that there is currently not enough comparative information on the methods and practices European countries use to monitor the scale and scope of ESL. Therefore it was decided to launch a mapping exercise to collect more systematic information on data collection methods and practices. This is seen as the first step in the process of comparing the different practices and developing policy guidance on data collection and monitoring of ESL. A questionnaire was sent to all members of the TWG in February 2012; by December countries 1 had replied to it and provided information on their data collection methods. The Council Recommendation on policies to reduce early school leaving from June 2011 (OJ C ) states that "The development of evidence-based and cost-effective policies to combat early school leaving requires gathering and maintaining data on the phenomenon. This should allow analysis at local, regional and national levels. It may contain information on early school leaving rates, on transitions between educational levels, enrolment rates and completion rates of upper secondary education, as well as on school absenteeism and school-avoiding behaviour." The Recommendation highlights the need to collect information on the main reasons underlying early school leaving for different groups of pupils, schools, types of education and training institution, municipalities or regions, and to combine data on early school leaving and contextual data such as socio-economic information in order to better target measures and policies The mapping exercise shows that most countries face difficulties in establishing data collection systems that fulfill these requirements. The following analysis describes the current situation and aims to identify the main gaps and difficulties in collecting relevant information on early school leaving processes. The structure and use of data collection and monitoring systems is strongly linked to the existence or development of so called early warning systems (EWS) to identify young people at risk of dropping out. EWSs are the subject of another mapping exercise. The results of both mappings will support the TWG in their work on developing guidelines for evidence-based and comprehensive policies against ESL. 1 AT, BE, BG, CZ, EE, ES, HU, IE, LU, LT, MT, PL, SK, SI, SE, UK, HR, IS, NO. 2

3 Definition of Early School Leaving ESL can be defined as a failure to complete upper secondary school, a failure to complete compulsory schooling or a failure to gain qualifications or school leaving certificates. The term is often distinguished from the term "school drop-out" which refers to discontinuing an ongoing course in general or vocational education and training. At EU level ESL rates are defined by the proportion of the population aged with only lower secondary education or less and no longer in education or training. Early school leavers are young people who have only achieved pre-primary, primary, lower secondary or a short upper secondary education of less than 2 years (ISCED 0, 1, 2 or 3c short ), and include those who have only a prevocational or vocational education which did not lead to an upper secondary certification. Only few Member States, e.g. Bulgaria, Czech Republic, Malta, Spain, Ireland and Slovakia, use this definition. Most national definitions of ESL refer to the non-completion of compulsory education. Compulsory education is defined either by age (with a range from 15 to 18 years across countries) or by educational level, e.g. having achieved a school leaving certificate/ qualification. Strongly linked to that is the fact that many countries measure school drop-out rather than ESL; they count the number of students who discontinue education during the school year or do not return to school at the start of the new school year. The European Labour Force Survey (LFS) provides additional data by measuring the educational level of young people at a later stage in their lives and education careers. The following examples show the differences in defining ESL. Belgium (nl): Early school leavers are students who are no longer in compulsory education and who did not obtain a qualification e.g. diploma of secondary education or vocational education certificate. Iceland: Statistics Iceland defines early school leavers as the percentage of students who have been listed in the student registers for year N and are not included in the registers in the following year, are still alive but have not graduated. Sweden: The municipalities are required by law to monitor the number of inhabitants aged years who are not attending upper secondary education in order to offer them education and training perspectives. In Sweden ESL can therefore be defined as not having completed upper secondary education even though upper secondary education is not compulsory. Hungary: Early school leavers are those who do not have an upper secondary level qualification, but only lower secondary or primary education. Data collection systems are strongly linked to the definition of ESL or school drop-out; in some cases the availability of data might also shape the understanding of ESL. Type of data collected Most countries have a national data collection system which also provides data at NUTS level 2 and 3. In some countries regional and national data collection systems are combined and provide 3

4 complementary information. Often local and regional data are aggregated at national level. Answers show that the establishment of more elaborate national data collection systems in the area of education and training and especially with regard to early school leaving is a recent development. Several countries introduced new systems in the last years in order to better monitor developments in education and training. As illustrated below there is an overall tendency to develop national student registers or to introduce an individual student number and to allow for tracking learning careers in the education and training system. The introduction of these systems is not necessarily triggered by the level of early school leaving; student registers or data bases with individual student numbers provide advantages in the monitoring of education and training in general. All countries collect data on the number of early school leavers, their educational level and their sex. What is also often monitored is absenteeism, educational performance and the repetition of school years. The transition rate from lower to upper secondary education is also monitored by most countries, sometimes based on estimations. But additional background information on students is collected only by half of the countries answering to the questionnaire. The graph shows that data collections rely mainly on data available within the school education system: educational level from which young people drop out, presence or absenteeism, marks, repetition of school years. Contextual data such as socio-economic information is collected by 10 out of 18 countries, but this information is often incomplete: 8 countries collect information on migration status, 6 on the educational background of parents and only 3 on the socio-economic background of students. This might be strongly linked to availability of data; looking at the data used in the context of early warning systems, more information on the background of students seems to be available at local level, but is not systematically collected at national level. 4

5 Lithuania collects at national, regional and local level information on the number of early school leavers, the educational level (including VET), gender, migration background (partly), absenteeism, educational performance, year repetition and behavior. It is planned to collect in future also information on the socio-economic background and on the educational level of parents. Lithuania has a national student register with individual student numbers, requests schools to report on the performance of their students and runs additional surveys. In Sweden, the national agency responsible for financial aid for students (CSN) hosts data on each student in upper secondary education. Every month the school has to report on the students presence to CSN and depending on the level of absenteeism financial aid is paid or withdrawn. The local/sub-local level (school) level has the most detailed information about the students, e.g. marks/grades and test results. Information on student behaviour and reasons for dropout are sometimes also available locally. Background data are extracted from national population registers and linked through the social security number. 8 countries have access to data of individual pupils. In many countries these individual data sets exist, but for data protection reasons, data are only used in aggregated format. Also here more detailed information on students is often available at local level, but not integrated in the national data collection system. Only 7 countries systematically gather information on the main reasons for early school leaving or drop-out; some countries collect this information in the context of studies or specific surveys. The reasons identified are mainly related to personal and family circumstance, to educational problems, the relation with school or teachers, motivation and pull-factors from the labour market. Research on the reasons of young people for leaving education and training show the relevance of this information for policy development. Regular studies carried out by the Research Centre for Education and the Labour Market (ROA) (University of Maastricht) reveal for the Netherlands that the principal reasons for ESL are education related (cited as the reason by 28% of early school leavers), personal problems (23%) and labour market pull factors (16%). Also (mental) health problems play an important role. 2 In Luxembourg statistics show for 2009/2010 that 17,9 % of all drop-outs left school due to educational problems, 11 % said that they couldn't find an apprenticeship, 11,1 % indicated wrong study choice as reason for dropping out and 10,7 % mentioned personal reasons. 3 The reasons for young people to leave education and training may differ from country to country and from region to region, depending on the education and training system, the situation on the labour market and the social situation of young people. While ad hoc studies or surveys provide an insight in the motivation of early school leavers, they do not allow the monitoring of developments or of the situation of specific risk groups. 2 Research Centre for Education and the Labour Market (ROA) (2007) taken from the presentation of Christop Meng on Early School Leaving: Causes and Chances at European Commission 3 Tageblatt.lu, 13 March 2012; referring to a study of the 'Action locales pour les Jeunes' in Luxembourg. 5

6 Data collection methods All countries use different sources for their data collection: administrative data gathered through regular reports from educational institutions, information from student registers, dedicated surveys and studies. Nearly all countries answering to the questionnaire have either a system of individual pupil numbers or a student register or both. Some of them introduced the system only recently; one country reported difficulties in tracking individual student careers due to concerns about data protection. This problem was also reported by other European countries not participating in this mapping exercise. In addition to sometimes very elaborate systems of data collection, in nearly all countries schools have a legal obligation to report on attendance and/or on drop-out. Estonia is in the process of introducing such a reporting obligation. 9 countries also conduct regular surveys and studies in addition to the LFS of Eurostat. Estonian Educational Information System (EEIS) is a national register that consolidates information concerning the education system. The information entered into the register includes information on educational institutions and individual information on students, teachers, graduation documents and curricula. Local governments can use EEIS to access information concerning the students living in their territory as well as information on the transfer of students to a school located in the territory of another local government. Educational institutions have access to all of the information contained in EHIS concerning the institutions themselves and their students and teachers. Educational institutions also have the obligation to enter information into EEIS and to check and amend the entered information. Students and teachers can see the education-related information concerning themselves. The register keeps track of each student's education career. It is also visible if the student has dropped out of school and if he/she has continued in evening school, vocational school etc. The register does not provide data about entry into the labour market. The national student data base in Luxembourg allows for a quick follow up of every early school leaver. Parents receive a letter in a month s time after their child has dropped out of school and are invited to contact the Action Locale pour Jeunes (ALJ). ALJ provides information and guidance and tries to find a good solution for each young person to continue education and training. If parents do not reply to this invitation, the social education workers will try to contact them during the next 3 months to offer help. Despite the wealth of data sources, administrative data are often not or not sufficiently used for analyzing early school leaving processes or for developing policy advice. Several countries report that data are collected for administrative purposes only or that data are not analysed and published quickly enough to be useful for policy making. Also the format in which data and information on ESL processes are provided and their quality can hamper their use in policy making. 6

7 In the UK (England) several publications provide data on early school leaving. Statistical First Release: Participation in education, training and employment by year olds in England: This is an annual publication that draws together administrative data about young people in education from schools, colleges and Universities to estimate the number and proportion of young people who are NET (not in education or training). It provides overall numbers and proportions of young people in education and training; their gender and age; the level and type of institution in which they are studying. 4 Youth Cohort Survey and Longitudinal Survey of Young People in England: Beginning at the age of 14, this survey tracks a sample of young people, each year, until age 19. It collects information about their characteristics, aspirations and attitudes towards education, training and other factors that affect them. Local Authority Databases: Local authorities maintain databases that hold information on all young people resident in their area. Information provided by schools and colleges is put onto the database, so that those who are not in education or training can be identified. Information from advisers, youth workers and specialist support services can also be recorded on the database to build an overview of the characteristics of those not in education or training. An extract from each areas local database is transferred to the Department each month and is used to produce figures on young people not in education and training in each region and local authority area. In most countries the Ministries of Education and the National Statistical Offices are in charge of the data collection and the publication of official data on ESL. Sometimes also local or regional authorities are involved in this process. In Ireland the School Completion Programme, a national measure to reduce ESL, annually collects data on young people not completing educational milestones. The question of ownership of data and their use for policy development might need further attention. The strong link between definition of ESL, data collection and the understanding of ESL processes points to the importance of involving the main stakeholders in combatting ESL in the development of data collection and monitoring systems. To complement the information on ESL, most countries conduct surveys and studies. The majority of these studies are ad hoc studies covering the following aspects of ESL: Social background of early school leavers, profile of early school leavers Reasons for ESL and motivation of early school leavers Consequences of ESL, social exclusion and labour market prospective of early school leavers Costs of early school leaving 4 The latest publication can be found here: 7

8 ESL in VET Local or regional situation, activities at municipality level to reduce ESL Longitudinal studies on early school leaving and school failure, life course surveys Development of indicators for equity in education and to better monitor ESL Ad-hoc studies risk providing non-comparable data and regionally or time limited data. They can often only be a snapshot of the situation in one specific area or in a specific timeframe. Some studies try to overcome these limits by e.g. using longitudinal data. Regional studies or surveys can have the advantage to address the specific situation in a region and to be able to provide more specific policy recommendations. Spain has not conducted a national study on ESL, but several regional studies complement information on ESL in Spain. For example: The study El abandono escolar temprano en las ciudades de Ceuta y Melilla (2010) carried out by the University of Granada analyzes the profile of ESL in these two cities by personal, school academic and family background and the reasons why the individuals left school. It also evaluates the training needs of early school leavers, possible cooperation between socio community organizations and schools, and the importance of specific measures to prevent ESL. Fracaso y abandono escolar en España (2010) is a longitudinal study of 856 students who left school in the year They belonged to 35 different schools of the Autonomous Community of Castile Leon and the Community of Madrid. Hungary launched in 2006 a Life Course Survey which follows students from the 8th grade (last grade of primary education) till the end of upper secondary education using questionnaires. It enables the most important trends both in school success and school drop-out to be analysed. Norway conducted several studies during the last years addressing the effect of different student background characteristics, the difference between groups of students (gender, immigrant background, parents education, etc.), the cost of ESL (for the individual and the society), and the consequences of ESL for the labour market (salary, employability). Local and regional data collection systems As mentioned above, most countries have national data collection systems. In some cases regions or municipalities are in charge of providing the data e.g. through regular reporting. But some countries report also on data and monitoring systems operating independently at regional or local level. In Belgium (Flanders) some municipalities collect e.g. data on truancy; the methods used by municipalities differ. Also Hungary, Sweden, the UK (England) and Croatia report on different data collection systems used at local or regional level. In other countries municipalities use systems which are either directly linked to the national system or follow the same structure. Also the way municipalities are using the collected information can differ substantially. 8

9 While local and regional data collection systems might respond better to the situation within a region or municipality, they risk a lack of comparability and do not substitute for general information on ESL at national level. Harmonized systems with a certain level of flexibility might offer advantages compared to a broad local or regional variety in data collection. Future data monitoring needs The mapping exercises demonstrated shortcomings in the way data and information on ESL are collected in most European countries. Asked about the strengths and weaknesses in their data collection systems, countries are in general satisfied with the high reliability of their data and the fact that all schools are covered. Only in Ireland are private schools not integrated into the national data collection and monitoring system. Weaknesses are in all countries related to gaps in the type of data and information collected. These gaps concern the lack of information on the socio-economic background of early school leavers and on their motivation. Several countries indicated that there is a need to get more information on the profile of early school leavers. Little information is collected on the motivation to leave education and training prematurely. Also the situation of specific groups with a high risk of dropping out (e.g. Roma, migrants) cannot be monitored sufficiently in all countries, sometimes lacking information such as the age of newly arrived migrants when being integrated into the education system. Even if the follow-up of individual school drop-outs would be technically possible, countries lack the resources to do so. One country expressed the need to better monitor NEETs, young people not in employment, education and training. The focus of data collection is criticized by two countries: They highlight that measuring attendance instead of drop-out or collecting data on absenteeism and drop-out but not on the overall problem of early school leaving risks to create a false understanding of the situation, and consequently might lead to wrong policy choices. The cooperation between national, regional and local level also causes problems in some countries. Municipalities lack access to data or use different data collection systems. Insufficient communication between the municipalities or regions can also allow young people to 'escape' from the monitoring system by moving to another municipality. Here centralized systems with e.g. individual student numbers are seen as a possible solution. Besides the gaps in the methods used or the data and information collected, respondents worry about the limited use of the existing data and information for policy development. Conclusions Both criteria for good data collection and monitoring systems in the area of early school leaving as mentioned by the Council Recommendation seem to pose difficulties for the majority of countries: 9

10 Only limited and scattered information is available on the main reasons underlying early school leaving for different groups of pupils, schools, types of education and training institution, municipalities or regions. Data on early school leaving can often not be combined with contextual data such as socioeconomic information. These weaknesses are acknowledged by most countries answering to the questionnaire. For the future work of the TWG the following questions might be relevant: What type of data is necessary for a better understanding of ESL? How is the need of data and information on ESL influenced by a broadened understanding of ESL and the processes leading to it? How can these data be gathered without risking data protection problems or creating additional administrative burden for all stakeholders involved (schools, municipalities, regional and national governments)? Are there alternatives to student registers or the introduction and use of individual student numbers for statistical purposes? How can data from different sources be combined systematically? How can databases on education and training integrate contextual data and information such as information on the socio-economic background of students? What experiences exist in harmonizing local, regional and national data collection systems? How can the communication between different levels be ensured? Are there good practice examples in involving the main stakeholders in combatting ESL in the development of data collection systems on ESL? How can data be presented and published to be more accessible to policy makers? How can they be better used for policy development? 10