1 Sociale ongelijkheid en integratie in het onderwijs Emeritiforum – 23 oktober 2008 Jan Van Damme, K.U.Leuven

2 INLEIDING 1.Secundair onderwijs 2.Basisonderwijs 3.Wat moeten we denken van het PISA-verhaal? 4.Conclusie

3 1.Secundair onderwijs a.Eindpositie S.O. (en vertraging) : functie van sekse, SES en allochtoon/autochtoon? - zonder aanvangskenmerken S.O. - met aanvangskenmerken S.O. b.Effect van soort medeleerlingen als vorm van kansenongelijkheid + mogelijke reacties van scholen en leerkrachten

4 Eindpositie S.O.

5 Laatste succesvolle positie ih. S.O. zonder controle voor aanvangskenmerken - Meisjes > Jongens -Hoge SES > Lage SES -Autochtonen > Allochtonen Interactie-effect tussen etniciteit en SES: het effect van SES is kleiner voor allochtone leerlingen dan voor autochtone leerlingen

6 Laatste succesvolle positie ih. S.O. onder controle voor aanvangskenmerken - Meisjes > Jongens -Hoge SES > Lage SES - Geen effect van etniciteit

7 1.Secundair onderwijs a.Eindpositie S.O. (en vertraging) : functie van sekse, SES en allochtoon/autochtoon? - zonder aanvangskenmerken S.O. - met aanvangskenmerken S.O. b.Effect van soort medeleerlingen als vorm van kansenongelijkheid + mogelijke reacties van scholen en leerkrachten

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12 1.Secundair onderwijs 2.Basisonderwijs 3.Wat moeten we denken van het PISA-verhaal? 4.Conclusie

13 2. Basisonderwijs

14 Ongelijkheid tussen leerlingen Gecorrigeerde score wiskunde  NL niet-GOK ▲ AT niet-GOK  NL-GOK ▼ Turks-GOK ◆ Arab/Berber GOK □ Overige AT-GOK Begin L1 Einde L1 Einde L2 Wiskunde

15 Ongelijkheid tussen leerlingen Gecorrigeerde score wiskunde  NL niet-GOK ▲ AT niet-GOK  NL-GOK ▼ Turks-GOK ◆ Arab/Berber GOK □ Overige AT-GOK Begin L1 Einde L1 Einde L2 Wiskunde

16 Ongelijkheid tussen leerlingen Gecorrigeerde score wiskunde  NL niet-GOK ▲ AT niet-GOK  NL-GOK ▼ Turks-GOK ◆ Arab/Berber GOK □ Overige AT-GOK Begin L1 Einde L1 Einde L2 Wiskunde

17 Ongelijkheid tussen leerlingen Wiskunde Gecorrigeerde score wiskunde  NL niet-GOK ▲ AT niet-GOK  NL-GOK ▼ Turks-GOK ◆ Arab/Berber GOK □ Overige AT-GOK Begin L1 Einde L1 Einde L2 Initiële kloof: 31%  92% van jaarlijkse gemiddelde leerwinst; Kloof einde L2: 19%  65%

18 Background  achievement Initial gap for mathematics –“ Large ” in terms of % average annual learning gain: 30% - 90%  Gap = 1 trimester up to almost one full school year ! –Large differences between student categories Constant gap for Dutch speaking ED students + no other ED-categories raise above  Socially determined gap appears hard to overcome non-Dutch sp. ED make recovery move in G1  Ethnic-cultural gap appears less hard to overcome Maths (SiBO)

19 Ongelijkheid tussen leerlingen Technisch lezen Gecorrigeerde score DMT  NL niet-GOK ▲ AT niet-GOK  NL-GOK ▼ Turks-GOK ◆ Arab/Berber GOK □ Overige AT-GOK Begin L1 Einde L1 Einde L2 Kloof: 2%  25% van jaarlijkse gemiddelde leerwinst

20 Ongelijkheid tussen leerlingen Spelling Kloof: 10%  38% van jaarlijkse gemiddelde leerwinst Gecorrigeerde score spelling  NL niet-GOK ▲ AT niet-GOK  NL-GOK ▼ Turks-GOK ◆ Arab/Berber GOK □ Overige AT-GOK Begin L1 Einde L1 Einde L2

21 Background  achievement Reading comprehension G4 (PIRLS) Invloed voorschoolse thuistaal P75 P50 P25 Néerlandophone Turque Arabe / BerberAutre

22 Background  achievement Reading comprehension G4 (PIRLS) Cumulated effects of different factors P75 P50 P25 ED Turkish ED Arab / B ED Dutch Average Dutch Advant. Dutch

23 Rol aanv. NL taalvaardigheid WiskundeTechn lezen Spelling NL – GOK44%65%45% Turk.- GOK41%77%85% Arab – GOK31%74%52% OAT – GOK38%91%63% AT – niet GOK29%---92% Onbekend39%57%47% Pct van kloof (begin / einde L1) verklaard door gebrek aan aanvankelijke Nederlandse taalvaardigheid

24 Background  achievement Summary Low SES & minority group students face a serious gap at start of grade 1 –for maths, reading fluency & spelling Lack of initial Dutch language proficiency plays an important role Some recovery move in course of G1 for minority students, not for low SES students A persistent gap throughout primary education –e.g. reading comprehension

25 Differences in effectiveness “Value added” –Measure for school effectiveness –Shows contribution of school to students’ learning having adjusted for effects of social background –Relative measure: Shows difference with “average school” Shows difference with “what could be expected taking into account school’s intake characteristics”

26 Verschillen tussen scholen Verschillen in toegevoegde waarde m.b.t. leerwinst wiskunde L1 + L2 Verschil P10 – P90 ≈ half schooljaar P10P90 scholen Schoolresidu leerwinst wiskunde L1+L2 +/- 1,39 SE

27 Verschillen tussen scholen 4 clusters van scholen op basis van instroom –“kansrijk” ▲ ( 6 % v.d. scholen) Gem. 52% niet-NL niet-GOK Vooral Franstaligen, hoge SES –“modaal” ● (70 % v.d. scholen) Gem. 70 % NL niet-GOK –“kansarm” ■ (20 % v.d. scholen) Gem. 36% NL niet-GOK Gem. 24% NL GOK –“zeer kansarm” ▼ ( 4 % v.d. scholen) Gem. 44% niet-NL GOK Gem. 15% niet-NL niet-GOK

28 Verschillen tussen scholen  Geen verband tussen samenstelling schoolbevolking en “effectiviteit” Verschillen in toegevoegde waarde m.b.t. leerwinst wiskunde L1 + L2 Schoolresidu leerwinst wiskunde L1+L2 +/- 1,39 SE scholen

29 3.Wat moeten we denken van het PISA-verhaal? a.De OESO en anderen brengen het met verve. b.Wordt dat verhaal bevestigd door ander onderzoek? bijdrage UCL bijdrage van de Hofmans e.a. bijdrage van Dronkers e.a. c.Andere vragen die rijzen

30 Variation of performance between schools Is it all innate ability? Variation in student performance in mathematics OECD (2004), Learning for tomorrow’s world: First results from PISA 2003, Table 4.1a, p.383. In some countries, parents can rely on high and consistent standards across schools –In Canada, Denmark, Finland, Iceland and Sweden average student performance is high… …and largely unrelated to the individual schools in which students are enrolled Variation of performance within schools

31 Variation in student performance in mathematics Variation of performance between schools Variation of performance within schools Variation explained by socio- economic level of students and schools OECD (2004), Learning for tomorrow’s world: First results from PISA 2003, Table 4.1a, p.383. In other countries, large performance differences among schools persist –In Austria, Belgium, Germany, Hungary, Italy, Japan, the Netherlands and Turkey, most of the performance variation among schools lies between schools… …and in some of these countries, most notably those that are highly stratified, a large part of that variation is explained by socio-economic inequalities in learning opportunities Belgium: 43%, OECD: 23%, Canada: 7%, Finland: 1%

32 School performance and schools’ socio- economic background - Finland Student performance and student SES Student performance and student SES within schools School performance and school SES School proportional to size Student performance

33 Durchschnittliche Schülerleistungen im Bereich Mathematik Strong socio-economic impact on student performance Socially equitable distribution of learning opportunities High mathematics performance Low mathematics performance Early selection and institutional differentiation High degree of stratification Low degree of stratification Greece Russian Federation Liechtenstein Korea Hong Kong-China Finland Netherlands Canada Switzerland New Zealand Belgium Japan Australia Iceland Czech Republic Sweden France Denmark Ireland Germany Austria Slovak Republic Luxembourg PolandHungary Norway Spain United States Latvia PortugalItaly

34 INSTITUTIONAL CONTEXT OFEDUCATION SYSTEMSIN EUROPE A cross-country comparison on quality and equity Editors Hofman R. H. Hofman W.H.A. ­Gray J. Daly P. Co-authors: Gertrudes Amaro Peter Daly Birgitta Fredander John Gray Henk Guldemond Adriaan Hofman Roelande Hofman Dimokritos Kavadias Maria Isabel Lopes da Silva Javier Murillo Franck Poupeau Graham Thorpe Peter Weng

35 QUALITY AND EQUITY OF EUROPEAN EDUCATION SYSTEMS Quality: Are their major differences in achievement between students in the 13 European education systems? Equity: Do the 13 European countries differ in the achievement gap between their native and their minority students? Institutional contexts: Are there trends in the data showing relationships between quality and equity of these education systems and certain institutional characteristics of these countries Explanations: And, if such trends appear, what kind of explanations can we found upon them?

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39  Indicators of concepts of institutional context:  Size and type of funding: -4 indicators of relative sizes of public and private sector -3 types of financial bases on which they are founded  Variation in governance and power: -4 types of governance structures -3 models of power of school councils (that include parents)  Degree of school choice: - 4 types of freedom of school choice -3 models regarding school fees to be paid

40 Configuration theory: Multi Dimensional Scaling 2 dimensions resulting from MDS 4 configurations of countries

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43 Some conclusions: countries that include high percentages of students within grant-aided education have been performing better in terms of quality than countries that are dominated by public schools (or less than 10%) Furthermore, the native students in these countries tended to be near the top of the quality rankings Countries with relatively high percentages of students in grant-aided schools tended to perform better than others when equity dimensions are taken into account. The gap in performance between low/ses and native high/middle-ses students is frequently smaller The Netherlands and Belgium scored well overall and in terms of performance of their low/ses minorities. However, for their ethnic minority students, the picture was by no means as favourable. A reverse pattern can be seen for countries as Portugal and Spain

44 Immigrants and school segregation by Dronkers & Levels (PISA 2003)

45 Study 1 by Levels and Dronkers (2005) Big differences in achievement between students from another ethnic background and native students Why? 1)Country of origin 2)Country of residence 3)SES

46 Data: PISA 2003 (students math achievement at age 15) Results: 1) Country of origin → achievement of students 2) Country of residence → achievement of students 3) Effects of country of origin on achievement are stronger than the effects of country of residence 4) 1st and 2nd generation students from countries in West-Asia, North-Africa, Latin-America scored lower in math than students from countries in Europe and the Pacific Rim even after controlling for SES → effect of country of origin on achievement cannot be reduced to the effect of SES on achievement →explanation? Distance between culture of origin and current culture

47 Study 2 by Dronkers and Levels (2005) Main research question: Are the lower achievement of students from another ethnic background related to the SES and the ethnic school composition? Hypotheses: 1)The effect of the SES and the ethnic composition of schools on achievement is larger for the students from another ethnic background than for native students 2)The variation between countries of the effect of SES and the ethnic composition of schools on achievement is related to differences in school resources 3)The effect of the SES and the ethnic composition of schools on achievement is larger for students from West-Asia, North-Africa and Latin America than for students from other regions

48 Main results: 1) The SES composition of schools has a larger impact on achievement than the ethnic composition of schools 2) The SES and the ethnic composition of schools have independent effects on achievement 3) The effects of the ethnic school composition are not larger for students from West-Asia, North-Africa, Latin-America than for students from Europe and the Pacific Rim → the differences in achievement between students from different ethnic background could not be explained by the school SES en ethnic segregation

49 4) The variation between countries of the effect of SES and the ethnic composition of schools on achievement was not related to differences in school resources 5) The high achieving students in math (native students and students from Europe, North-America, Australia and Southeast Asia) are more negatively influenced by the ethnic school segregation than the lower achieving students in math → the ethnic school segregation is not negative for all students 6) The SES segregation of schools is negative for all students

50 3.Wat moeten we denken van het PISA-verhaal? a.De OESO en anderen brengen het met verve. b.Wordt dat verhaal bevestigd door ander onderzoek? c.Andere vragen die rijzen: Verwachte evoluties gezien het gevoerde beleid Is een benadering op basis van een leeftijdscohorte adequaat om het onderwijs te evalueren? Zijn de prestatieverschillen tussen scholen meer dan instroomverschillen? Wat meet PISA?

51 4. Conclusie Aan welk soort onderzoek is er behoefte?