School Effectiveness and School Improvement
2002, Vol. 13, No. 4, pp. 383±397
0924-3453/02/1304-383$16.00
# Swets & Zeitlinger
A New Study on Educational Effectiveness in Secondary
Schools in Flanders: An Introduction
Jan Van Damme1, Bieke De Fraine1, Georges Van Landeghem1,
Marie-Christine Opdenakker1, and Patrick Onghena2
1
Secondary and Higher Education Research Centre, K.U. Leuven, Belgium, and 2Centre for
Methodology in Educational Sciences, K.U. Leuven, Belgium
ABSTRACT
As an introduction to the articles of Opdenakker, Van Damme, De Fraine, Van Landeghem, and
Onghena (2002) and Van Landeghem, Van Damme, Opdenakker, De Fraine, and Onghena
(2002) in this issue, we give some background information on a new study on educational
effectiveness in secondary schools, and on the variables measured in that study that are relevant
to the 2 articles mentioned. We conclude with some information on the system of secondary
education in Flanders.
THE LOSO-PROJECT
Ten years ago, Scheerens (1992) wrote: ``Apart from being dif®cult, a fully
¯edged state-of-the-art school effectiveness study is also a time-consuming
affair and a demanding organisational effort. In fact, studies that more or less
meet these requirements have been quite exceptional.'' And after mentioning
four examples ± the study of Mortimore, Sammons, Stoll, Lewis, and Ecob
(1988), and those of Brookover, Beady, Flood, Schweitzer, and Wisenbaker
(1979) and Rutter, Maughan, Mortimore, Ouston, and Smith (1979), and the
Louisiana School Effectiveness Study (e.g., String®eld & Teddlie, 1990),
Scheerens wrote: ``It is quite important that there be more state-of-the-art
studies, only in this way can the emerging substantive explanatory models of
Address correspondence to: Jan Van Damme, K.U. Leuven, Department of Educational
Sciences, Secondary and Higher Education Research Centre, Vesaliusstraat 2, B-3000 Leuven,
Belgium. Tel.: ‡32 (0)16 32 62 45. Fax: ‡32 (0)16 32 62 74. E-mail: Jan.VanDamme@
ped.kuleuven.ac.be
384
JAN VAN DAMME ET AL.
school effectiveness be further tested and re®ned'' (Scheerens, 1992, p. 66±
67). A perusal of the most important recent reference books in the domain of
school effectiveness research (e.g., Scheerens & Bosker, 1997; Teddlie &
Reynolds, 2000) shows that Scheerens' words are still true nowadays.
Since the beginning of the 1990s, a longitudinal study on school careers has
been realised in Flanders, the Dutch-speaking part of Belgium. The LOSOproject (``Longitudinaal Onderzoek in het Secundair Onderwijs,'' in English:
``Longitudinal Research in Secondary Education'') followed 6,411 students
entering one of 57 secondary schools, even when they changed schools, had to
repeat a grade, went to the university, or left the educational system and took a
job. The follow up will be ®nished shortly, after having kept track of at least
90% of the original group for at least 9 to 10 years. The sample of students was
taken from almost all schools of three regions in Flanders. The set of schools is
to a certain extent representative of the Flemish secondary schools in general.
The programmes offered and the distribution of the students over these
programmes is comparable to the situation in Flanders as a whole.
The main objectives of the data gathering design were:
± to have good intake measures, such as intelligence, initial achievement and
SES,
± to have a broad perspective on the functioning of the schools, classes, and
teachers. At the start of the project only the school level was considered, but
from the second grade on, also class-level processes were studied. Indeed,
in the beginning of the 1990s, it became more and more clear that the class
level is more important than the school level (Creemers, 1994; Hill &
Rowe, 1996; Reynolds et al., 1994; Teddlie, 1994). Because of the large
sample size, the LOSO data on schools, classes, and teachers had to be
collected by means of questionnaires.
± We aimed at studying a variety of effectiveness criteria. As in some other
effectiveness studies (Brookover et al., 1979; Knuver & Brandsma, 1993;
Mortimore et al., 1988; Reynolds, 1976; Rutter et al., 1979), we explicitly
studied not only student achievement, but also noncognitive outcomes. The
mathematics and the language (i.e., Dutch) achievement was measured by
means of curriculum relevant multiple choice tests at the start of the
secondary school and at the end of the ®rst, the second, the fourth, and the
sixth grade. The questionnaire with regard to the noncognitive outcomes
was also administered several times during the students' secondary school
career. This questionnaire touches upon attitudes (towards the school
EDUCATIONAL EFFECTIVENESS IN SECONDARY SCHOOLS
385
environment, towards learning tasks, etc.), motivation, social integration in
the peer group, and the academic self-concept (see Appendix A).
As already mentioned, the LOSO-cohort was followed through secondary
school, but also afterwards. This makes it possible to consider another type of
effectiveness criterion by studying the effects of secondary schools upon
dropout (Rumberger & Thomas, 2000), passing on to postsecondary
education, success in higher education or success at the labour market.
Studies about these postsecondary effectiveness criteria are scarce (BeÂguin,
De Jong, Rekers-Mombarg, & Bosker, 2000; Marsh, 1991). Data about the
students' primary school career were also collected because some school
effectiveness studies indicate that the primary school can have long-term
effects upon achievement in secondary school (Goldstein & Sammons, 1997;
Rasbash & Goldstein, 1994).
ANALYTICAL WORK UP TILL NOW AND OUR
NEW CONTRIBUTIONS
The ®rst research project in which the LOSO database was used, focused upon
the school career in secondary education (Van Damme et al., 1997; Van Damme,
Meyer, De Troy, & Mertens, 2001). About 56% of the variance in the ®nal
position reached in secondary education could be explained in terms of intake
characteristics. Prior achievement was by far the best predictor, but there were
small direct effects of sex (girls outperforming boys), SES, and language spoken
in the family. It is worth mentioning that students from a non-Dutch speaking
family outperform the other students with the same initial status.
Repeating a grade is quite common in Flemish secondary schools.
Although our ®rst analyses indicated rather positive short-term effects on
achievement and well-being of repeating the ®rst or the second grade, later
analyses showed that in the longer term, almost half of the repeaters drop out
early from secondary education.
Our second research project was the study of educational effectiveness in
the ®rst grade (Opdenakker & Van Damme, 2000, 2001). This research
demonstrated that school and class effects with regard to achievement are
much larger than the effects on the students' well-being. It also showed that
some school characteristics are always effective independent of the outcome
criterion, while the effectiveness of other school characteristics depends on the
386
JAN VAN DAMME ET AL.
criterion considered. In addition, this work demonstrated that the school
composition in terms of ability and SES is an important predictor of (math)
achievement, because, among other reasons, aspects of the functioning of
schools are correlated with the school composition.
The composition of schools as well as classes is important again in our
new contributions published in this issue (Opdenakker et al., 2002; Van
Landeghem et al., 2002), in which (math) achievement and noncognitive
outcomes at the end of the second grade are analysed. The two effectiveness
studies have the same sample and method. Mostly the same variables are
examined in the two studies. Therefore, information on the sample, the
method, and the variables is presented in this introduction.
SAMPLE, METHOD, AND VARIABLES
Sample
In this research, we consider only the students who stayed 2 consecutive years
in the general track, the so-called A-stream, and who did not have to retake the
®rst grade: a set of 4,759 students. (In Flanders, about 4% of the students
repeat the ®rst grade of secondary school.) The students considered were
enrolled in the second grade of the A-stream in 1991±1992, grouped in 275
classes in 57 secondary schools.
There were 150 math teachers, so some teachers taught more than one class.
Therefore the data have in fact a four-level structure: individuals within
classes within teachers within schools. For the analyses of mathematics
achievement, the two intermediate levels were combined by a random
selection of one class per teacher (reducing the sample to 2,552 students). So,
we distinguish three levels in the data: the student, the class, and the school
levels. But this class level combines the teacher and the class group. In
contrast with the achievement data, the noncognitive results cannot be
associated with one teacher. We hypothesise that every teacher, whatever the
subject he/she teaches, has a small impact on the noncognitive aspects. Thus,
the noncognitive data have an inherent three-level structure and the
noncognitive outcomes of all 4,759 students are analysed. The sample size
can be reduced throughout the analyses due to missing values on some of the
variables involved.
In the sample, as in Flanders in general, there are more private schools than
public schools, as can be seen in Table 1. Multitrack schools and autonomous
387
EDUCATIONAL EFFECTIVENESS IN SECONDARY SCHOOLS
Table 1. Number of Schools and Students by School Type and Denomination.
PUBLIC
School Type
PRIVATE
Total
Students
Schools
Students
Schools
Students
Schools
ASO
AUTONMIDDLE
MLTLAT
TSO/BSO
298
255
114
77
3
5
4
7
1748
930
680
657
12
7
7
12
2046
1185
794
734
15
12
11
19
Total
744
19
4015
38
4759
57
middle schools (i.e., schools with only a ®rst cycle) prepare for both academic
(or: general) and technical/vocational options in the higher cycles. In
multitrack schools (MLTLAT), most students do not change school after their
second grade. In autonomous middle schools (AUTONMIDDLE), students
have to choose another school after their second grade. ASO-schools are
unitrack schools, offering only the academic (or: general) track. So-called
TSO/BSO-schools offer only the technical and the vocational tracks.
Method
Because of the grouping structure in the data, a multilevel analysis is
necessary (Goldstein, 1995; Kreft & De Leeuw, 1998; Snijders & Bosker,
1999). The MLwiN-software (Rasbash et al., 2000) was used.
The multilevel analysis was performed stepwise. The starting point was an
empty model, without explanatory variables, in which the total variance is
partitioned into a component at each level. In the next step we included
explanatory variables at the student level, thereby controlling for student
intake. By adding student background characteristics, we avoid an overestimation of the importance of the schools and classes due to their selective
entrance.
Once this net effect of schools and classes had been estimated, variables of
the higher levels were added to the model, ®rst the class and teacher
characteristics and secondly the school characteristics, to ``explain'' the class
and school-related variability. This stepwise multilevel analysis distinguishes
the relevant from the irrelevant predictors. Finally, a model with only the
relevant variables was tested. In this ®nal model we examined the possible
existence of random slopes among schools and among classes within schools.
388
JAN VAN DAMME ET AL.
Variables
Student-Level Explanatory Variables
If we want to estimate the effects of particular school and class policies and
practices, and school and class composition, we must include a detailed
description of the body of students entering the schools. Therefore, six
explanatory variables at the individual level were selected, based upon both
educational theory and prior empirical evidence. These are: initial cognitive
ability (COGN), socioeconomic status of the family (SES), achievement
motivation (AM), immunity to stress (STRESSIMM), gender (SEX), and
language spoken at home (DUTCHHOME).
In September 1990, when the students started their secondary education,
®ve tests or questionnaires were administered: the Getlov-battery for intelligence (Lancksweerdt, 1989), school achievement tests for Dutch and
mathematics, a parent questionnaire and a questionnaire on achievement
motivation and fear of failure (or: debilitating anxiety), based on a Flemish
version of the PMT-k (Hermans, 1983). These instruments yielded 15
variables that could be represented by four independent components. The
component ``initial cognitive ability'' is a combination of scores on the
intelligence and the achievement tests at the beginning of ®rst grade. The
measure of the socioeconomic status of the family is a weighted composite of
six indicators: the educational level and the occupation of both parents,
monthly income, and cultural capital of the family. The two other independent
components are the achievement motivation and the immunity to stress. High
scores on this last component indicate low levels of fear of failure, or in other
words: more immunity to stress. Families are also characterised by the
language at home: in some families only the Dutch language is spoken (score
1), in other families also other languages are used (score 0). This variable can
be regarded as a crude indicator of the ethnic background of the family. Most
students who speak another language at home have a Turkish background, and
others a Moroccan or an Italian one. The students' sex was coded ``0'' for boys
and ``1'' for girls.
Class-Level Explanatory Variables
Student-level measures were aggregated and used as descriptive indicators of
the composition of the group of students in the classroom. A mean score is
calculated for each class separately: mean initial cognitive ability (CLCOGN), mean SES (CL-SES), mean achievement motivation (CL-AM), mean
EDUCATIONAL EFFECTIVENESS IN SECONDARY SCHOOLS
389
immunity to stress (CL-STRESSIMM), proportion of girls in the class (CLSEX), and proportion of students who speak Dutch at home (CLDUTCHHOME). The group means are calculated over all students for which
the particular variable is available. The aggregation included all students in a
class and not only those students belonging to the LOSO-cohort. Students with
missing data are mostly omitted from the multilevel analyses, but in the
aggregation process even students with missing values on other variables are
included (see also the recommendation of Snijders & Bosker, 1999, p. 53). On
the other hand, we did not calculate group composition scores that are based
on too small a fraction of the group. If less than 50% of the scores on a studentlevel variable in a class was available, the aggregated score for that class was
not calculated. This procedure is expected to reduce the overall measurement
error on the independent variables.
The mathematics teachers were the main source of information about
educational processes employed by Opdenakker et al. (2002) and Van
Landeghem et al. (2002). The teachers described their class groups on
different aspects. This description is characterised as the learning climate
(LEARNCLIM). It is the main component of four scales indicating the extent
to which the class group is a calm (7 items, ˆ 0:89), a study-oriented (4
items, ˆ 0:87), and a cohesive (6 items, ˆ 0:77) group of which the
teacher has high expectations (9 items, ˆ 0:91). On the other hand, the
teachers were asked to give a description of their teaching practice. The effect
of the following variables was explored: focus on individual development
(INDDEV, 7 items, ˆ 0:63), special attention to low achievers (ATTLOW, 1
item) and special attention to high achievers (ATTHIGH, 1 item), and
feedback on study results (FEEDBACK: individual feedback, 1 item;
feedback in group, 1 item). The variable describing the consultation between
teachers (CONSULT) is a higher order combination of consultation on
students (3 items, ˆ 0:76) and consultation on teaching methods (4 items,
ˆ 0:82). Two additional variables measure the degree of structured teaching
(4 items, ˆ 0:76) and proportion of intellectually challenging questions in a
regular class test (INTELTEST).
The content validity of the achievement test for mathematics was assessed
by teacher ratings of the extent to which students have had the opportunity to
learn the content represented in the individual test items. A test item is scored
``1'' by the mathematics teacher when the item is not covered in the
curriculum. A score of ``2'' refers to items that students should be able to solve
on the basis of the content covered, although the formulation of the item
390
JAN VAN DAMME ET AL.
differs from the usual presentation in the class. A score of ``3'' indicates that
the item is a typical question for the students in the class. This item could have
appeared in a regular examination. For every class, the mean of the item scores
was calculated (OPPM, opportunity to learn mathematics), indicating the
degree to which the content of the achievement test at the end of the second
grade was covered during the school year.
School-Level Explanatory Variables
As we mentioned above, the school type refers to the study programmes
offered by the school (see Table 1). Multilateral and middle schools offer
general, technical and vocational secondary education. These multilateral and
middle schools are compared with schools that offer only general or only
technical and vocational education. Also, private (catholic) schools are
compared with public schools.
A similar technique of calculating means of student characteristics as
described for the class level, was used to describe the student population of a
school. The averages of, for example, initial cognitive ability, SES, and
achievement motivation were derived. The proportion of girls within the
school is another group composition characteristic that was included in the
multilevel analysis.
The educational process variables at the school level are based upon
information from different sources: students, teachers and school heads. At the
end of the ®rst grade, a school environment questionnaire was administered to
the students. And in every school, a representative sample of 15 teachers in the
®rst cycle completed a school characteristics questionnaire. The following
school variables were constructed using the answers of this sample of
teachers: orderly learning environment in the classes (ORDLEARN, 6 items,
ˆ 0:74), the use of test results to improve teaching (USERESULT, single
item), and the extent to which the school is characterised by formal structures
and regulations (STRUCT&RULES, 11 items, ˆ 0:69). The heads
described their schools on several aspects of school life, including (secondorder variables): student coaching (COACHING, parent meetings and
counselling on subject choices) and attention of the school head to
pedagogical aspects (HEADPED). (The variables COACHING and
HEADPED are components based on a number of single items and three
scales with 's ˆ 0:75, 0.80 and 0.84.) The perceptions of the students
resulted in six scales, with -coef®cients between 0.72 and 0.92. Combining
the descriptions of both students and teachers by means of principal
EDUCATIONAL EFFECTIVENESS IN SECONDARY SCHOOLS
391
component analysis, four additional school variables were constructed:
attention towards differences between students (ATTDIFF), focus on
discipline and subject matter acquisition (DISC&SUBJ), an evaluation of
the functioning of the school by the teachers (FUNCT_T) and by the students
(FUNCT_S).
School-level variables were also constructed by aggregating some of the
class-level variables. The aggregations yielded the following school variables:
average level of focus on individual development (S-INDDEV), average level
of special attention to high- and low-achieving students (S-ATTHIGH, SATTLOW), average level of consultation between teachers (S-CONSULT),
average level of feedback on study results (S-FEEDBACK), and average level
of opportunity to learn (S-OPPM). Since the variables S-ATTHIGH, SATTLOW and S-INDDEV were highly correlated, they were combined into
one variable: attention to individual students (S-ATTINDSTUD).
SECONDARY EDUCATION IN FLANDERS
Since the educational reform in September 1989, there is a uniform structure
in Flemish secondary education. Six grades are grouped into three cycles (of
two grades), as can be seen in Figure 1. The ®rst cycle is rather comprehensive. In the ®rst cycle, the majority of the students follow the general track,
called the A-stream. In the ®rst grade of the A-stream, a limited number of
hours per week is devoted to optional subjects. Students with learning
dif®culties take the B-stream where they receive education at pace with their
ability. In the second grade of the A-stream, students can make a subject
choice for 5 to 7 hr a week. These choices can be grouped into four groups:
classical languages (CL) with Greek and Latin, general subjects (GS),
technical-theoretical options (TECHN_T), and technical-practical options
(TECHN_P).
From the third grade on, four different categories of study programmes are
distinguished, namely academic or general (ASO), technical (TSO), artistic
(KSO), and vocational secondary education (BSO). The general track
emphasises academic education and prepares for higher education. The
technical track contains theoretical and technical training. With a TSOdiploma the student can enter the job market or higher education. The artistic
secondary education combines general education with active practice of art.
Higher education and entering the job market are both possible with a KSO
392
JAN VAN DAMME ET AL.
Fig. 1. Secondary education in Flanders.
diploma. The vocational track concentrates upon practical education and
prepares the student to a speci®c vocation. Nevertheless, also many of the
BSO-students are allowed, after having ®nished a seventh grade, to enter
higher education.
Multitrack schools are comprehensive schools that offer both general and
technical/vocational education, other schools have a more limited programme.
Only a small number of schools offer artistic education. A distinction can be
made between schools that organise only the ®rst cycle, schools with only the
second and third cycle, and schools with all six grades. Public schools in
Flanders have a slightly different curriculum than private (mostly catholic)
schools. The majority of the schools are catholic schools and these receive
almost the same amount of government funding as the public schools. The
autonomy of schools in Flanders is large. For example, the central administration does not organise any exam. The educational system has always been
characterised by a free school choice.
EDUCATIONAL EFFECTIVENESS IN SECONDARY SCHOOLS
393
CONCLUSION
We have provided some information about a new study concerning educational
effectiveness in secondary schools in Flanders (Belgium). In particular, we have
described the sample and a selection of variables. We have explained the
objectives, guided by the international school effectiveness research, on which
the data acquisition design was based and have referred to some of the research
results that have already been reported. We also presented an outline of the
Flemish system of secondary education. This introductory information makes it
possible for the following contributions by Opdenakker et al. (2002) and Van
Landeghem et al. (2002) to be focused on the results of the analyses.
ACKNOWLEDGEMENTS
Acknowledgements to the Department of Education of the Ministry of the Flemish Community
for funding the project, to the reviewers for careful reading and helpful comments, and to all the
former and current members of the LOSO-team for their ceaseless effort to build and
supplement the database.
REFERENCES
BeÂguin, A.A., De Jong, T., Rekers-Mombarg, L.T.M., & Bosker, R.J. (2000). Het externe
rendement van het voortgezet onderwijs [The external ef®ciency of secondary
education]. Enschede, The Netherlands: Twente University Press.
Brookover, W., Beady, C., Flood, P., Schweitzer, J., & Wisenbaker, J. (1979). School social
systems and student achievement: Schools can make a difference. New York: Praeger.
Creemers, B.P.M. (1994). The effective classroom. London: Cassell.
Goldstein, H. (1995). Multilevel statistical models. London: Edward Arnold.
Goldstein, H., & Sammons, P. (1997). The in¯uence of secondary and junior schools on sixteen
year examination performance: A cross-classi®ed multilevel analysis. School Effectiveness and School Improvement, 8, 219±230.
Hermans, H.J.M. (1983). Prestatie Motivatie Test voor Kinderen [Achievement motivation test
for children]. Lisse, The Netherlands: Swets & Zeitlinger.
Hill, P.W., & Rowe, K.J. (1996). Multilevel modelling in school effectiveness research. School
Effectiveness and School Improvement, 7, 1±34.
Janssen, P. (1982). Vragenlijst studiebeleving [Study experience questionnaire]. Leuven,
Belgium: K.U. Leuven, Afdeling Psychodiagnostiek en Psychologische Begeleiding,
Centrum voor Schoolpsychologie.
Knuver, A.W.M., & Brandsma, H.P. (1993). Cognitive and affective outcomes in school
effectiveness research. School Effectiveness and School Improvement, 4, 189±204.
394
JAN VAN DAMME ET AL.
Kreft, I., & De Leeuw, J. (1998). Introducing multilevel modeling. London: Sage.
Lancksweerdt, P. (1989). Getlov: Gemeenschappelijke Testbatterij Lager Onderwijs OostVlaanderen [Common Test Battery Primary Education East of Flanders]. Deinze,
Belgium: Vrij P.M.S.-centrum 1.
Marsh, H.W. (1991). Failure of high-ability high schools to deliver academic bene®ts
commensurate with their students' ability levels. American Educational Research
Journal, 28, 445±480.
Mortimore, P., Sammons, P., Stoll, L., Lewis, D., & Ecob, R. (1988). School matters: The junior
years. Somerset, UK: Open Books.
Opdenakker, M.-C., & Van Damme, J. (2000). Effects of schools, teaching staff and classes
on achievement and well-being in secondary education: Similarities and differences
between school outcomes. School Effectiveness and School Improvement, 11,
165±196.
Opdenakker, M.-C., & Van Damme, J. (2001). Relationship between school composition and
characteristics of school process and their effect on mathematics achievement. British
Educational Research Journal, 27, 407±432.
Opdenakker, M.-C., Van Damme, J., De Fraine, B., Van Landeghem, G., & Onghena, P. (2002).
The effect of schools and classes upon mathematics achievement. School Effectiveness
and School Improvement (this issue).
Rasbash, J., Browne, W., Goldstein, H., Yang, M., Plewis, I., Healy, M., Woodhouse, G.,
Draper, D., & Lewis, T. (2000). A user's guide to MLwiN. London: Institute of
Education, Multilevel Models Project.
Rasbash, J., & Goldstein, H. (1994). Ef®cient analysis of mixed hierarchical and crossclassi®ed random structures using a multilevel model. Journal of Educational and
Behavioral Statistics, 19, 337±350.
Reynolds, D. (1976). The delinquent school. In P. Woods (Ed.), The process of schooling.
London: Routledge and Kegan Paul.
Reynolds, D., Teddlie, C., Creemers, B.P.M., Cheng, Y.C., Dundas, B., Green, B., Epp, J.R.,
Hauge, T.E., Schaffer, E.C., & String®eld, S. (1994). School effectiveness research: A
review of the international literature. In D. Reynolds, B.P.M. Creemers, P.S. Nesselrodt,
E.C. Schaffer, S. String®eld, & C. Teddlie (Eds.), Advances in school effectiveness
research and practice (pp. 25±51). Oxford: Pergamon.
Rumberger, R.W., & Thomas, S.L. (2000). The distribution of dropout and turnover rates
among urban and suburban high schools. Sociology of Education, 73, 39±67.
Rutter, M., Maughan, B., Mortimore, P., Ouston, J., & Smith, A. (1979). Fifteen thousand
hours: Secondary schools and their effects on children. Cambridge, MA: Harvard
University Press.
Scheerens, J. (1992). Effective schooling: Research, theory and practice. London: Cassell.
Scheerens, J., & Bosker, R.J. (1997). The foundations of educational effectiveness. Oxford:
Elsevier Science.
Smits, J., & Vorst, M. (1982). Schoolvragenlijst voortgezet onderwijs [School questionnaire
secondary education]. Nijmegen: Berkhout Nijmegen.
Snijders, T.A.B., & Bosker, R.J. (1999). Multilevel analysis: An introduction to basic and
advanced multilevel modeling. London: Sage.
Stoel, W. (1980). De relatie tussen de grootte van scholen voor voortgezet onderwijs en het
welbevinden van leerlingen [The relationship between school size and well-being of
pupils in secondary education]. Haren: RION.
EDUCATIONAL EFFECTIVENESS IN SECONDARY SCHOOLS
395
String®eld, S., & Teddlie, C. (1990). School improvement efforts: Qualitative and quantitative
data from four naturally occurring experiments in phases III and IV of the Lousiana
School Effectiveness Study. School Effectiveness and School Improvement, 1, 39±66.
Teddlie, C. (1994). The integration of classroom and school process data in school effectiveness
research. In D. Reynolds, B.P.M. Creemers, P.S. Nesselrodt, E.C. Schaffer, S. String®eld,
& C. Teddlie (Eds.), Advances in school effectiveness research and practice (pp. 111±
132). Oxford: Pergamon.
Teddlie, C., & Reynolds, D. (2000). The international handbook of school effectiveness
research. London: Falmer Press.
Van Damme, J., De Troy, A., Meyer, J., Minnaert, A., Lorent, G., Opdenakker, M.-C., &
Verduyckt, P. (1997). Succesvol doorstromen in de aanvangsjaren van het secundair
onderwijs [Successful passing through the ®rst years in secondary education]. Leuven,
Belgium: Acco.
Van Damme, J., Meyer, J., De Troy, A., & Mertens, W. (2001). Succesvol middelbaar
onderwijs? Een antwoord van het LOSO-project [Successful secondary education? An
answer of the LOSO-project]. Leuven, Belgium: Acco.
Van Landeghem, G., Van Damme, J., Opdenakker, M.-C., De Fraine, B., & Onghena, P. (2002).
The effect of schools and classes on noncognitive outcomes. School Effectiveness and
School Improvement (this issue).
396
JAN VAN DAMME ET AL.
APPENDIX A
The Loso Well-Being Questionnaire
The scales and/or 104 ®ve-point items of the ``well-being questionnaire'' have
been derived from the ``Schoolvragenlijst voortgezet onderwijs'' of Smits and
Vorst (1982), a questionnaire by Janssen (1982) and Stoel's (1980) ``academic
self-concept'' scale. Table A1 lists the eight scales on which the study of Van
Landeghem et al. (2002) is based. (More information with regard to the
construction of the scales is provided in that text.)
Table A1. The Eight Scales Derived From the Well-Being Questionnaire.
Interest in learning tasks (INTERLT, 8 items, ˆ 0:88)
± I enjoy doing most of the subjects in this school.
± To me, many things we have to learn in school are unimportant. (±)
± I think that I learn useful things in school.
± I am really interested in most of the subjects.
± I think it's great that I learned all sorts of things this year.
± I think that most of the subjects we are taught are very worthwhile.
± I think that I have to learn things in school that I won't ever need in future. (±)
± Personally, I ®nd the subject matter usually interesting.
Relationship with teachers (RELTEACH, 10 items, ˆ 0:88)
± I think that most of the teachers are very helpful when I have problems with the school
work.
± Some teachers are kinder to others than to me. (±)
± I feel at ease with most of the teachers.
± There are few teachers who help me well with my school work. (±)
± There are enough teachers who listen patiently when I ask something.
± I get on well with most of the teachers.
± There are few teachers who understand me. (±)
± Some teachers don't have the patience to explain things to me. (±)
± The teachers dislike me. (±)
± Most of the teachers treat me in a nice way.
Well-being at the school (WELLBS, 4 items, ˆ 0:86)
± I am glad to go to this school.
± I think it's nice at school.
± If the choice was mine, I would rather go to another school. (±)
± If we were to move to another neighbourhood, I would prefer to stay at this school.
Attentiveness in the classroom (ATTENTCL, 10 items, ˆ 0:89)
± I ®nd it dif®cult to keep my mind on my work during a whole lesson. (±)
± In class I am often thinking about things that have nothing to do with the lesson. (±)
± I often miss part of what has been said in class. (±)
EDUCATIONAL EFFECTIVENESS IN SECONDARY SCHOOLS
397
Table A1. (Continued).
±
±
±
±
±
±
±
In most lessons I pay attention well.
I am easily distracted in class. (±)
I usually listen carefully when the teacher explains something.
I can easily keep my attention on the work during the whole morning.
I am often daydreaming in class. (±)
When I have to carry out a task in class, I can keep my thoughts on it.
I am often chatting in class. (±)
Motivation towards learning tasks (MOTLT, 5 items, ˆ 0:82)
± There are few subjects for which I really do my best. (±)
± For some subjects I could work much better than I do now. (±)
± I think that I rarely do my best at school. (±)
± I work hard for all subjects to get good results.
± I really do my best at school.
Attitude to homework (ATHOMEW, 5 items, ˆ 0:82)
± When I have homework, I put it off for as long as possible before I start. (±)
± When I have homework, I start as soon as possible.
± I usually start doing my homework of my own accord.
± When I want to do something nice, I still complete my homework ®rst.
± At home, I only start doing my homework when I am told to do so. (±)
Academic self-concept (ACSELFC, 9 items, ˆ 0:80)
± I think I am able to deal with the subject matter.
± I fear that I will fail the exams at the end of the year. (±)
± I am usually slower at digesting the subject matter than my classmates. (±)
± I think that I am good at learning.
± My classmates are better at learning than me. (±)
± I usually ®nd the homework quite easy.
± When I have studied something, I sometimes feel that I can't tell much about it. (±)
± When I take an exam, I usually feel that I am up to it.
± I can keep up well with the pace of the lessons.
Social integration in the class (SOCINTCL, 10 items, ˆ 0:89)
± In our class I feel that I am rather outside the group. (±)
± I think that most of my classmates treat me in a nice way.
± I have few friends in this class. (±)
± I feel at ease with my classmates.
± I often feel lonely in the class. (±)
± There are enough classmates who help me when I ask them to do so.
± I ®nd few of my classmates really kind. (±)
± I get on well with my classmates.
± I quite easily make friends at school.
± I am often teased by the other students. (±)
Note. The symbol (±) indicates items with a negative contribution to the scale.