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On the development of educational policies
European Journal of Operational Research 82 (1995)409-421 North-Holland
409
Theory and Methodology
On the development of educational policies L. V a l a d a r e s
Tavares
CESUR-IST, Av. Rovisco Pais, 1000 Lisbon, Portugal Received March 1992; revised October 1992 Abstract: The development of educational policies is studied in this paper using the system approach. The most promising areas for application of O R in policy design and evaluation are identified and discussed in terms of illustrative data taken from several countries, namely member states of the European Community. Keywords: Policy design; Evaluation; Education
1. Introduction During the last decades, the importance being given to issues and policies concerning a macrolevel of decision is growing in most industrial societies. This level is defined as opposed to the micro-level which is traditionally associated to the firm, the family or the individual. The macro-level includes not just the national or multi-national cases but also the regional or sub-regional systems as well as economic sectors or social classes and groups. The inclusion in the same system of a large number of decision-makers with different values and objectives may be considered as one of the most specific features of this level of analysis. Recently, the role of O R as a decision-aid has been enhanced but most of the published literature concerns with theoretical models or applications carried out at the micro-level. Few applications of O R tools to support decision-making at more aggregated levels of analysis and decision can be quoted despite the usual praise given to
Correspondence to: Prof. L. Valadares Tavares, CESUR-IST Av. Rovisco Pais, 1000 Lisbon, Portugal.
the supportive role of O R for macro policy making whenever its nature or future is discussed. The educational sector is, no doubt, a good example of an important sector of activity with complex and difficult policy making issues (Smith, 1971) which have recently received very little attention by the O R community (Lesourne, 1988). In this paper, the potential of O R to support policy making in education is studied. The contributions of O R can be particularly useful for systems modeling, policy design and policy evaluation. These lines are discussed in terms of recent developments taking place in Portugal and in other countries, some of them belonging to the EC.
2. The educational system The educational sector of most countries is a complex and important part of their cultural, political, social and economic structures (Banks, 1987). The complexity of this sector is a direct result of being the outcome of historical processes where
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L. Valadares Tavares / On the development of educational policies
410
Table 1 Education as a sector of activity (EEC countries, 1988) a
B
Average percentage 1) 5 - 2 4 year old population 2) 5 - 2 4 age-group
VW-II
[]I.
25% Minimum: 18% ( F R G ) Maximum: 36% (Republic of Ireland) I
Participation in education (5-24 year old) Labour force in education (as a percentage of the total labour force) G D P devoted to education
80% 4% Minimum: 2% (Spain) Maximum: 10% (Belgium)
13 - Compulsory
}
, . l'm - Primarylevel e~ucation~_B2- Lower secondary level
FCI -general C - Upper secondary education].(2 -Vocational
6%
a Using data from O E C D (1991).
[Dt - Higher education(Universitylevel) D - Post secondary education ~ 132- Higher education(Politechniclevel)
[.D3 - Highervocationaleducation
private and public actors interacted during several centuries with a wide diversity of values and objectives (Gal, 1987). This explains the strong diversity of features exhibited by present educational systems even within groups of countries belonging to the same community as it is the case of E E C Member States. The importance of each educational sector is not just due to its role of developing the system of values, knowledge and skills of each new generation but also due to its political social and economic features. Usually, as it is shown in Table 1, more than 20% of the population is directly involved in this sector as clients (students) and no less than 4% of the active population works for this sector. This sector is one of
g - Continouslong - life education Figure 1. Major components of the education system
the largest consumers of public expenditure in a permanent and strong competition with two other sectors: health and defence. Each educational sector includes a wide variety of levels, institutions, programs, certificates and activities (Rassekh et al., 1987) but its major components are identified in Figure 1. The extension of each one depends not just on the demographic structure of the population but also on the stage of development of the whole society.
Table 2 Duration of education periods in E E C Year of education 1 Minimal age 4 Belgium Denmark FRG France Greece Ireland Italy Luxembourg Netherlands Portugal Spain United Kingdom P: Primary. 1: Lower secondary. 1I: U p p e r secondary.
5
P
P
2
3
4
5
6
7
8
9
10
11
12
13
6
7
8
9
10
11
12
13
14
15
16
17
18
19
P P P P P P P
P P P P P P P
P P P P P P P
P P P P P P P
P P P P P P P
P P 1 I P P I
1 I 1 I I I I
I 1 1 II I I I
11 I I 11 I I II
II I I II 11 II 11
11 11 11 II II II II
11 11 11 II II
II II II
II II II
II
P P P P P
P P P P P
P P P P P
P P P P P
P P P P P
P, P P I I
1I I I I I
1I II I I I
11 II I II I
II II I1 I1 I
11 II 1I 11 II
11 II I1 I1 II
II II
II II
L. Valadares Tavares / On the development of educational policies
Under-developed countries have short periods of compulsory education (e.g., 3 or 4 years) as opposed to the most advanced societies where no less than nine or ten years of schooling is imposed (see Table 2, from Derenbach, 1990). Industrial countries enhance the role of the vocational stream within the upper secondary education in contrast with more traditional and landbased economics where the percentage of students following such option is low as it is the case of southern Europe (see Table 3, from Derenbach, 1990). Pre-school education has initially been developed to allow both parents having a job but it can also play a key role to compensate depressed social backgrounds. Higher education can embrace more than 20 or 30 percent of the age group of 20-24 year olds in more modern societies and then the degree of its diversification is also higher. The average composition of EEC students is presented in Figure 2. Technological progress is responsible for longer leisure periods in the working population and for a faster rate of obsolescence of human knowledge and skills. These two combined effects can explain the increasing importance of the role played by long life education whenever technology leads a process of development (Kairamo, 1989). Despite all these differences, it seems that two paradigms are generally accepted for this sector (UNESCO, 1982): • The educational activities should be oriented to contribute to the full development of each person according to the values, the goals
Table 3 Percentage of students in level II of secondary education following vocational programs (EEC countries, 1988) Country
Percentage
14 - 15 17 - 18
5-6
12% Pre-primary
411
44%
34%
[
I
Primary
Secondary
Lower Secondary
III
year old
10% Te/~ ary
level
Upper Secondar
Compulsory --- ( Higher f General ----------~..~Education "1 / - [ Advanced kVocational ~ L Vocational Figure 2. Distribution of students in EEC (using data from (OECD, 1991)
and the needs accepted and perceived by each society. • The components of the educational sector should be harmonically and consistently interconnected in order that each individual can select the most appropriate path for hi s/ her education and training. These two paradigms are the logical basis for considering the educational sector as a system (Lazlo, 1983): the educational system. Therefore, important efforts to apply the systemic approach to education have been made since the early sixties (Churchman, 1964; Shepard, 1965) but unfortunately little attention is being given to this line of research during the last decade. However, the contribution of OR can be particularly relevant in two areas which are critical for the development of educational policies: a) the modeling of the educational system; b) the design and the evaluation of policies.
Group 1: Italy Netherlands FRG France UK Denmark Spain
64 62 60 46 46 39 37
Group 2: Greece Ireland Portugal
27 13 7
3. Modeling the educational system The most general and basic model of any educational system is presented in Figure 3 where major flow-variables are identified and defined (Tavares, 1991). This 'black-box' model can be applied to the overall sector or just to sub-systems such as a region, a school or a course.
L. Valadares Tavares / On the development of educationalpolicies
412
................................
'R
F
,
i
[
I
x . _ ...._....a. . . . . . . . . . . . ~ i~~::~i~ .: 7~i::#::
................
~::~ '::~.,
~ # ~~~~
.................................................
j
studeaats flows B
.
Infra-structures (Buildings, ere)
......... in~orrmtion flows
C
-
System's control
.....
E
Expectations
ED -
NO-
Effective d e m a n d (students)
resource* flows
Outputofnon-succeededstudents
N O = D + FO
b'D - S t u d e n t s w h o failed entering into the system F
-
Financial resources devoted to Education
/-[
-
H u m a n resources
I
-
Effective i n p u t o f s t u d e n t s
L
_
Lost potencial d e m a n d
where D = drop-outs and F O = Students without success 0 Output of well succeeded students PD
-
Potencial d e m a n d (students)
Q
.
C o n t e n t s quality
R
Finances d e v o t e d to e d u c a t i o n a l resources
S MQ -
Social s u p p o r t allocated to s t u d e n t s
M o n i t o r e d q u a l i t y of the
educational systems
T
.
T e a c h i n g aids a n d t e c h n o l o g y
Figure 3. The basic model of the educational system
The simulation of the process within the box is usually carried out in terms of a two-dimensional chain model describing the students flows along the succession of grades and academic years as it is presented in Figure 4. F r o m past data, the probabilities d~(i), d~(i) and s(i) can be estim a t e d (see, e.g., U N E S C O , 1981) and hence the propagation of a population along the system can be easily simulated. The state equations can be easily deduced:
X ( i , t) = S ( i - 1, t - 1 ) [ 1 - d s ( i -
+F(i, t -
Figure 4. The chain model of an educational system
x(i, t) = N u m b e r of students at grade i and academic year t.
s(i, t ) = N u m b e r of students flowing from i to i + 1 during the transition from year t to year t + 1. F(i, t ) = N u m b e r of students flowing from i to i + 1 during the transition from year t to year t + 1. Obviously, Markov chain models can also be built and their application is particularly useful if the stationarity of the process is acceptable (see, e.g., Correa, 1963).
1)]
1)-[1 -d~(i)],
F ( i , t) = X ( i , t ) [ 1 - s ( i ) ] , S(i, t) = X ( i , t ) ' s ( i ) , O(i, t) =
D'(i-
1, t)
+ D"(i, t)
S(i- 1, t).ds(i - 1)
with:
F(i, t).dr(i)
d~(i) = Probability of dropping out for a student who passed at grade i.
dr(i) = Probabifity of dropping out for a student who failed at grade i.
s(i) = Probability of passing for a student at grade i.
Figure 5. Resources analyses
L. Valadares Tavares / On the development of educational policies
A second stage of analysis oriented to estimate the needs of resources can be then started. Another simulation model can be built following the structure presented in Figure 5. Particular attention should be given to the spacial distribution of the educational system as it always has to be widely spread all over the country. The network of schools for compulsory education should also cover low density areas which implies having a very low number of students per school. This difficulty arises in many European regions (e.g, Scotland, Wales, hinterland of Portugal, some central areas of France, northern areas of Scandinavia, Southern Italy, etc.) and for instance, in Portugal, about 10% of the primary schools have less than ten students (Tavares, 1991). The well developed set of OR techniques to study distribution and routing problems can help improving the network of schools and the transportation systems adopted to collect and to take back home their students (see, e.g., Foyer et al., 1967). The interactions between the educational system and the external world deserve capital attention as the system 'belongs' to society and it is supposed to contribute to its development (Figure 6). Three major areas of modeling can be described: A. The relationship between the students choices or performances and their social or economic origins.
413
Private
Public ,~ourc~
/kt
Families
Enterprises
Regions
support
Figure 6. Relationship between education and society
B. The relationship between the educational attainment and the professional success/reward. C. The contribution of education to the social and economic development.
Table 4 Educational success in terms of social-economic background Social-economic level of the student's father
Non-skilled worker Skilled worker • agriculture • industry Liberal professional Middle m a n a g e r Top m a n a g e r
Portugal 8 9 / 9 0 (using data from Tavares, 1991) Percentage of students at 6th grade without having failed any academic year
Fraction of the best score
53% 56% 69% 76% 72% 87%
Netherlands for students born around 1978 (using data from M V O W , 1989) Academic level of results at the end of primary education
Fraction of the best score
0.61 0.64 0.79
2.65 3.09
0.75 0.87
0.87 0.83 1.00 M a x - Min = 0.39
3.0 3.35 3.55
0.85 0.94 1.00
M a x - Min = 0.25
L. Valadares Tavares / On the development of educational policies
414
Skill score
1%
Ymr19~7 S%
i ~
M~ ,~i~::i!::
Ym'~ 11%
term of the number of years spent in school which can be considered as the accumulated human capital (see Schultz, 1960, and Machlup, 1984). The internal rate of return of the investment defined by an additional year of study can be estimated in terms of the corresponding increase of wages (receivals) and of the lost wages plus study costs (expenses). The third line of research has studied the impact of education on the economic development and it was started by the pioneering work of Schultz (1963) in the USA and of Tinbergen et al. (1965) in Europe.
4. Policy - m a k i n g in e d u c a t i o n
4.1. Policy aims
0
Sta~s'dcaldi~bu~on
Figure 7. Forecasted skills rating for USA (in RAJAN, 1990)
The first topic was addressed by many authors (see Tawney, 1956, Coleman, 1966, and Husen, 1986) and it seems that a rather significant relation can be estimated using a multivariate statistical model explaining the success of a student at year t in terms of the social-economic level of his parents and of their achievements before t. The contribution of the first factor is much higher in more heterogeneous societies (Cherkaoui, 1979) than in the less stratified ones as it is well examplified for Portugal and the Netherlands in Table 4. The second topic has been subject to intensive analysis with the purpose of closing the gap between the contents of education and the future society needs expressed in terms of the required skills (as an example, a forecasting analysis developed for USA is included in Figure 7, from Rajan, 1990). Modeling the contents of education to fulfill the new needs has also been studied by E E C as it is presented in the well known I R D A C report (IRDAC, 1991) and by O E C D (OECD, 1992). Another area of modeling about this second topic has been oriented to study the wages in
Despite the diversity of cultural traditions, ethical standards and political systems, it seems that most societies are giving priority in education to three major aims: accessibility, quality and efficiency. Accessibility implies not just easy systems to participate in the educational system but also favourable cultural, social and economic conditions supporting the generation of demand for education. This aim can be particularly difficult to achieve in more depressed regions or social classes where short term economic needs receiver a stronger priority. Quality is a key paradigm for any educational activity but its definition is always controversial and complex. This concept can be formulated along three different criteria: quality of the goals assigned to each educational program, quality of its contents and quality of the processes adopted to implement such program. The quality of the goals should reflect their social and economic utility as it is important that the needs of each society will be fulfilled by its educational system. The contents has to be adequate for the selected goals and it should have cultural, scientific and technical quality. The adopted educational process should have pedagogic quality using the most appropriate tools and paths to motivate the students and to improve their results. These three perspectives on quality should be applied to the transformations induced in the
415
L. Valadares Tavares / On the development of educational policies
students by education in order that the overall level of quality will be estimated. Such level is the added value generated by education and it should be not identified with the academic results achieved by t h e students as they do not take into account their initial state. This means that the added value generated by a school receiving students from a deprived background and obtaining low academic results can be higher than that created by a school serving high income students and achieving high results. Obviously, the multi-criteria modeling (Roy, 1985) can contribute to the formulation a n d the estimation of the quality levels. Efficiency is another key paradigm in education and it is a source for permanent debate. This concept can be defined in terms of the ratio between the o u t p u t of education and all the inputs devoted to its activities. The quantitative estimation of the output implies the application of the multi-criteria approach to the assessment of the transformations
generated by education which is not an easy task. On the other hand, the estimation of the inputs is also far from trivial because it requires a model to estimate the allocation of resources to each activity. This explains the controversial nature of any attempt to assess the efficiency level of each educational system. 4.2. Decision-makers
The processes of intervention to develop educational systems have to consider the different classes of decision-makers and their decision levels (Tavares, 1991). A taxonomy is presented in Table 5, showing that: • the number and the diversity of decisionmakers are quite high; • the strategic and the tactical levels should not be restricted to higher authorities but should also be present in decision-making by schools and associations;
Table 5 A taxonomyof decision-making in education Classes of decision-makers A. International authorities
Decision level Strategic
Joint policies (quality; access; mobility) B. National authorities National policies (curriculum; resources; staff; social support) C. Regional/local authorities Regional/local issues (school development, fund raising, students suppor0 D. Schoolsmanagers, teachers, Schoolplanning students, parents,...) E. Unions (teachers, and Careers negotiation non-teaching staff) and recognition F. Association Participation in • Parents decision-making • Students G. Suppliers of schools National and regional • Buildings programs • Teaching aids (books, videos,. ;. ) • Equipment (labs, computers.... ) • Distribution • Transportation
Tactical International programs
Operational Funding; Recognitionsystems
Budgeting; rules: incentives
Monitoring control
Resources allocation
• Personnel management • Supplies • Transportation
School programmingand assessment Initial and continuous training
School management Teaching conditions
School-familyrelations and youth activities
School management
Designing Tendering Scheduling
Operations
416
L. Valadares Tavares / On the development of educational policies
UnJt~Stat~s ~
~
s..°
~
C.mt~llutho~tl~
I--1
'Italy ~ijiiii:i::ii:!i!ii !!~!iiiJiiiii Figure 8. Distribution of responsibilities within the educational system(in OECD, 1991)
• the achievement of specific goals implies setting up principles guidelines, rules and incentives to lead all classes of decision-makers to select alternatives producing results consistent with such goals; • the design and the assessment of policies should consider the diversity of decision-makers and of levels of decision. Obviously, the distribution of responsibilities and of the type of decision-making among these actors varies substantially between countries as it is shown in Figure 8. 4.3. Policy analysis and design
Modern democracy emphasises the moral duty of any society to offer equal opportunities of education to any citizen which explains that the development of educational subsystems devoted to specific groups based on social privileges has become undesirable. The process of offering equal opportunities implies banning discriminatory rules and economic obstacles. The main approach to fight these obstacles has been to provide 'free education' which means, in economic terms, edu-
cation supported by the public (central, regional or local) budget. In some countries, namely in latin Europe, this policy gave to the central power the roles of owner and manager of the whole network of schools producing a very uniform supply of education. Often, this policy has been responsible for the adoption of the same rigid curriculum, textbooks and exams all over each country. This solution was initially considered very favourable as a guarantee of an equalitarian policy but it has been shown that such uniformity does not respect the natural diversity of groups and individuals generating higher rates of dropout and failure in individuals with different goals and motivation scales. Furthermore, societies respecting the pluralism of values should respect the right of each family to choose the type and the style of education which requires a diversified supply of education without economic discrimination. This target implies a system of cost compensation whenever education is not publicly operated. Also, offering equal opportunities has been initially considered equivalent to the supply of education under the same conditions to all the different social and economic groups. However, there is now full evidence that more favourable conditions should be offered to the more depressed groups if the goal of equal opportunities is kept (positive discrimination). The policies designed to improve the access can be expressed in terms of variables already defined for the general model of the educational system (Figure 3). Improving the access means increasing E D / P D in terms of the youth expectations (E), of the social support (S) and of the attractiveness of the educational system which is a function of the quality of the contents (Q) and of the resources allocated to this system (B, T, H). Usually, the design of a policy to improve accessibility implies initiatives along these three action lines (expectations, improvement of the educational system and social support) but the relative importance given to each component should be defined in terms of the most crucial obstacles identified in each specific situation. The generation of a stronger motivation towards education can be a critical factor either in less developed regions where youths do not frequently meet more educated people or in highly developed
417
L: Valadares Tavares / On the development of educational policies
areas where the expected increase of salary due to further education is small. In any case, mass media campaigns and the circulation of information about jobs and careers can be invaluable instruments to increase the level of expectations. Obviously, this action line is also directly associated to the achievement of a higher level of adequacy of the educational contents to the needs and interests of potential students. This can be the results of a strategy searching for a higher quality teaching-learning process as well as for a m o r e flexible and diversified supply of education. The quest for quality (OCDE, 1987) implies p e r m a n e n t systems to adapt the educational goals to the society needs and to monitor the quality of the educational programs (contents and processes). This means that dosing the gap between education and society can never be considered as a settled problem and that the quality of the educational results should be continuously estimated and assessed. Initiatives including representatives of enterprises and of academic institutions can help to adapt the educational goals to the society needs as it is described by (1991) and E E C (1992). The comparative assessment of the knowledge acquired by students in different countries can be
Figure 9. Percentage of correct answers in mathematics (populations for 13 year students; using data from IAEP, 1992)
Table 6 Budget allocation in educational systems (1988) a % % salaries capital Portugal France Luxembourg UK Canada Netherlands Spain Austria Japan
80.1 75.1 71.9 68.4 63.6 60.0 59.9 59.7 52.1
9.1 6.7 14.0 3.9 7.5 9.1 11.4 9.0 16.8
a Using data from OECD (1991).
also a key factor to improve the quality in each system. Institutions such as the International Association for the Evaluation of the Educational Achievement (IEA) or the Educational Testing Service (ETS, USA) have developed powerful methodologies to compare the level of knowledge acquired by students from different countries and with distinct cultures (Purves, 1989). As an exemple, recent results obtained by ETS (1991) for the area of Mathematics and for 13 year-old students are presented in Figure 9, showing a wide spectrum of levels and that the best results are not necessarity associated to the most affluent societies. The improvement of the efficiency of each educational system always requires a careful discussion on how resources are allocated. Unfortunately, this allocation is often unbalanced particularly in developing countries. For instance, Table 6 shows clearly that a too high percentage of resources devoted to wages is strongly associated to less developed systems. The insufficient quality of basic or secondary education in such systems is also a result of a biased allocation in favour of higher education as it is shown in Table 7. Usually, this situation is not just due to less high quality standards in basic and secondary education but also to stronger lobbying pressures coming from the staff of higher education institutions without an equivalent counterpart from the other levels. Recent events such as large demonstrations of representatives of unions, teachers secondary education students taking place in different E E C countries (France,
418
L. Valadares Tavares / On the development of educational policies
UK, Belgium, etc.) show that leaders of this level are finding out and using other sources of presL sure which were used with a reasonable success by higher education during the early seventies. Comprehensive initiatives to support the social costs of longer schooling periods have to be adopted whenever a momentum of higher motivation and commitment is achieved. Such initiatives have to cover the lack of resources of population groups with a lower income. This means that the split of F into S and R (Figure 3) should be regulated in terms of the difficulties experienced by such groups. Unfortunately it seems that there is a paradox situation of having S / F with a high level just in countries with a more affluent situation. As an example, the case of the Netherlands can be quoted where about 24% of the public budget of higher education is allocated to S despite of being one of the countries with a more favourable ratio GDP/(young population) (OECD, 1991). However, even adopting the most convenient allocation of resources, it seems clear that the level of efficiency decreases rapidly whenever resources are insufficient which means that shortages can be particularly expensive. Fortunately, the improvement and the expansion of the educational systems of less developed EEC regions has been recently supported by EEC structural funds (ERDF - European Regional Development Fund and ESF - European Social Fund) through integrated programs including the construction of infrastructures, the acquisition of equipment and the training of staff (teachers, managers, etc.). The impact of these intervenTable 7 Annual cost per student in higher education/annual cost per student in secondary education (1988) a Canada USA Japan Austria France Luxembourg UK Italy Portugal Spain Denmark Sweden a using data from OECD (1991).
2.02 1.63 0.93 1.56 1.26 2.15 1.79 2.04 3.24 1;44 2.54 0.78
participation
/
/
f
Years
Figure 10. Participation rate for the (15-17 age group) in Portugal (in Tavares, 1991)
tions in some countries (namely, Portugal where the program is called PRODEP - Programa de Desenvolvimento Educativo para Portugal, see GEP, 1990) is being more rapid and intense than expected as it can be shown by the acceleration of the participation rate presented in Figure 10 (Tavares, 1991). The estimates of the required investment to cope with the expansion of educational systems in priority regions of EEC were already computed (Figure 11). Improving the quality and the efficiency does not just require enough resources but also clear principles about the roles to be played by educational systems as well as about the needs and types of motivation of different groups of students. A clear example of this issue is the diversification of upper secondary education (Max Planck Institute for Development and Education, 1979). Table 3 shows that the supply of a vocational branch within upper secondary level has much lower impact in southern Europe where the participation rates for the critical ages of 15-18 years are also much lower (Figure 12).
4. 4. Policy assessment The general framework for assessment of a policy can be formulated in terms of two major comparisons (Figure 13):
L. Valadares Tat;ares / On the det;elopment of educational policies
!
Resources (R)
~- ii~i i~ii, ,t~ ~ :~ ~ ,,:~ ~i .~i ~ b
Students Inflow
W , L IlL.J,, . .......... J i . L , ,i.[ .MJ] =
419
:~
i;~. "~:. :~ • ~i. ~ '~
I~. :~
~:: ~? ' ~:~ i~"i -~ ::!~i ~: .~: ..,'.~'~
~i:.
-::~." ~ii ~:
/l:: .~- .:~:i.
(A])
outflow
(Ao)
i~ ackground culture
U gPltll:~l M'I'ACJ rPivb I'VFr bi~-I U MLAMCP~ICSS N CLiAAAMAAABCCCCCL~CI~LILM M P~P
Regions
Comple~on rates
i~ Social/economic conditions
Figure 11. Regional investment requirements (in Derenbach, 1990). Increase of capacity of lower and upper secondary education required by several E E C regions (expressed in thousands of student places)
Students
AI !~ Personal w o r k
~
Achie~ment scores ~:,:,
~:::~Pubhc support .
Educational attainment
Figure 13. Policy evaluation
a) the changes of students features due to education (A o - A ~ ) in terms of the committed resources (R) where A o (A t) represents the attributes of the out (in) flow of students and R the committed resources;
][~urtipatlon rate 100 (%)
~::;--o......0...
gO
"'l
"'~',
""%
""'li, ',""'B.. " "I,"",, "r~
8o
".,
70
tl
N
...~... EECSot lm, ...[~'..EECN~'~
~,ii
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6O
': ~" L
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"~ 'l ~',
4O
'1 "01
"~,, 'l "'. •,
° , . °H3.o.
Io --A ...... /~ ...... a
o
1
I
I
I
I
I
I
I
I
I
I
I
13.
14.
1~
16.
17.
18.
19.
20.
21.
2?-
23.
24. Years
Figure 12. The participation rate in E E C countries (in Derenbach, 1990)
b) the gap between the goals A~ and the achieved results, ,4 0 . Obviously, the development of these analyses requires the use of multi-criteria decision methods. The major attributes to be considered may be aggregated into three major dimensions: • the cultural perspective (historical heritage, ethical standards, etc.); • the monetary perspective (resources, wages, etc.); • the social-economic perspective (the rate of unemployment, the impact of education in the economic development, etc.). The assessment of any policy implies a good information system to provide decision makers with the appropriate data allowing the estimation o f R , A xand A o. Compensatory a n d non-compensatory approaches can be used, and models helping to understand the trade-offs between these three attributes. Again, multi-criteria decision aids can help to structure the process of policy evaluation and to select the most appropriate alternative. Special importance should be given to the support of negotiation models (see, e.g., Tavares'et al., 1989) as most policy making issues involve the cooperation of multiple decision-makers.
42O
L. Valadares Tavares / On the development of educational policies
List of r e g i o n s
G R P In E T M T A C Ir Pi V L
Greater A t h e n Rest of central Greece and Euboea Peloponnesos Inoian Islands Epirus Thessaly Macedonia Thrace A e g e a n islands Crete Ireland Piemonte Valle d'Aosta Lombardia
T V Fr Li E T U M L A M C P
Trentino - Alto Adige Veneto Friuli - V e n e z i a Giulia Liguria Emilia - R o m a g n a Toscana Umbria Marche Lazio Abruzzi Molise Campania Puglia
References Banks, Olive. (1987), The Sociology of Education, Batsford. Boyer, R.A., Rossand, R.D., and Ross, T.A. (1967), "The use of a computer to design school bus routes; A status report, I", Educational Data Processing 4/3, 143-151. Cherkaoui, M., (1979), Les Paradoxes de la R~ussite Scolaire, PUF. Churchman, C.W. (1964), " A design for systems research on instruction", Syracuse University. Coleman, J.S., et al. (1966), "Equality of opportunity", US Dept. of Health, Education and Welfare, Washington. Correa, M. (1963), The Economics of Human Resources, North-Holland, Amsterdam. Debeauvais, M., and Psacharopoulos, G. (1985), "Forecasting the needs for qualified manpower: Towards an evaluation", in: A. Youdi and F. Hinchliffe (eds.), Forecasting Skilled Manpower Needs, UNESCO, 1985. Derenbach, (1990), "Human capital and related infrastructure endowments: Investment requirements in problem regions", Unpublished Report. EEC (1992), "Memorandum on higher education", EEC. Gal, R. (1987),. Histoire de l'l~ducation, PUF. GEP (1990), "PRODEP: Programa de Desenvolvimento Educativo para Portugal, 1990-1993", GEP-Minist6rio da Educa~o, Lisbon (in Portuguese). Hus6n, T. (1986), Meio Social e Sucesso Escolar, Horizonte. IAEP (1992), "Learning Mathematics", ETS. IRDAC, (1991), "Skill shortages in europe", Commission of the European Communities, Brussels. Kairamo, K. (ed.) (1989), Education for Life, Butterworths, London.
B C S S N C Li A A A M A A A B
Basilicata Calabria Sicilia Sardegna Norte Centro Lisboa Alentejo Algarve A~ores Madeira Andalucia Aragon Asturias Baleares
C C C C C C C E G L M M N P
Canarias Cantabria Castilla - La Mancha Castilla y Leon Catalufia Ceuta - Melilla Comu. Valenciana Extremadura Galicia La Rioja Madrid Murica Navarra Pais Basco
Lazlo, E. (1983), Systems Science and World Order, Pergamon Press, Oxford. Lesourne, J. (1988), IEducation et Socidtd: Les Ddfis de FAn 2000, La D6couverte, Paris. Machlup, F. (1984), The Economics of Information and Human Capital, Princeton University Press, Princeton, NJ. Max Planck Insitute for Development and Education (1979), "Between elite and mass education in Federal Republic of Germany", Max Planck Institute for Development and Education. MVOW (1989), "Richness of the uncompleted: Challenges facing Dutch education", Ministerie van Onderwijs en Wetenschappen, The Hague. OCDE (1987), "La qualit6 de l'enseignement: Un rapport explicatif', OCDE. OECD (1991), "Education at a glance", OECD Internal Report of INES project; unpublished draft version. Purves, A. (1989), International Comparisons and Educational Reform, Association for Supervision and Curriculum Development, Chicago Press. Rajan, A. (1990), "1992 - A Zero-sum Game. Business, KnowHow and Training Challenges in an Integrated Europe", Industrial Society Press. Rassekh, S., and Vaideanu, G. (1987), "The contents of education. A worldwide view of their development from the present to the year 2000", UNESCO. Roy, B. (1985), M£thodologie MulticritOre d'Aide ~ la D£cision, Economica, Paris. Schultz, T.W. (1960), "Capital formation by education", Journal o f Political Economy 68, 571-583. Shepard, W.C. (1965), "Operations Research in Education", Management Science 2/4.
L. Valadares Tavares / On the development of educational policies Smith, W.O., Lester, (1971), Government of Education, Pelican. Tavares, L.V. (1984), "The TRIDENT approach to rank alternative tenders for large engineering projects", Foundations of Control Engineering 9/4, 181-193. Tavares, L.V. (1991), "Desenvolvimento de sistemas educativos: Modelos e perspectivas", GEP-Minist6rio da Educa~ao, Lisbon (in Portuguese). Tavares, L.V., and Santos, R.F. (1989), "Searching for consensus and convergence", in: M.C. Jackson, P. Keys and S.A. Cropper (eds.), Operational Research and the Social Sciences, Plenum Press, New York, 1989.
421
Tawney, R. (1986), Equality, Allen & Unwin, London. Tinbergen, J., Bos, H.C., Blum, J., Emmerij, L., and Williams, G. (1965), "Econometric models of education: Some applications", OECD, Paris. UNESCO, (1981), "Statistical methods for improving the estimation of repetition and drop-out. Two methodological studies", UNESCO. UNESCO, (1982), "Perspectives et t~ches du d6velopment de l'dducation en Europe ~ l'anbe d'un nouveau milldnaire", UNESCO.
409
Theory and Methodology
On the development of educational policies L. V a l a d a r e s
Tavares
CESUR-IST, Av. Rovisco Pais, 1000 Lisbon, Portugal Received March 1992; revised October 1992 Abstract: The development of educational policies is studied in this paper using the system approach. The most promising areas for application of O R in policy design and evaluation are identified and discussed in terms of illustrative data taken from several countries, namely member states of the European Community. Keywords: Policy design; Evaluation; Education
1. Introduction During the last decades, the importance being given to issues and policies concerning a macrolevel of decision is growing in most industrial societies. This level is defined as opposed to the micro-level which is traditionally associated to the firm, the family or the individual. The macro-level includes not just the national or multi-national cases but also the regional or sub-regional systems as well as economic sectors or social classes and groups. The inclusion in the same system of a large number of decision-makers with different values and objectives may be considered as one of the most specific features of this level of analysis. Recently, the role of O R as a decision-aid has been enhanced but most of the published literature concerns with theoretical models or applications carried out at the micro-level. Few applications of O R tools to support decision-making at more aggregated levels of analysis and decision can be quoted despite the usual praise given to
Correspondence to: Prof. L. Valadares Tavares, CESUR-IST Av. Rovisco Pais, 1000 Lisbon, Portugal.
the supportive role of O R for macro policy making whenever its nature or future is discussed. The educational sector is, no doubt, a good example of an important sector of activity with complex and difficult policy making issues (Smith, 1971) which have recently received very little attention by the O R community (Lesourne, 1988). In this paper, the potential of O R to support policy making in education is studied. The contributions of O R can be particularly useful for systems modeling, policy design and policy evaluation. These lines are discussed in terms of recent developments taking place in Portugal and in other countries, some of them belonging to the EC.
2. The educational system The educational sector of most countries is a complex and important part of their cultural, political, social and economic structures (Banks, 1987). The complexity of this sector is a direct result of being the outcome of historical processes where
0377-2217/95/$09.50 © 1995 - Elsevier Science B.V. All rights reserved
L. Valadares Tavares / On the development of educational policies
410
Table 1 Education as a sector of activity (EEC countries, 1988) a
B
Average percentage 1) 5 - 2 4 year old population 2) 5 - 2 4 age-group
VW-II
[]I.
25% Minimum: 18% ( F R G ) Maximum: 36% (Republic of Ireland) I
Participation in education (5-24 year old) Labour force in education (as a percentage of the total labour force) G D P devoted to education
80% 4% Minimum: 2% (Spain) Maximum: 10% (Belgium)
13 - Compulsory
}
, . l'm - Primarylevel e~ucation~_B2- Lower secondary level
FCI -general C - Upper secondary education].(2 -Vocational
6%
a Using data from O E C D (1991).
[Dt - Higher education(Universitylevel) D - Post secondary education ~ 132- Higher education(Politechniclevel)
[.D3 - Highervocationaleducation
private and public actors interacted during several centuries with a wide diversity of values and objectives (Gal, 1987). This explains the strong diversity of features exhibited by present educational systems even within groups of countries belonging to the same community as it is the case of E E C Member States. The importance of each educational sector is not just due to its role of developing the system of values, knowledge and skills of each new generation but also due to its political social and economic features. Usually, as it is shown in Table 1, more than 20% of the population is directly involved in this sector as clients (students) and no less than 4% of the active population works for this sector. This sector is one of
g - Continouslong - life education Figure 1. Major components of the education system
the largest consumers of public expenditure in a permanent and strong competition with two other sectors: health and defence. Each educational sector includes a wide variety of levels, institutions, programs, certificates and activities (Rassekh et al., 1987) but its major components are identified in Figure 1. The extension of each one depends not just on the demographic structure of the population but also on the stage of development of the whole society.
Table 2 Duration of education periods in E E C Year of education 1 Minimal age 4 Belgium Denmark FRG France Greece Ireland Italy Luxembourg Netherlands Portugal Spain United Kingdom P: Primary. 1: Lower secondary. 1I: U p p e r secondary.
5
P
P
2
3
4
5
6
7
8
9
10
11
12
13
6
7
8
9
10
11
12
13
14
15
16
17
18
19
P P P P P P P
P P P P P P P
P P P P P P P
P P P P P P P
P P P P P P P
P P 1 I P P I
1 I 1 I I I I
I 1 1 II I I I
11 I I 11 I I II
II I I II 11 II 11
11 11 11 II II II II
11 11 11 II II
II II II
II II II
II
P P P P P
P P P P P
P P P P P
P P P P P
P P P P P
P, P P I I
1I I I I I
1I II I I I
11 II I II I
II II I1 I1 I
11 II 1I 11 II
11 II I1 I1 II
II II
II II
L. Valadares Tavares / On the development of educational policies
Under-developed countries have short periods of compulsory education (e.g., 3 or 4 years) as opposed to the most advanced societies where no less than nine or ten years of schooling is imposed (see Table 2, from Derenbach, 1990). Industrial countries enhance the role of the vocational stream within the upper secondary education in contrast with more traditional and landbased economics where the percentage of students following such option is low as it is the case of southern Europe (see Table 3, from Derenbach, 1990). Pre-school education has initially been developed to allow both parents having a job but it can also play a key role to compensate depressed social backgrounds. Higher education can embrace more than 20 or 30 percent of the age group of 20-24 year olds in more modern societies and then the degree of its diversification is also higher. The average composition of EEC students is presented in Figure 2. Technological progress is responsible for longer leisure periods in the working population and for a faster rate of obsolescence of human knowledge and skills. These two combined effects can explain the increasing importance of the role played by long life education whenever technology leads a process of development (Kairamo, 1989). Despite all these differences, it seems that two paradigms are generally accepted for this sector (UNESCO, 1982): • The educational activities should be oriented to contribute to the full development of each person according to the values, the goals
Table 3 Percentage of students in level II of secondary education following vocational programs (EEC countries, 1988) Country
Percentage
14 - 15 17 - 18
5-6
12% Pre-primary
411
44%
34%
[
I
Primary
Secondary
Lower Secondary
III
year old
10% Te/~ ary
level
Upper Secondar
Compulsory --- ( Higher f General ----------~..~Education "1 / - [ Advanced kVocational ~ L Vocational Figure 2. Distribution of students in EEC (using data from (OECD, 1991)
and the needs accepted and perceived by each society. • The components of the educational sector should be harmonically and consistently interconnected in order that each individual can select the most appropriate path for hi s/ her education and training. These two paradigms are the logical basis for considering the educational sector as a system (Lazlo, 1983): the educational system. Therefore, important efforts to apply the systemic approach to education have been made since the early sixties (Churchman, 1964; Shepard, 1965) but unfortunately little attention is being given to this line of research during the last decade. However, the contribution of OR can be particularly relevant in two areas which are critical for the development of educational policies: a) the modeling of the educational system; b) the design and the evaluation of policies.
Group 1: Italy Netherlands FRG France UK Denmark Spain
64 62 60 46 46 39 37
Group 2: Greece Ireland Portugal
27 13 7
3. Modeling the educational system The most general and basic model of any educational system is presented in Figure 3 where major flow-variables are identified and defined (Tavares, 1991). This 'black-box' model can be applied to the overall sector or just to sub-systems such as a region, a school or a course.
L. Valadares Tavares / On the development of educationalpolicies
412
................................
'R
F
,
i
[
I
x . _ ...._....a. . . . . . . . . . . . ~ i~~::~i~ .: 7~i::#::
................
~::~ '::~.,
~ # ~~~~
.................................................
j
studeaats flows B
.
Infra-structures (Buildings, ere)
......... in~orrmtion flows
C
-
System's control
.....
E
Expectations
ED -
NO-
Effective d e m a n d (students)
resource* flows
Outputofnon-succeededstudents
N O = D + FO
b'D - S t u d e n t s w h o failed entering into the system F
-
Financial resources devoted to Education
/-[
-
H u m a n resources
I
-
Effective i n p u t o f s t u d e n t s
L
_
Lost potencial d e m a n d
where D = drop-outs and F O = Students without success 0 Output of well succeeded students PD
-
Potencial d e m a n d (students)
Q
.
C o n t e n t s quality
R
Finances d e v o t e d to e d u c a t i o n a l resources
S MQ -
Social s u p p o r t allocated to s t u d e n t s
M o n i t o r e d q u a l i t y of the
educational systems
T
.
T e a c h i n g aids a n d t e c h n o l o g y
Figure 3. The basic model of the educational system
The simulation of the process within the box is usually carried out in terms of a two-dimensional chain model describing the students flows along the succession of grades and academic years as it is presented in Figure 4. F r o m past data, the probabilities d~(i), d~(i) and s(i) can be estim a t e d (see, e.g., U N E S C O , 1981) and hence the propagation of a population along the system can be easily simulated. The state equations can be easily deduced:
X ( i , t) = S ( i - 1, t - 1 ) [ 1 - d s ( i -
+F(i, t -
Figure 4. The chain model of an educational system
x(i, t) = N u m b e r of students at grade i and academic year t.
s(i, t ) = N u m b e r of students flowing from i to i + 1 during the transition from year t to year t + 1. F(i, t ) = N u m b e r of students flowing from i to i + 1 during the transition from year t to year t + 1. Obviously, Markov chain models can also be built and their application is particularly useful if the stationarity of the process is acceptable (see, e.g., Correa, 1963).
1)]
1)-[1 -d~(i)],
F ( i , t) = X ( i , t ) [ 1 - s ( i ) ] , S(i, t) = X ( i , t ) ' s ( i ) , O(i, t) =
D'(i-
1, t)
+ D"(i, t)
S(i- 1, t).ds(i - 1)
with:
F(i, t).dr(i)
d~(i) = Probability of dropping out for a student who passed at grade i.
dr(i) = Probabifity of dropping out for a student who failed at grade i.
s(i) = Probability of passing for a student at grade i.
Figure 5. Resources analyses
L. Valadares Tavares / On the development of educational policies
A second stage of analysis oriented to estimate the needs of resources can be then started. Another simulation model can be built following the structure presented in Figure 5. Particular attention should be given to the spacial distribution of the educational system as it always has to be widely spread all over the country. The network of schools for compulsory education should also cover low density areas which implies having a very low number of students per school. This difficulty arises in many European regions (e.g, Scotland, Wales, hinterland of Portugal, some central areas of France, northern areas of Scandinavia, Southern Italy, etc.) and for instance, in Portugal, about 10% of the primary schools have less than ten students (Tavares, 1991). The well developed set of OR techniques to study distribution and routing problems can help improving the network of schools and the transportation systems adopted to collect and to take back home their students (see, e.g., Foyer et al., 1967). The interactions between the educational system and the external world deserve capital attention as the system 'belongs' to society and it is supposed to contribute to its development (Figure 6). Three major areas of modeling can be described: A. The relationship between the students choices or performances and their social or economic origins.
413
Private
Public ,~ourc~
/kt
Families
Enterprises
Regions
support
Figure 6. Relationship between education and society
B. The relationship between the educational attainment and the professional success/reward. C. The contribution of education to the social and economic development.
Table 4 Educational success in terms of social-economic background Social-economic level of the student's father
Non-skilled worker Skilled worker • agriculture • industry Liberal professional Middle m a n a g e r Top m a n a g e r
Portugal 8 9 / 9 0 (using data from Tavares, 1991) Percentage of students at 6th grade without having failed any academic year
Fraction of the best score
53% 56% 69% 76% 72% 87%
Netherlands for students born around 1978 (using data from M V O W , 1989) Academic level of results at the end of primary education
Fraction of the best score
0.61 0.64 0.79
2.65 3.09
0.75 0.87
0.87 0.83 1.00 M a x - Min = 0.39
3.0 3.35 3.55
0.85 0.94 1.00
M a x - Min = 0.25
L. Valadares Tavares / On the development of educational policies
414
Skill score
1%
Ymr19~7 S%
i ~
M~ ,~i~::i!::
Ym'~ 11%
term of the number of years spent in school which can be considered as the accumulated human capital (see Schultz, 1960, and Machlup, 1984). The internal rate of return of the investment defined by an additional year of study can be estimated in terms of the corresponding increase of wages (receivals) and of the lost wages plus study costs (expenses). The third line of research has studied the impact of education on the economic development and it was started by the pioneering work of Schultz (1963) in the USA and of Tinbergen et al. (1965) in Europe.
4. Policy - m a k i n g in e d u c a t i o n
4.1. Policy aims
0
Sta~s'dcaldi~bu~on
Figure 7. Forecasted skills rating for USA (in RAJAN, 1990)
The first topic was addressed by many authors (see Tawney, 1956, Coleman, 1966, and Husen, 1986) and it seems that a rather significant relation can be estimated using a multivariate statistical model explaining the success of a student at year t in terms of the social-economic level of his parents and of their achievements before t. The contribution of the first factor is much higher in more heterogeneous societies (Cherkaoui, 1979) than in the less stratified ones as it is well examplified for Portugal and the Netherlands in Table 4. The second topic has been subject to intensive analysis with the purpose of closing the gap between the contents of education and the future society needs expressed in terms of the required skills (as an example, a forecasting analysis developed for USA is included in Figure 7, from Rajan, 1990). Modeling the contents of education to fulfill the new needs has also been studied by E E C as it is presented in the well known I R D A C report (IRDAC, 1991) and by O E C D (OECD, 1992). Another area of modeling about this second topic has been oriented to study the wages in
Despite the diversity of cultural traditions, ethical standards and political systems, it seems that most societies are giving priority in education to three major aims: accessibility, quality and efficiency. Accessibility implies not just easy systems to participate in the educational system but also favourable cultural, social and economic conditions supporting the generation of demand for education. This aim can be particularly difficult to achieve in more depressed regions or social classes where short term economic needs receiver a stronger priority. Quality is a key paradigm for any educational activity but its definition is always controversial and complex. This concept can be formulated along three different criteria: quality of the goals assigned to each educational program, quality of its contents and quality of the processes adopted to implement such program. The quality of the goals should reflect their social and economic utility as it is important that the needs of each society will be fulfilled by its educational system. The contents has to be adequate for the selected goals and it should have cultural, scientific and technical quality. The adopted educational process should have pedagogic quality using the most appropriate tools and paths to motivate the students and to improve their results. These three perspectives on quality should be applied to the transformations induced in the
415
L. Valadares Tavares / On the development of educational policies
students by education in order that the overall level of quality will be estimated. Such level is the added value generated by education and it should be not identified with the academic results achieved by t h e students as they do not take into account their initial state. This means that the added value generated by a school receiving students from a deprived background and obtaining low academic results can be higher than that created by a school serving high income students and achieving high results. Obviously, the multi-criteria modeling (Roy, 1985) can contribute to the formulation a n d the estimation of the quality levels. Efficiency is another key paradigm in education and it is a source for permanent debate. This concept can be defined in terms of the ratio between the o u t p u t of education and all the inputs devoted to its activities. The quantitative estimation of the output implies the application of the multi-criteria approach to the assessment of the transformations
generated by education which is not an easy task. On the other hand, the estimation of the inputs is also far from trivial because it requires a model to estimate the allocation of resources to each activity. This explains the controversial nature of any attempt to assess the efficiency level of each educational system. 4.2. Decision-makers
The processes of intervention to develop educational systems have to consider the different classes of decision-makers and their decision levels (Tavares, 1991). A taxonomy is presented in Table 5, showing that: • the number and the diversity of decisionmakers are quite high; • the strategic and the tactical levels should not be restricted to higher authorities but should also be present in decision-making by schools and associations;
Table 5 A taxonomyof decision-making in education Classes of decision-makers A. International authorities
Decision level Strategic
Joint policies (quality; access; mobility) B. National authorities National policies (curriculum; resources; staff; social support) C. Regional/local authorities Regional/local issues (school development, fund raising, students suppor0 D. Schoolsmanagers, teachers, Schoolplanning students, parents,...) E. Unions (teachers, and Careers negotiation non-teaching staff) and recognition F. Association Participation in • Parents decision-making • Students G. Suppliers of schools National and regional • Buildings programs • Teaching aids (books, videos,. ;. ) • Equipment (labs, computers.... ) • Distribution • Transportation
Tactical International programs
Operational Funding; Recognitionsystems
Budgeting; rules: incentives
Monitoring control
Resources allocation
• Personnel management • Supplies • Transportation
School programmingand assessment Initial and continuous training
School management Teaching conditions
School-familyrelations and youth activities
School management
Designing Tendering Scheduling
Operations
416
L. Valadares Tavares / On the development of educational policies
UnJt~Stat~s ~
~
s..°
~
C.mt~llutho~tl~
I--1
'Italy ~ijiiii:i::ii:!i!ii !!~!iiiJiiiii Figure 8. Distribution of responsibilities within the educational system(in OECD, 1991)
• the achievement of specific goals implies setting up principles guidelines, rules and incentives to lead all classes of decision-makers to select alternatives producing results consistent with such goals; • the design and the assessment of policies should consider the diversity of decision-makers and of levels of decision. Obviously, the distribution of responsibilities and of the type of decision-making among these actors varies substantially between countries as it is shown in Figure 8. 4.3. Policy analysis and design
Modern democracy emphasises the moral duty of any society to offer equal opportunities of education to any citizen which explains that the development of educational subsystems devoted to specific groups based on social privileges has become undesirable. The process of offering equal opportunities implies banning discriminatory rules and economic obstacles. The main approach to fight these obstacles has been to provide 'free education' which means, in economic terms, edu-
cation supported by the public (central, regional or local) budget. In some countries, namely in latin Europe, this policy gave to the central power the roles of owner and manager of the whole network of schools producing a very uniform supply of education. Often, this policy has been responsible for the adoption of the same rigid curriculum, textbooks and exams all over each country. This solution was initially considered very favourable as a guarantee of an equalitarian policy but it has been shown that such uniformity does not respect the natural diversity of groups and individuals generating higher rates of dropout and failure in individuals with different goals and motivation scales. Furthermore, societies respecting the pluralism of values should respect the right of each family to choose the type and the style of education which requires a diversified supply of education without economic discrimination. This target implies a system of cost compensation whenever education is not publicly operated. Also, offering equal opportunities has been initially considered equivalent to the supply of education under the same conditions to all the different social and economic groups. However, there is now full evidence that more favourable conditions should be offered to the more depressed groups if the goal of equal opportunities is kept (positive discrimination). The policies designed to improve the access can be expressed in terms of variables already defined for the general model of the educational system (Figure 3). Improving the access means increasing E D / P D in terms of the youth expectations (E), of the social support (S) and of the attractiveness of the educational system which is a function of the quality of the contents (Q) and of the resources allocated to this system (B, T, H). Usually, the design of a policy to improve accessibility implies initiatives along these three action lines (expectations, improvement of the educational system and social support) but the relative importance given to each component should be defined in terms of the most crucial obstacles identified in each specific situation. The generation of a stronger motivation towards education can be a critical factor either in less developed regions where youths do not frequently meet more educated people or in highly developed
417
L: Valadares Tavares / On the development of educational policies
areas where the expected increase of salary due to further education is small. In any case, mass media campaigns and the circulation of information about jobs and careers can be invaluable instruments to increase the level of expectations. Obviously, this action line is also directly associated to the achievement of a higher level of adequacy of the educational contents to the needs and interests of potential students. This can be the results of a strategy searching for a higher quality teaching-learning process as well as for a m o r e flexible and diversified supply of education. The quest for quality (OCDE, 1987) implies p e r m a n e n t systems to adapt the educational goals to the society needs and to monitor the quality of the educational programs (contents and processes). This means that dosing the gap between education and society can never be considered as a settled problem and that the quality of the educational results should be continuously estimated and assessed. Initiatives including representatives of enterprises and of academic institutions can help to adapt the educational goals to the society needs as it is described by (1991) and E E C (1992). The comparative assessment of the knowledge acquired by students in different countries can be
Figure 9. Percentage of correct answers in mathematics (populations for 13 year students; using data from IAEP, 1992)
Table 6 Budget allocation in educational systems (1988) a % % salaries capital Portugal France Luxembourg UK Canada Netherlands Spain Austria Japan
80.1 75.1 71.9 68.4 63.6 60.0 59.9 59.7 52.1
9.1 6.7 14.0 3.9 7.5 9.1 11.4 9.0 16.8
a Using data from OECD (1991).
also a key factor to improve the quality in each system. Institutions such as the International Association for the Evaluation of the Educational Achievement (IEA) or the Educational Testing Service (ETS, USA) have developed powerful methodologies to compare the level of knowledge acquired by students from different countries and with distinct cultures (Purves, 1989). As an exemple, recent results obtained by ETS (1991) for the area of Mathematics and for 13 year-old students are presented in Figure 9, showing a wide spectrum of levels and that the best results are not necessarity associated to the most affluent societies. The improvement of the efficiency of each educational system always requires a careful discussion on how resources are allocated. Unfortunately, this allocation is often unbalanced particularly in developing countries. For instance, Table 6 shows clearly that a too high percentage of resources devoted to wages is strongly associated to less developed systems. The insufficient quality of basic or secondary education in such systems is also a result of a biased allocation in favour of higher education as it is shown in Table 7. Usually, this situation is not just due to less high quality standards in basic and secondary education but also to stronger lobbying pressures coming from the staff of higher education institutions without an equivalent counterpart from the other levels. Recent events such as large demonstrations of representatives of unions, teachers secondary education students taking place in different E E C countries (France,
418
L. Valadares Tavares / On the development of educational policies
UK, Belgium, etc.) show that leaders of this level are finding out and using other sources of presL sure which were used with a reasonable success by higher education during the early seventies. Comprehensive initiatives to support the social costs of longer schooling periods have to be adopted whenever a momentum of higher motivation and commitment is achieved. Such initiatives have to cover the lack of resources of population groups with a lower income. This means that the split of F into S and R (Figure 3) should be regulated in terms of the difficulties experienced by such groups. Unfortunately it seems that there is a paradox situation of having S / F with a high level just in countries with a more affluent situation. As an example, the case of the Netherlands can be quoted where about 24% of the public budget of higher education is allocated to S despite of being one of the countries with a more favourable ratio GDP/(young population) (OECD, 1991). However, even adopting the most convenient allocation of resources, it seems clear that the level of efficiency decreases rapidly whenever resources are insufficient which means that shortages can be particularly expensive. Fortunately, the improvement and the expansion of the educational systems of less developed EEC regions has been recently supported by EEC structural funds (ERDF - European Regional Development Fund and ESF - European Social Fund) through integrated programs including the construction of infrastructures, the acquisition of equipment and the training of staff (teachers, managers, etc.). The impact of these intervenTable 7 Annual cost per student in higher education/annual cost per student in secondary education (1988) a Canada USA Japan Austria France Luxembourg UK Italy Portugal Spain Denmark Sweden a using data from OECD (1991).
2.02 1.63 0.93 1.56 1.26 2.15 1.79 2.04 3.24 1;44 2.54 0.78
participation
/
/
f
Years
Figure 10. Participation rate for the (15-17 age group) in Portugal (in Tavares, 1991)
tions in some countries (namely, Portugal where the program is called PRODEP - Programa de Desenvolvimento Educativo para Portugal, see GEP, 1990) is being more rapid and intense than expected as it can be shown by the acceleration of the participation rate presented in Figure 10 (Tavares, 1991). The estimates of the required investment to cope with the expansion of educational systems in priority regions of EEC were already computed (Figure 11). Improving the quality and the efficiency does not just require enough resources but also clear principles about the roles to be played by educational systems as well as about the needs and types of motivation of different groups of students. A clear example of this issue is the diversification of upper secondary education (Max Planck Institute for Development and Education, 1979). Table 3 shows that the supply of a vocational branch within upper secondary level has much lower impact in southern Europe where the participation rates for the critical ages of 15-18 years are also much lower (Figure 12).
4. 4. Policy assessment The general framework for assessment of a policy can be formulated in terms of two major comparisons (Figure 13):
L. Valadares Tat;ares / On the det;elopment of educational policies
!
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Figure 11. Regional investment requirements (in Derenbach, 1990). Increase of capacity of lower and upper secondary education required by several E E C regions (expressed in thousands of student places)
Students
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~
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Figure 13. Policy evaluation
a) the changes of students features due to education (A o - A ~ ) in terms of the committed resources (R) where A o (A t) represents the attributes of the out (in) flow of students and R the committed resources;
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Figure 12. The participation rate in E E C countries (in Derenbach, 1990)
b) the gap between the goals A~ and the achieved results, ,4 0 . Obviously, the development of these analyses requires the use of multi-criteria decision methods. The major attributes to be considered may be aggregated into three major dimensions: • the cultural perspective (historical heritage, ethical standards, etc.); • the monetary perspective (resources, wages, etc.); • the social-economic perspective (the rate of unemployment, the impact of education in the economic development, etc.). The assessment of any policy implies a good information system to provide decision makers with the appropriate data allowing the estimation o f R , A xand A o. Compensatory a n d non-compensatory approaches can be used, and models helping to understand the trade-offs between these three attributes. Again, multi-criteria decision aids can help to structure the process of policy evaluation and to select the most appropriate alternative. Special importance should be given to the support of negotiation models (see, e.g., Tavares'et al., 1989) as most policy making issues involve the cooperation of multiple decision-makers.
42O
L. Valadares Tavares / On the development of educational policies
List of r e g i o n s
G R P In E T M T A C Ir Pi V L
Greater A t h e n Rest of central Greece and Euboea Peloponnesos Inoian Islands Epirus Thessaly Macedonia Thrace A e g e a n islands Crete Ireland Piemonte Valle d'Aosta Lombardia
T V Fr Li E T U M L A M C P
Trentino - Alto Adige Veneto Friuli - V e n e z i a Giulia Liguria Emilia - R o m a g n a Toscana Umbria Marche Lazio Abruzzi Molise Campania Puglia
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B C S S N C Li A A A M A A A B
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C C C C C C C E G L M M N P
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