Factors influencing the academic achievement of the Turkish urban poor

Factors influencing the academic achievement of the Turkish urban poor

Cennet Engin-Demir *

Middle East Technical University, Department of Educational Sciences, 06531 Ankara, Turkey

International Journal of Educational Development 29 (2009) 17–29

A R T I C L E I N F O

Keywords:

Primary school

Urban poor

Academic achievement

Gecekondu

A B S T R A C T

This study estimates the individual and combined effects of selected family, student and school

characteristics on the academic achievement of poor, urban primary-school students in the Turkish

context. Participants of the study consisted of 719 sixth, seventh, and eighth grade primary-school

students from 23 schools in inner and outer city squatter settlements. The findings indicated that the set

of variables comprising student characteristics, including well-being at school, scholastic activities and

support, explained the largest amount of variance in academic achievement among the urban poor.

Although the effect sizes are small, family background characteristics and school quality indicators were

also found to be significantly related to academic achievement. The implications of this study for

improving primary schools in urban poor neighborhoods are discussed.

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1. Introduction and purpose

Empirical evidence clearly shows that education plays asignificant role in influencing an individual’s economic and socialcircumstances, with formal schooling playing an important role inthe enhancement of economic growth (Barro, 1997; Krueger andLindahl, 2001). By increasing economically productive knowledgeand skills (e.g. literacy, numeracy and problem solving skills),education increases individual productivity and thereby individualearnings (Psacharopoulos, 1994). Education is considered as abasic need that supports the fulfillment of other basic needs suchas shelter, food, clothing and security and helps steady improve-ment of quality of life. Through its positive effects on earnings(Psacharopoulos, 1994) and on housing, water, sanitation, utiliza-tion of health facilities and women’s behavior in terms of decisionsrelated to fertility, family welfare and health (Lleras-Muney, 2005),education has been regarded as an instrument for povertyreduction (Tilak, 2002). In this context, the increasing importanceof educational experiences and achievements in shaping people’sopportunities, especially their ability to secure decent work, hassignificant implications for social policies in many countries(Machin, 2006).

Learning is a product not only of formal schooling, but also offamilies, communities and peers. Social, economic and culturalforces affect learning and thus school achievement (Rothstein,2000). A great deal of research on the determinants of schoolachievement has centered on the relative effects of home- and

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school-related factors. Most findings have suggested that familybackground is an important determinant of school outcomes,whereas school characteristics have minimal effects (Brooks-Gunnand Duncan, 1997; Coleman et al., 1966; Heyneman and Loxley,1983); however, debates continue regarding the relative impor-tance of family and school inputs (Chevalier and Lanot, 2002;Schiller et al., 2002). Various studies have shown that both homeand school environments have a strong influence on theperformance of children, especially at the primary-school level(Carron and Chau, 1996; Griffith, 1999; Mancebon and MarMolinero, 2000). In addition to influences related to home andschool, academic achievement is also affected by students’ pre-existing human capital, which includes their unique way ofinteracting with each type of educational ‘‘institution’’, namely,family, community, school, peer group, the economy and theculture (Rothstein, 2000). Individual characteristics such asattitude towards school, perceptions of the school environment,involvement in scholastic activities and level of motivation havealso been found to influence academic achievement (Connollyet al., 1998; Ma, 2001; Veenstra and Kuyper, 2004).

A review of the literature reveals that studies investigatingdeterminants of school achievement have focused on the relativeimportance of home- and school-related factors, whereas scho-lastic activities, student well-being in school, attitude towardsschool, family characteristics and school characteristics are rarelyexamined in the same study. The present study differs from earlierstudies, especially those conducted in Turkey, in that it focusessimultaneously rather than separately on how home-, student- andschool-related factors affect the school achievement of the urbanpoor. Therefore, the purpose of this study is to examine the relativeimportance of home-, individual- and school-related factors in

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C. Engin-Demir / International Journal of Educational Development 29 (2009) 17–2918

accounting for academic achievement of poor, urban primary-school students in Turkish context. The specific research questionsin the study are as follows:

1. H
ow well each set of home-student and school-related factorsexplain the variance in academic achievement over and abovethe other sets?
2. T
o what extent the combination of home-student and school-related factors accounts for the variance in academic achieve-ment?
2. Theoretical background

2.1. Family characteristics

Research has consistently shown that family backgroundcharacteristics such as socio-economic status (SES) as measuredby parental education level, parental occupation and familyincome have an influence on school achievement (Colemanet al., 1966; Hakkinen et al., 2003; Heyneman and Loxley,1983). Among SES indicators, parental level of education has beenfound to be the most significant source of disparities in studentperformance (Chevalier and Lanot, 2002; Fuchs and Woßmann,2004; Guncer and Kose, 1993; Parcel and Dufur, 2001; Schilleret al., 2002; Willms and Somers, 2001; Yayan and Berberoglu,2004). Using PISA results, Fuchs and Woßmann (2004) concludedthat the effects of parental education on reading achievement of15-year-old students are greater than on math and scienceachievement. PISA 2000 results indicated that students whosemothers had completed their upper-secondary education achievedhigher levels of performance in reading than other students in allparticipating countries (OECD, 2001). Hanushek and Luque (2003)reported that family background exerts a very strong effect on 9-and 13-year-old students’ performance. Specifically, they foundthat students from disadvantaged families and families whereparents had less education have systematically performed worseon the Third International Mathematics and Science Study (TIMSS)tests than other students. Schiller et al. (2002) have argued thatregardless of national context, parents who have more educationappear better able to provide their children with the academic andsocial support important for educational success when comparedto parents with less education.

Parents with higher levels of education also have greater accessto a wide variety of economic and social resources (e.g. familystructure, home environment, parent–child interaction) that canbe drawn upon to help their children succeed in school (Coleman,1988, 2006; Gregg and Machin, 1999; McNeal, 1999). Looking atTurkish TIMMS data, Yayan and Berberoglu (2004) found thatwhen parental education levels and numbers of books at homeincreased, eighth grade student achievement in mathematics alsoincreased. Similarly, Thompson and Johnston (2006) used PISAresults from 20 OECD countries to explore the relationshipbetween non-school factors and student achievement. They foundthat students at the highest SES levels, as measured by the numberof books in a student’s home, had an educational advantage overstudents at the lowest SES levels. A sizable body of evidence(Currie, 1995; Gregg and Machin, 1999) exists that indicateseducational achievement is significantly lower among childrenfrom disadvantaged backgrounds characterized by poverty, lowlevels of parental education, negative parental attitudes andnegative neighborhood characteristics. Furthermore, a number ofstudies have found that a child’s home environment – specifically,the existence of opportunities for learning, the warmth of mother–child interactions and the physical conditions of the home –accounts for a substantial portion of the measured effects of family

income on cognitive outcomes of children (Brooks-Gunn andDuncan, 1997; Majoribanks, 1994). Higher family income isassociated with higher student achievement in most of the studies(Hanushek, 1992; McLanahan and Sandefur, 1994; Peters andMullis, 1997). However, whether the income effect is causal, ormerely reflects the correlation of income and some observablecharacteristics of parents such as parental education, occupationalstatus and parent–child interaction remains unclear in somestudies (Chevalier and Lanot, 2002; Ganzach, 2000; Mayer, 1997).Smits and Gunduz-Hosgor (2006) found that education of bothparents, the number of brothers, whether or not mother was ableto speak Turkish and father’s occupation were the major variablesaffecting educational participation of 9–11 years old Turkish girls.Parental education and income of the household had significantpositive affect on educational participation of both boys and girls.

Several studies have demonstrated that increased numbers ofchildren in the family leads to less favorable child outcomes,presumably through the mechanism of resource dilution (Blake,1989; Patrinos and Psacharopoulos, 1995). Resource dilution refersto the quantity of time and material resources that parents are ableto invest in their children (Teachman et al., 1996); when thenumber of children increases, parents can offer fewer resources perchild. Under such conditions, all forms of family capital – financial,human and social – are more finely spread across the children(Coleman, 1991). Again, empirical evidence supports these claims:children from larger families have been found to have lessfavorable home environments and lower levels of verbal facility(Parcel and Menaghan, 1994) as well as higher rates of behaviorproblems and lower levels of educational achievement (Downey,1995).

Cross-national research on the relative effects of home andschool has indicated that the relationship between a child’s socialbackground (e.g. parent’s education, family structure) and his orher academic achievement is stronger in developed nations than indeveloping nations, whereas school-related factors have beenfound to be more important than out-of-school factors inexplaining achievement variance in developing countries (Cole-man et al., 1966; Fuller and Clarke, 1994; Heyneman and Loxley,1983). In contrast, Simmons and Alexander (1978) concluded thatthe determinants of student achievement appear to be basicallythe same in both developing and developed countries. Similarly,recent cross-national studies found variations in national levels ofeconomic development had no affect on the relationship betweenchildren’s social background and their academic achievement(Baker et al., 2002; Hanushek and Luque, 2003).

2.2. Individual student characteristics

Studies have shown that individual student characteristics suchas student well-being, perception of the school environment,motivation, involvement in scholastic activities and student effort,gender, work and students’ perception of parental support andinvolvement all have significant effects on a student’s schoolachievement. In their School Well-being Model, Konu and Rimpela(2002) conceptualized well-being in school as a four-dimensionalphenomenon: school conditions, social relationships, means forself-fulfillment and health status. Research has shown that studentwell-being in school affects both their behavior and theirexamination results (Hoy and Hannum, 1997; Sabo, 1995).Well-being of students in school depends on many factors,including their opinions about school rules and their relationswith teachers and schoolmates (Veenstra and Kuyper, 2004).Student well-being may also affect other student-related char-acteristics, such as achievement, motivation, attitude towardsstudy and effort (Samdal, 1998; Veenstra and Kuyper, 2004). For

C. Engin-Demir / International Journal of Educational Development 29 (2009) 17–29 19

instance, late elementary school children who perceive theirteachers to be fair and caring are more likely to have positiveattitude towards school and increased motivation to achieve(Babad, 1996). Children’s perceptions of teacher support andteacher expectations have also been found to be positively relatedto achievement (Connolly et al., 1998). Moreover, children who areaccepted by their peers have been found to be more likely to enjoyschool (Verkuyten and Thıjs, 2002).

Scholastic activities and individual effort are also important forachievement. Keith et al. (1986) showed that regardless ofintelligence, as students spend more time on homework, theirgrades improve. In an international comparison study of scienceachievement in 23 countries, Postlethwaite and Wiley (1992)found that the average science achievement was high in thosecountries where students reported spending large amounts of timeon homework. Amount of time spent on homework has also beenfound to be strongly related to a student’s motivation to achieveand the positive feelings associated with achievement, whichthemselves have been shown to have an affect on actualachievement (Steinberg et al., 1992). In addition, school atten-dance has been shown to be highly correlated with individualachievement (Hanushek et al., 1996).

Gender is another important variable to be considered inexplaining variations in school achievement. In a sequentialregression analysis of gender differences, Farkas et al. (1990)concluded that when all other variables are held constant, girlsreceive higher course grades than boys. Evidence has also beenfound to indicate girls score higher than boys in terms of studentwell-being, achievement motivation and effort (homework time)(Connolly et al., 1998; Veenstra and Kuyper, 2004). On the otherhand, girls have been shown to perform lower than boys in terms ofmath and science scores (Berberoglu, 2004; Woßmann, 2003).

The relationship between school performance and work isgenerally perceived to be negative. Balancing the demands of workand education places physical and psychosocial strain on childrenand often leads to poor academic performance (Binder and Scrogin,1999; Heady, 2003). Akabayashi and Psacharopoulos (1999), founda child’s reading and math ability decreased with additional hoursof work, whereas they increased with additional hours of schoolattendance and study. Ray and Lancaster (2003) investigated theeffect of work on the school attendance and performance ofchildren in the 12–14 year age group in seven countriesparticularly in terms of the relationship between hours of workand school attendance and performance. They concluded thathours spent at work had a negative impact on education variableswith the marginal impact weakening at higher levels of workhours. An exception to this was in the case of Sri Lanka, where aweekly work load of up to (approximately) 12–15 h a weekcontributed positively to the child’s schooling and to his/her studytime.

Students’ perceptions of parental support and involvement arealso considered as influential factors on their achievementmotivation (Grolnick and Slowiaczek, 1994). Children’s percep-tions that their parents are involved and interested in school andencourage them to do well are positively related to academicachievement (Wang and Wildman, 1995). Through their involve-ment, parents convey the message that school is important andprovide their children with positive emotional experiences inrelation to school. Children, in turn, internalize their parents’positive expectations toward school and reflect them in their ownschool attitudes (Connolly et al., 1998). Fuchs and Woßmann(2004) observed that students performed significantly worse inreading, math and science in schools whose principals reportedthat learning was strongly hindered by the lack of parental support.Some research, however, has shown most aspects of the relation-

ship between educational support of parents and scholasticachievement of children to be negative (Muller and Kerbow,1993; Sui-Chu and Willms, 1996). It may be that parents, in aneffort at what might be termed ‘‘crisis-intervention’’, increase helpwith homework, discuss grades more often and contact teachersmore frequently when their child’s school achievement drops orwhen their child has a discipline problem (Veenstra and Kuyper,2004).

2.3. School characteristics

Findings reported in the literature regarding the relationshipbetween school resources and student achievement measure-ments are inconsistent. While some research has suggested thatmore resources do not necessarily yield performance gains forstudents (Hanushek, 1997; Hanushek and Luque, 2003; Hakkinenet al., 2003), other research provides clear evidence that variationsin school characteristics are associated with variations in studentoutcomes (Card and Krueger, 1996; Greenwald et al., 1996;Lockheed and Verspoor, 1991). Parcel and Dufur (2001) havedemonstrated that attending a school with a better physicalenvironment is associated with increased math scores. Willms andSomers (2001) reported a significant positive effect on schoolingoutcomes associated with student–teacher ratio, instructionalmaterials, size of the library and teacher training in 13 LatinAmerican countries. Large-scale studies in low-income countrieshave emphasized the importance of human and material resourcesin achieving better schooling outcomes, including such factors asschool infrastructure, class size, teacher experience and qualifica-tions and availability of instructional materials (Fuller and Clarke,1994; Heyneman and Loxley, 1983). However, in a studyexamining the role of schools and proxies for school quality inexplaining increases in student achievement levels in a developingcountry, Bacolod and Tobias (2005) concluded that schoolcharacteristics explained only six percent of total variations inschool achievement.

Among the various school characteristics, class size has beenthe most widely examined variable in educational policy studies;however, findings regarding the effects of class size on schoolachievement are inconsistent. Contrary to expectations, Woßmann(2003) found that smaller class size was significantly related toinferior student performance in math and science in 39 countriesparticipating in the 1994/1995 TIMSS, whereas Lindahl (2005)found that some minorities and economically disadvantagedgroups in Sweden benefited from smaller classes. Lindahl’s resultsare in line with those of Angrist and Lavy (1999) for Israel andKrueger (1999) for the United States, but they conflict with those ofHoxby (2000), whose longitudinal study of 649 elementary schoolsin the U.S. indicated that class size had no statistically significanteffect on student achievement. Another recent study conducted byRivkin et al. (2005) with three through eighth grade students inTexas demonstrated that the effects of class size on math andreading achievement growth, while statistically significant, weremodest and declined as students progressed through school.However in seventh grade students did not get any significantbenefit from smaller classes in mathematics and reading. Althoughsome studies have shown a positive effect of class size on academicachievement, especially in lower grades (Rivkin et al., 2005;Lindahl, 2005; Krueger, 1999) there has been no critical class sizesuggested by the researchers that increased academic achievement(Ehrenberg et al., 2001).

In addition to class size, teacher–student ratio is anothervariable widely used as an index of school quality; however, resultsof studies looking at the effects of teacher–student ratios on schoolachievement are also ambiguous (Hanushek et al., 1996; Fuchs and


Woßmann, 2004). International comparisons have failed to showany significant improvements in academic achievement as a resultof smaller teacher–student ratios (Woßmann, 2003).

Recent studies have highlighted the contribution of teacherquality to academic achievement (Darling-Hammond, 2000;Fetler, 2001; Rivkin et al., 2005). As determined by Darling-Hammond and Sykes (2003), key teacher quality components areverbal ability, subject-matter knowledge, knowledge of teachingand learning and ability to use a wide range of teaching strategiesadapted to student needs. Wiseman and Brown (2002) found thatteacher education levels are positively related to studentperformance. That is, as teachers attain higher levels of education,meet standards for certification in their communities and spendmore of their pre-service preparation time actually teaching, theirstudents tend to score higher on standardized achievement tests.On the other hand, other studies have shown teacher degree levelto be a relatively unimportant predictor of school outcomes(Goldhaber and Brewer, 1996; Rivkin et al., 2005).

3. Method

3.1. Main characteristics of urban poor

This study was conducted in urban areas (population 20,001+)within the Greater Ankara Municipality. As the capital and thesecond largest city in the nation, Ankara attracts large numbers ofmigrant families from Central and Eastern Anatolia; however, itlacks the employment potential to adequately absorb theseincoming families. The subsequent mismatch between populationand urban physical infrastructure and basic services has led to the‘gecekondu’ phenomenon, i.e. the construction of illegal squatterhousing built by migrants along the outskirts of major cities. Mostof the urban poor in large cities live in such gecekondu settlements,while some live in similar squatter housing in inner cityneighborhoods. Gecekondu inhabitants can be distinguished fromthe established city population by the following distinctivecharacteristics: ‘‘stronger ties to the village in comparison withestablished urbanites; membership of the city’s lower classes(low-income, low skilled jobs and low education levels, informalhousing); and lives centered around the communities that theyhave formed in the city’’ (Erman, 2001, p. 995). It is thesecharacteristics of gecekondu dwellers, researchers argue, that havecreated a sub-culture within the city (Erder, 1995; Kongar, 1999).

As part of their everyday existence, the urban poor live withcertain basic problems such as inadequate and unsanitary livingconditions, including a lack of clean water and air pollution (Keles,2000). There is no doubt that children of poor families grow up incircumstances worse than children whose family income level issufficient to meet their daily needs. While one might believe theavailability of free schools in poor neighborhoods provideschildren of the urban underclass an opportunity to receive aneducation and thus improve their possibilities for the future, thefact is that education that is free in theory in practice requiresfamilies to pay for school uniforms, notebooks and lunches andcontribute funds solicited by school administrations, thus pre-venting some poor families from enrolling their children in school(Bugra and Keyder, 2003). Moreover, schools serving poor childrenin villages and in urban gecekondu neighborhoods tend to be low-performing and staffed with less-experienced, poorly trainedteachers with low morale and low expectations. Classrooms maybe inadequately supplied with reference material, books and otherlearning material, and the buildings themselves may be char-acterized by unsafe environments that lack adequate lighting oreven functioning toilets. While better endowed schools may existoutside these neighborhoods, poor children do not have the

opportunity to enroll in them. (World Bank, 2005). Yet, despite thepoor quality of education offered to gecekondu residents, studieshave indicated that almost all of them have positive attitudes andhigh aspirations regarding their children’s education; they assumetheir children will eventually go on to complete a university-leveleducation, thereby securing improved living conditions in betterneighborhoods (Erder, 1995; Kongar, 1999).

3.2. Turkish education system

Children in the Turkish education system may enter non-compulsory pre-school education at the age of three. Compulsoryprimary education begins at age six or seven and comprises eightyears of schooling, after which children may attend secondaryeducation (four-year general high school or vocational high schoolor technical high school) or vocational education (apprenticeshiptraining). Secondary education was extended from three to fouryears in 2005. Although efforts are being made, within theframework of European Union membership negotiations, to extendthe length of compulsory education to 12 years, secondaryeducation is currently not mandatory (Ministry of Education(MONE), 2007). The government runs and finances free publicschools, and MONE dictates the educational curricula of bothpublic and private pre-school, primary and secondary schools.Primary and some of the secondary school teachers (e.g. Englishlanguage teachers, Computer education and instructional technol-ogy teachers) are trained in four-year faculties of education.Secondary school teachers are trained in two main programs: First,the five-year undergraduate program for the students of facultiesof education. Second, a master of science program without thesisoffered by faculties of education for students who graduate fromfour-year science and letters and other relevant faculties.

3.3. Participants

The data used in this study are part of a larger research projecton light work and schooling. ‘‘Light work’’ is defined as work thatdoes not interfere with schooling and it is not exploitative, harmfulor hazardous to a child’s development (International LaborOrganization (ILO), 2002). For the main study a Multi-stageStratified Systematic Random Cluster Sampling method was usedin sample selection of schools, children who combine school andwork, children who are currently in school and not working.Initially a total of 200 schools were selected from within the sixdistricts of Greater Ankara Municipality based on the publishedinformation and opinions of an urban sociologist and an expertfrom ILO Ankara office about SES level of dwellers. It was assumedthat the number of children who combine school and work mightbe higher in inner city and other gecekondu neighbourhoods. Eachof the selected schools was contacted by phone and requested toprovide researchers with a list containing information on theapproximate numbers of working children and total number ofmale and female students at their schools. These lists were used toaid in the selection of schools from among the six districts to serveas the second stage sampling frame which was used in theselection of 25 schools based on the number of working childrenusing probability random selection. A listing form containingquestions on children’s sex, age, work status, family socio-economic status and neighbourhood developmental level formwas administered to all sixth, seventh and eighth grade students inselected 25 schools. Information collected from 10,040 studentsthrough listing form was compiled and used as the sampling framefor the third stage of sample selection. Two schools were excludeddue to the very low number of working children enrolled, asindicated by the listing study. At the final stage of sample selection,


50 students were selected randomly from each school with morethan 50 working children using stratification criteria. In schoolswith fewer than 50 working children, all working children wereselected. Students who were currently in school and not workingwere selected randomly from each stratum. A total of 1095students (672 working and 423 non-working) were selected from23 schools.

For the present study 296 working students from among 672were selected by using proportional stratified systematic samplingand all of the non-working students were included in the sample.Study participants consisted of 719 (441 male, 278 female) sixth-,seventh- and eighth-grade primary-school students from 23schools in inner city squatter settlements and other gecekondu

neighborhoods within the Greater Ankara Municipality. Thenumber of male and female students was not equal in the sampledue to the low proportion of female students among workingchildren.

3.4. Procedure

To ensure reasonable and accurate information capable ofgenerating sufficiently valid conclusions, face-to-face structuredinterviews were conducted with interview schedules (question-naires) developed by the research team. Both working and non-working students were asked same questions. However, addi-tional work related questions such as type of work, weekly hoursof work, reason of starting to work were asked to workingchildren. The common questions included in the StudentQuestionnaires were related to student perceptions regardingscholastic activities, peer support, teacher support and parentalsupport as well as questions related to household characteristicsand household possessions.

Principals were interviewed using a questionnaire developedby the research team and designed to collect information onschool-quality indicators. The questionnaire comprised questionsrelated to different school characteristics, including number ofstudents, teachers and classrooms; teacher–student ratios; classsize; availability of a school counselor; teacher characteristics,such as number of teachers who participated in MONE in-servicetraining during the previous year, number of teachers teachingoutside their subject area, number of teachers with a graduate orpost-graduate degree or currently enrolled in a graduate program;whether or not the lack of teacher availability prevented any classfrom being offered; and questions related to school facilities. TheTurkish language, math, and science scores as well as attendancerecords for each student interviewed were obtained from theschool records by the interviewers.

A pilot study was conducted to test the validity of thequestionnaires and to assess the data collection procedures intwo schools that were not included in the main sample. As a resultof the knowledge and experience gained from the pilot study,several changes were made to improve the survey instruments andto finalize a work plan for field implementation of the datacollection for the actual study. For example, it was observed thatsome students had difficulty in answering the questions in thelisting forms and the questionnaires because they lackedcompetency in certain basic skills such as reading and writing.Therefore, it was decided to use face-to-face structured interviewmethod to ensure the validity and accuracy of the data. In addition,questions in the initial listing form were reworded and the listingform was redesigned to make it more attractive to children.Questions on the Student Questionnaires were also revised toimprove clarity and coherence.

Interviewers were selected from among postgraduate andsenior sociology students at Ankara University. Interviewers were

requested to attend a one-day training session prior to datacollection. The training included information about the purpose ofthe study, data collection techniques and procedures, character-istics of school settings, characteristics of adolescents between theages of 12–14 and the purpose of each question asked in the datacollection instruments. A detailed field implementation work planwas prepared in advance and given to the interviewers. At the endof each day the interviewers brought the completed questionnairesto the co-ordinator’s office and discuss any difficulties encounteredand presented suggestions as solutions. Coordinator also con-ducted random checks of questionnaires providing feedback to theinterviewers regarding the quality of data collected and, ifnecessary requesting repeat interviews. Data collection processlasted about 40 days.

3.5. Measures

3.5.1. Academic achievement

A weighted composite of mathematics, Turkish and sciencescores (weighted .35, .35 and .30, respectively) from the samesemester obtained from school administrative records was used tomeasure academic achievement. This decision was based on thefact that, Turkish, math and science are allocated the greatestnumber of weekly hours (6 h/wk for Turkish, 4 h/wk for math andscience) in the curriculum and because a strong (Field, 2005) andsignificant correlation was observed between these three scores.The correlation coefficients between Turkish and math, Turkishand science and math and science are .61, .60 and .59, respectively(p � .001). In Turkish schools grading ranges from 1 to 5 (1 = Fail;2 = Pass; 3 = Moderate; 4 = Good; 5 = Excellent). Students’ overallGPA could not be obtained because of the time of the study. Datawere collected during December and students were asked toindicate whether they engaged in any work activity during theprevious (reference) month.

3.6. Independent variables

Independent variables in this study were selected based on boththeoretical and empirical considerations, including findings fromprevious research, data availability, data comparability. Three setsof independent variables – family characteristics, individualstudent characteristics and school characteristics – drawn fromthe Student and Principal Questionnaires were used in this study.Dummy coding was used to represent the categorical independentvariables.

Definitions of variables used and descriptive statistics arepresented in Table 1.

The first set of variables comprising family characteristics(family background) included variables for father’s education level,mother’s education level, home ownership, household size andhousehold possessions (Table 1). The decision to include a variablefor household size was based on the strong correlation (r = .75,p � .001) between number of siblings and total number ofhousehold members. Since the high percentage of urban poorworking in the informal sector and the large number of familymembers working temporary jobs made it difficult to obtainreliable information on family income from students, income wasnot included as an indicator of family SES. Instead, homeownership and household possessions were used as indicatorsof family income.

The second set of variables comprising individual studentcharacteristics included variables related to some backgroundcharacteristics such as grade, gender, work status and attendancelevel, as well as variables related to student well-being at school(perceptions of teacher support and peer support), scholastic

Table 1The variable definitions, percentages, means and standard deviations (N = 719)

Variables Definitions Percent Mean S.D.

Academic achievement A weighed composite of the math. Turkish and science achievement

scores of related semester (weighted .35. .35, .30, respectively).

Grading range: 1 = fail, 2 = pass, 3 = moderate, 4 = good, 5 = excellent

– 2.1846 1.0633

Family characteristics

Father education 1 = has a secondary level education or higher, 0 = otherwise 17.1 – –

Mother education 1 = has a secondary level education or higher, 0 = otherwise 7.2 – –

Household size Total number of people living in the dwelling 5.0250 1.3648

Home ownership Where do you live? 1 = our own home. 0 = otherwise 54 – –

Household possessionsa A summary of value was composed by summing the number of 1 s over each

area (with a range of 1–13), available = 1, not available = 0

– 9.4214 1.7597

Student characteristics

Grade 7 Students is at grade 7 = 1, 0 = otherwise (grade 6 is reference) 33.5 – –

Grade 8 Students is at grade 8 = 1, 0 = otherwise (grade 6 is reference) 34.5 – –

Work status Whether the child combine school and work (1) or not (0) 41.2 – –

Gender Male = 1 61.3 – –

Student’s perception of

treatment by teachers

How do your teachers treat you? 1 = very good, 2 = good, 3 =

moderate, 4 = bad and very bad

3.1238 .55853

Number of friends at school How many friends do you have in school? 1 = many, 0 = otherwise 70 – –

Participation in extra-

curricular activities

Do you participate in any extracurricular activities at school? 1 = yes, 0 = no 79.3

Time spent on studies Total hours spent on studying including time spent during the school

week and on weekends

15.165 7.4165

Time spent on leisure activities Total hours spent on sports/play and other leisure activities including

time spent during the school week and on weekends

23.022 11.873

Level of homework completion How often do you do your homeworks? 3 = often, 2 = sometimes, 1 = seldom and never 2.7830 .45425

Getting help with

studies outside school

Is there anyone who helps you with your studies after school? 1 = yes, 0 = no 54.5 – –

Parents level of follow-up Do your parents visit your school to ask about your progress?

3 = often, 2 = sometimes, 1 = not at all

1.8748 .65574

Attendance level Number of days child not attended school during the first semester 2.114 2.8701

School quality indicators

Teacher degree level Number of teacher with a master or Ph.D. degree or currently undertaking graduate study 2.8108 1.6531

Teacher in-service training Number of teachers participating in a MONE in-service training event during the past year 6.7761 9.4575

Teacher–student ratio Division of school enrollment by the number of teachers 30.695 14.447

Classize Principals perception of average class size in school 35.489 6.6827

School’s facilitiesb A summary of value was composed by summing the number

of 1 s over each area (with a range of 1–13), available = 1, not available = 0

7.3032 2.6128

a Bathroom, toilet-inside house, kitchen, central heating, running water, electricity, TV set, refrigerator, dishwasher, oven, washing machine, vacuum cleaner, personal

computer.b Library, sport facilities, science lab, computer lab, audiovisual materials, cafeteria, medical room, workshop or art room, school clubs, language lab, Internet connection,

playground for students, transportation.


activities, and perceptions of parental support (Table 1). Work wasmeasured in relation to a reference month during the school year.One hour of work during the reference month was consideredsufficient for classifying a child as engaged in economic activity.Definition of work encompasses all market production (paid work)and certain types of non-market production (unpaid work). Forexample, children engaged in unpaid activities in a market-oriented establishment operated by a relative living in the samehousehold were considered to be working in an economic activity.

The third set of variable school characteristics (school-qualityindicators) included variables for teacher–student ratio, class size,teacher in-service training, teacher degree level and schoolinfrastructure (Table 1). The decision to include a variable forteacher–student ratio was based on the strong correlation (r = .70,p � .001) between school size and teacher–student ratio.

4. Limitations of the study

Several study limitations deserve further attention in futureresearch. First, because the data utilized were derived from a largerstudy and not created specifically for this type of study or toanswer all the questions raised within the framework of thisresearch, not all the variables necessary were available; therefore,there is a potential for omitted variable bias. Second, study results

may be limited in their generalizability. The present study wasconducted in a single metropolitan area in Turkey. Thus the extentto which results apply to other cities is not known. Therefore,conclusions need to be verified by conducting similar studiesacross other large cities in Turkey. Third, academic achievementwas measured using grades given by subject teachers in language,math and science in the same semester; in order for these results tobe generalized with confidence to academic achievement ingeneral, this research needs to be extended to include standardizedachievement test scores. Finally, as with any cross-sectionalstudies such as this one the results should be viewed with caution.The data collected in this study did not include students’ academichistory.

5. Results

Multiple regression analysis was conducted to examine howwell each set of variables – family, students and schoolcharacteristics – predicted academic achievement over and abovethe other sets (Green et al., 2000). The models also suggested howacademic achievement was affected when family, students andschool characteristics were combined. The significance of a set ofindependent variables was tested by examining the increment ofR2 for the set over and above the R2 for those sets entered earlier.

Table 2Standardized regression coefficients for relations between family background characteristics, student characteristics, school quality indicators and academic achievement

Predictors Academic achievement

Model I Model II Model III

b t b t b t

Family background characteristics

Father education .143 3.573*** .106 2.788** .089 2.372*

Mother education .000 �.002 .039 1.053 .048 1.314

Household size .009 .238 .010 .288 .006 .188

Home ownership .103 2.787** .105 3.004** .087 2.499*

Household possessions .098 2.473* .051 1.364 .035 .893

Student characteristics

Grade 7 �.049 �1.211 �.029 �.734

Grade 8 �.013 �.312 �.001 �.024

Work status �.024 �.640 �.029 �.789

Gender �.179 �4.623*** �.173 �4.563***

Student’s perception of treatment by teachers .138 3.766*** .133 3.716***

Number of friends at school .101 2.919** .097 2.859**

Participation in extra-curricular activities .014 .413 .037 1.072

Time spent on studies .093 2.504* .075 2.059*

Time spent on leisure activities �.031 �.862 �.028 �.800

Level of homework completion .059 1.596 .060 1.653

Getting help with studies outside school �.084 �2.409* �.081 �2.356*

Parents level of follow-up .024 .702 .025 .724

Attendance level �.076 �2.115* �.073 �2.067*

School quality indicators

Teacher degree level �.132 �3.615***

Teacher in-service training �.118 �2.835**

Teacher–student ratio .144 3.704***

Classize �.035 �.989

School’s facilities �.054 �1.439

Multiple R .23*** .45*** .50***

Adjusted 100R2 .048 .18 .22

Effect size (R2) .054 .21 .25

R2 change .054 .15 .043

N = 719.* p < .05.** p < .01.*** p < .001.


Table 2 shows the standardized regression coefficients and t-teststatistics for relations between family, student and schoolcharacteristics and academic achievement.

The causal priority of three sets of variables – variables relatedto home, student and school – in explaining academic achievementwas determined considering the literature review as follows:

(a) F
amily SES influence student characteristics such as workstatus, their values and attitudes toward school.
(b) S
tudents’ perceptions of school environment influence schoolquality indicators.
Simultaneous-entry approach – all sets of explanatory variableswere entered into the model regardless of significance levels – wasselected because of the study aim of developing a comprehensivepicture of the different factors contributing to the explanation ofthe variances in the academic achievement of urban poor primary-school students in the Turkish context (Green et al., 2000).

The assumptions of the regression model were checked. As thezero-order correlations coefficients among independent variablesare all less than .34, the Variance Inflation Factors (VIF) valueschanged between 1.008 and 1.131 and tolerance statistics changedbetween .884 and .992, there is no evidence to suggest the finalmodel specification suffered from any multicollinearity that wouldchallenge the findings. That is to say, there is no strong correlationbetween two or more predictors in the regression model. TheDurbin–Watson statistic is also between one and three (1.620)

implying that errors in regression are independent (Tabachnickand Fidell, 1996). Standardized residuals were examined to detectthe availability of outliers. Two cases were determined as havingstandardized residuals 3.3 and 3.0. As none of those two cases hada Cook’s distance – a measure of the overall influence of a case onthe model – greater than one and sample size is large none of themwas having undue influence on the regression model (Field, 2005).The assumptions of normality, linearity and homescedasticitywere checked by looking standardized residuals scatterplots toexamine whether residuals are normally distributed about thepredicted achievement scores, the residuals have straight linerelationship with predicted achievement scores and the variance ofresiduals about predicted achievement scores is the same for allpredicted scores. It was found that all the assumptions were met(Tabachnick and Fidell, 1996).

The first equation included as predictors only those variablesassociated with family background characteristics. Regressionanalysis showed family characteristics were significantly relatedto school achievement (R2 = .054; adjusted R2 = .048; F(5,713) =8.204; p < .001. The multiple regression correlation coefficient ofModel I was .23. Standardized regression coefficients in Model Iindicated that father’s level of education, home ownership andhousehold possessions independently had significant effects onacademic achievement, whereas household size and mother’s levelof education independently did not have significant effects (Table 2).

In the second equation, the second set of variables – studentcharacteristics – was added to the set of family background


characteristic variables. Regression analysis showed the linearcombination of family and student characteristics to be signifi-cantly related to school achievement (R2 = .21; adjusted R2 = .18;F(13,700) = 10.172; p < .001). The set of student characteristicvariables accounted for 15 percent of the total variation inacademic achievement (R2 change = .15).

Standardized regression coefficients in Model II indicated thatstudent perceptions of treatment by teachers, student perceptionsof number of friends at school, sex (being male), total hours spenton studies per week, getting help with studies outside school andtotal number of days absent from school independently hadsignificant effects on academic achievement of urban poorprimary-school students. In contrast, this study found thatwhether or not the student combine school and work, grade level,student’s participation in an extracurricular activity, level ofhomework completion, time spent on leisure activities, andstudent’s perception of his/her parents level follow-up did notcontribute significantly to variations in academic achievement.The absolute t-values associated with Model II revealed thatgender was the most substantial predictor of academic achieve-ment. Boys perform on average .17 more poorly than do girls.Student’s perception of treatment by teachers was also found to bean important predictor of academic achievement (Table 2).

In the third equation, the third set of variables – school-qualityindicators – was added to the sets of family and studentcharacteristic variables. Regression analysis showed the linearcombination of family, student and school characteristics to besignificantly related to academic achievement (R2 = .25; adjustedR2 = .22; F(5,695) = 7.881; p < .001). The set of school-relatedvariables accounted for 4.3 percent of the total variation in academicachievement (R2 change = .043). The multiple regression correlationcoefficient of Model III between combined family, student andschool predictors and academic achievement was .50. Standardizedregression coefficients in Model III indicated that teacher–studentratio, in-service teacher training and teacher’s level of educationindependently had significant effects on academic achievement,whereas school facilities and class size did not have significanteffects. The absolute t-values associated with Model III indicatedthat teacher–student ratio was the most substantial predictor ofacademic achievement. Teacher degree level was also found animportant predictor of student achievement (Table 2).

Analysis indicated that when entered into the regressionequation with student characteristics and school quality indicatorsthe contribution of the variable ‘‘household possessions’’ becamenon-significant.

The final R of .50, an index of the goodness-of-fit of the finalregression model (Model III), demonstrated that the overall fit ofthe academic achievement model to data was acceptable.

In sum, the most important set of predictors was found to be theset of student characteristics, which accounted for 15 percent ofvariance in academic achievement. The set of family backgroundcharacteristics accounted for 5.4 percent of variance and the set ofschool-quality indicators accounted for 4.3 percent. The combina-tion family, student and school characteristics (Model III)accounted for .25 percent of variance in academic achievement.

6. Discussion

6.1. Family characteristics

Family background accounted for 5.4 percent of the totalvariations in academic achievement among urban poor students,which, although small, is still significant. Among the familybackground variables examined in this study, educational level offathers (at least a secondary education) as one of the SES indicators

had statistically significant and positive unique effect on variationsin academic achievement among the urban poor. That is, studentswhose fathers have at least secondary or higher level of educationtend to have higher academic achievement. This result confirmsthose of other studies on the effects of family SES on educationaloutcomes of children (Fuchs and Woßmann, 2004; Guncer andKose, 1993; Parcel and Dufur, 2001; McEwan and Marshall, 2004;Schiller et al., 2002; Willms and Somers, 2001; Woßmann, 2003;Yayan and Berberoglu, 2004). Another study in the Turkish contextby Guncer and Kose (1993) found that family background asmeasured by father’s educational level accounted for morevariance than school-related factors on the academic achievementof Turkish high school students. The finding that family income asmeasured by home ownership and household possessions had asignificant and positive effect on academic achievement was alsoconsistent with the results of other studies that found bothparental education levels and home ownership had significanteffects on children’s academic achievement in Turkey (Tansel,2002; Tansel and Bircan, 2006) and other countries (Al-Nhar, 1999;Bacolod and Tobias, 2005).

One interesting finding from this study with regard to familycharacteristics is that educational level of the mother (at least asecondary education) did not contribute significantly to explainingvariations in academic achievement. This conflicts with PISA 2000results, which suggested that students whose mothers havecompleted upper-secondary education attain higher levels ofreading performance in all participating countries (Fuchs andWoßmann, 2004). It is, however, in line with a study by Ma (1997),which found that educational levels of mothers in the DominicRepublic, a developing country like Turkey, did not have astatistically significant effect on math achievement. It should benoted that levels of education are in general quite low amongurban poor women in Turkey (according to the Student Ques-tionnaire, 53.5 percent of mothers had completed only five years ofprimary school and 12.8 percent were illiterate), as are the rates ofwomen wage-earners (General Directorate of Women’s Status andProblems, 1999). Thus, it may be argued that the finding of a lack ofcorrelation between academic achievement and mother’s educa-tional level is due to the similar SES among the mothers of studentsincluded in this study. This, in turn, implies that mother’seducational level affects academic achievement through themechanism of SES, or, in other words, that mother’s educationlevel is strongly moderated by mother’s SES. In light of this finding,future studies utilizing regression equations should includevariables related to employment and occupation of mothers toexamine their effects on school achievement.

Results of this study revealed that household size did not have asignificant effect on academic achievement, suggesting thatvariation in the number of siblings does not affect the amountof attention provided by parents per individual child with respectto school work. This result is consistent with results of case studiesconducted in developing countries that found that number ofsiblings does not contribute substantially or has a positive effect onchildren’s educational outcomes in developing countries (Buch-mann and Hannum, 2001). In contrast, studies conducted in theUnited States and some European countries (Downey, 2001; Parceland Menaghan, 1994) have consistently found a negativeassociation between large numbers of siblings and individualeducational outcomes.

6.2. Student characteristics

Results of this study revealed that the set of variablescategorized as student characteristics significantly accounted for15 percent of the variation in the academic achievement of urban


poor primary-school students in the Turkish context. Perceptionsof treatment by teachers had strong and positive unique effects onacademic achievement from among the set of student-relatedvariables (Table 2). Students who describe treatment of theirteachers as ‘very good’ and ‘good’ tend to have higher achievementscores than students who describe treatment of their teachers as‘bad’ and ‘very bad’. Student perceptions of number of friends theyhave in school also had a significant and positive unique effect onstudent achievement. Considering these two variables are relatedto student well-being at school, these findings are in line with theliterature. As mentioned earlier, well-being at school includesstudent perceptions of relationships with teachers and school-mates as well as opinions regarding school rules (Hoy andHannum, 1997; Samdal, 1998; Samdal et al., 1999). Researchershave stated that student well-being at school affects behavior andexam results as well as work attitude, achievement motivation andeffort, and thus school performance (Babad, 1996; Connolly et al.,1998). Other studies have also reported great positive effects ofschool climate, especially the teacher–student relationship, onstudent achievement and attitude towards school in schools withdisadvantaged students, including economically disadvantagedstudents (Schouse, 1996; Griffith, 1999). One possible explanationof this result is that a teacher–student relationship and schoolenvironment characterized by warmth and care may meet theurban poor student’s unmet needs for intimacy, warmth andsupport.

This study showed gender to have the strongest unique effecton student achievement levels. The finding that girls had betteraverage achievement scores than boys is consistent with theliterature, which shows that although boys outperform girls onmath and science tests (Farkas et al., 1990), girls receive highercourse grades than boys (Sammons, 1995; Veenstra and Kuyper,2004; Van Houtte, 2004). This trend has also been observed amongTurkish students (MONE, 2005). It is possible to argue that thecontinuing perception among villagers and the urban poor ofeducation as a privilege for girls also increases its perceived valuefor girls, thus increasing their achievement motivation and effort.

In line with expectations, total hours spent on studies per weekwere found to have a strong positive effect on academicachievement. However, student characteristic ‘‘homework com-pletion’’, was not found to be statistically significant. This resultcontradicts the results of other research which found the amountof homework completed by students to be an important predictorof school achievement (Postlethwaite and Wiley, 1992; Keith et al.,1986; Simmons and Alexander, 1978). A significant negativerelationship was found between academic achievement andavailability of someone to offer help with homework. This resultis consistent with a study by Epstein (1987) that found a negativerelationship between pupil achievement in math and reading testscores and parental help with homework. This negative relation-ship might be an indication that rather than helping regularly,parents or older siblings help only when a child needs help. Muller(1998) points out that parental response to adolescent needs interms of schoolwork is context-specific, that is, parents tend torespond when a child needs help. It may also be argued thatbecause of their own low levels of education, gecekondu parentsmay lack the knowledge and skills needed to assist their childrenwith homework and stimulate them intellectually. When thesefactors are taken into consideration, it becomes clear that moredetailed information is needed regarding the nature and extent ofthe help a child receives from family members.

In terms of perceived parental support and involvement,student perceptions of the level of parental follow-up regardinga child’s academic progress was not found to contributesignificantly to variations in academic achievement. This result

is consistent with the findings of Fine and Cook (1993), showingparental involvement in parent–teacher organizations (PTOs) inlow-income communities had no significant impact on studentachievement. Similarly Aypay (2003) concluded that parent–school relations did not have a significant effect on achievementand school choice of 14-year-old Turkish students. Research seemsto indicate that the effects of parental involvement on studentacademic achievement depend on both school characteristics andthe nature of parental involvement. For instance, Lee (1993) foundpersonal contacts between parents and teachers to be associatedwith poor student performance and behavioral problems. Whenstudents are having trouble with school, their parents are morelikely to become involved by maintaining contact with the school(McNeal, 1999). In Turkey, especially among the urban poor,parental involvement, including checking on student progress, isquite low. Only 16 percent of students interviewed in this studyreported that their parents visited school often. One reason for thisthat has often been mentioned by principals and teachers in Turkeyis that parents are frequently asked by school administrators tomake financial contributions they are unable to afford, ostensiblyto cover school expenses, despite the fact that education isprovided free by the state. Parents’ own low levels of educationmay also lead them to leave the education of their children up tothe schools; research has shown that parents with highereducational levels frequently manifest greater confidence in theirability to support their school-age children academically (Harmonet al., 1997 cited in Sukon and Jawahir, 2005, p. 554).

Another expected finding was that student attendance level,measured by total number of days a student was absent during thesemester, had a significant negative effect on academic achieve-ment.

The other student characteristics such as work status, gradelevel, total hours spent on leisure activities per week and level ofparticipation in extra-curricular activities, were not found to haveany significant effect on student academic achievement. Contraryto the literature regarding the relationship between work andacademic performance (Akabayashi and Psacharopoulos, 1999;Heady, 2003) whether the student combine school and work wasnot found to have significant effect on school achievement. Thismight be due to the nature of work engaged by working students inthis study. That is, nearly two-thirds of working studentsinterviewed were unpaid family workers (e.g. working in familyowned shop and other economic activities at home). Working in afamily owned shop may limit the hazards associated with workoutside home, allow students to attend the school more regularlyand spent more time for their studies.

6.3. School characteristics

The findings of this study revealed school characteristics tohave a significant independent effect on the academic achievementof the urban poor. Variations in school quality as measured byschool facilities, teacher–student ratio, class size, in-serviceteacher training and teacher education levels were found toaccount for 4.3 percent of the variation in academic achievementamong students.

Interestingly, teacher–student ratio was positively correlatedwith achievement scores. The finding that achievement scoresincrease as the number of students per teacher increases was in linewith Fuchs and Woßmann (2004), whose analysis of PISA 2000results showed a significant positive correlation between teacher–student ratio and student performance, but in conflict with otherresearch showing a significant negative relationship betweenteacher–student ratio and school achievement (Guncer and Kose,1993; Willms and Somers, 2001). A significant positive relationship


between teacher–student ratio and academic achievement may bedue to the greater availability of resources, such as better teachingaids and physical equipment and facilities, at larger schools. Withregard to this study, it should be noted that the average teacher–student ratio (31) of the participating schools is above the figuresuggested by educators for an effective school.

Although this study found teacher–student ratio to have asignificant effect on student academic achievement, class size (35)was not found to have a significant effect. This result is consistentwith Hanushek and Luque’s (2003) findings regarding the effects ofclass size on performance in various countries. According to theseresearchers, the estimated effects of reduction in class-size are notsystematically larger on science and math performance in poorercountries. In another study Rivkin et al. (2005) concluded thatalthough class size had little impact on the achievement of childrennot from low-income families, it had a positive effect on the mathand reading achievement of low-income children in the fourth andfifth grades. In light of this conclusion, the authors suggested thatpolicies aimed at reducing class size for the fourth, fifth and sixthgrades for non-low-income children would not be cost-effective.Fuchs and Woßmann (2004) have argued that while betterequipment and instructional material and better-educated tea-chers always result in higher achievement, smaller class size doesnot. Darling-Hammond (2000) has also mentioned that reducingclass size, when accompanied by the hiring of well-qualifiedteachers, contributes to student learning. The results of all thesestudies make it clear that differences in teacher quality have muchgreater affects on variations in achievement than differences inclass size. It may be argued that the finding of a lack of significantcorrelation between class size which is 35 and can be considered aslarge (Brewer et al., 1999) and academic achievement in this studydue to similarity in the characteristics of all public schools in termsof limited instructional materials (World Bank, 2005) and teachers’wide use of deductive instructional strategies such as lecture andrecitation in all classes (Onur and Engin, 1996; World Bank, 2005).Although it is not statistically significant, there is still a negativerelationship between class size and academic achievement ofurban poor primary-school students (Table 2).

A closer examination of the study results revealed that theeffects of the number of teachers with graduate or post-graduatedegrees or currently engaged in graduate studies and the numberof teachers who participated in an in-service training programduring the previous year were negative and statistically significant.This result confirms the results of Parcel and Dufur (2001) studythat found attending a school where a high percentage of teachersheld graduate degrees had a negative effect on changes in mathachievement. Goldhaber and Brewer (1996) found a statisticallyinsignificant association between the percentage of teachers withat least an MA degree and student achievement. Fuchs andWoßmann (2004) found that students performed significantlybetter in schools where teachers had a higher than average level ofeducation. This is especially true for degrees in pedagogy in therespective subject and for holding specific teaching certificates.However, in line with most past research, Rivkin et al. (2005) foundno evidence that holding a master’s degree improved teacher skills.The lack of clarity regarding the estimated relationship betweenstudent achievement and higher education of teachers brings intoquestion the widespread existence of pay scales that reward suchteacher characteristics, as with the newly instituted teacherpromotion system in Turkey, which awards teachers who obtain atleast a master’s degree a title and a salary increase.

The counterintuitive finding of this study that teacher level ofeducation correlated negatively with student achievement may berelated to the unavailability of necessary teaching materials inschools. According to PISA 2003 results, 80 percent of Turkish

school principals reported that student learning is hindered by alack of quality instructional materials (MONE, 2005), a problemthat is particularly acute in primary schools in poor neighborhoods.It can thus be argued that knowledge, competencies andproficiencies possessed by teachers do not necessarily translateinto teaching practice. Essentially, a teacher may know what to doand how to do it, but may be unable to put this knowledge intopractice in the classroom.

Finally, school facilities seemed to have a negative impact onstudent achievement, although the effect was not statisticallysignificant. This is understandable, considering the PISA 2003results of Turkey, in which more than two-thirds of schoolprincipals reported that an inadequate school infrastructureadversely affected math achievement of primary-school students.This adverse effect was well above the average adverse effect ofOECD countries (MONE, 2005). Furthermore, students whoreported using computers in primary schools were found to havelower cognitive performances on average than those who reportedhaving no access to computers at their schools. Similar findingshave been determined with regard to other facilities, such aslibraries (Berberoglu, 2004). A lack of books and a shortage ofteachers in Turkish schools were also mentioned more frequentlyas concerns among poorer households when compared towealthier ones (World Bank (WB), 2005). It is possible to concludethat merely equipping schools with such facilities is not enough toraise student achievement, rather, what matters most is whetherthese facilities are utilized properly. In this regard, much remainsto be learned as to how principals and teachers mobilize andorganize scarce instructional materials.

7. Conclusions and implications

This study investigated the relative importance of selectedfamily-, individual- and school-related factors in accountingacademic achievement of urban poor primary-school students.The findings indicate that the set of variables comprising studentcharacteristics, including grade, gender, work status, well-being atschool, scholastic activities and parental support, explained thelargest amount of variance (15 percent) in academic achievementamong the urban poor. Family background characteristics andschool quality indicators accounted for 5.4 and 4.3 percent ofacademic achievement, respectively.

Variables related to student well-being, such as perceptions oftreatment by teachers and number of friends in school, clearly hadsignificant positive effects on academic achievement. This suggeststhat educational policymakers take into greater consideration theaffective characteristics of teachers, such as their attitudes andexpectations from students, in order to improve school achieve-ment among the urban poor. Teacher training should equipcandidate teachers with the necessary knowledge and skills as wellas attitudes to work successfully with disadvantaged students,including those who are economically disadvantaged. It may beexpected that good teachers – those who can adapt a wide range ofteaching strategies to the specific needs their students and whohave high expectations from their students (Darling-Hammond,2000; Darling-Hammond and Sykes, 2003; Samdal et al., 1999;World Bank, 2005) – can go a long way towards increasingachievement among gecekondu children. This, in turn, wouldtransform schools into more attractive places for children andcould thus be expected to increase student attendance, which thepresent study found to be a significant factor in academicachievement.

Time spent on studies and the availability of someone to offerhelp with studies were also found to have significant effects onchildren’s academic achievement. Given the low level of parental


education, especially that of mothers, as well as the absence oflearning materials at home, schools in poor neighborhoods couldincrease academic achievement by providing students with after-school remedial sessions under a teacher’s guidance. Results ofprevious studies suggest that after school remedial sessions onschool subjects are related to student academic performance(Philips, 1997; Schouse, 1996).

Awareness of the fundamental role of education in producingsocial and economic disadvantages (Machin, 2006), coupled withthe understanding that children who experience favorablematerial conditions at home and at school achieve greateracademic success (Baharudin and Luster, 1998; Coleman, 1991),suggest that policies implemented in gecekondu areas to stimulateimprovements in human capital should target not only schools, buthouseholds as well. In this regard, instruction, materials andlearning experiences may be offered to parents to enable them toprovide a supportive learning environment at home. Such anapproach would also increase parental involvement and enhancethe school–community partnership. As Haghighat (2005) hasargued, strengthening community–school networks and creatingpositive school environments represent a significant means ofimproving academic achievement in schools located in neighbor-hoods in which poverty is concentrated.

A close examination of the study results indicate that whileschool facilities and class size do not have a significant effect onstudent achievement, teacher–student ratio and teacher training dohave a strongly significant effect. This is due to the fact that as publicschools in poor urban neighborhoods, and therefore subject toMinistry of Education rules and regulations with regard to resourceallocation, all the schools studied were equipped with more or lessthe same quality facilities and physical resources. In view of thehomogeneity of the participating schools, the findings of this studyshould be interpreted with caution when comparing them withfindings of other studies that have included public and privateschools from middle- and high-SES neighborhoods, where even stateschools are well known to benefit more from informal financial andin-kind contributions than schools serving poorer families.

The relationship between family background and academicachievement of primary school children brought to light throughthis study may be typical of other developing countries as well. Anumber of cross-cultural studies have found family background tobe less important than school characteristics in determiningacademic outcomes among students in less developed countries(Coleman et al., 1966; Fuller and Clarke, 1994; Heyneman andLoxley, 1983). Here, it is important to note that while this studyfound student characteristics to account for greater variance inacademic achievement than either family or school characteristics,some individual variables included within the set of studentcharacteristics – student perceptions of treatment by teachers, andstudent perceptions of having many friends – are closely related toschool climate variables in that they represent additions to schoolquality from a student perspective (Johnson et al., 1996; Hoy andHannum, 1997). In light of this understanding, it is possible toconclude from the findings that school characteristics, especiallythose involving social and human capital (e.g. teacher–studentrelationships, teacher degree level, teacher–student ratio) thatcontribute to a school’s ability to provide a positive environmentfor pupils are, in fact, more important than family characteristics aspredictors of academic achievement among the urban poor inTurkey. Such an analysis supports the investment in educationalresources, especially those that would improve teacher quality andschool environment, in order to increase student academicachievement.

Finally, it should be emphasized that the most comprehensiveregression model (Model III) employed in this study could only

account for approximately one-fourth of the variance in academicachievement registered among students. In other words, themajority of the variation in academic achievement among theurban poor remains unexplained by the selected independentvariables, which strongly suggests that further conceptual andempirical efforts be focused on identifying the additionalindependent variables related to academic achievement. Futurestudies may examine additional factors related to studentcharacteristics (e.g. differences in achievement levels uponentering school, self-esteem), family characteristics (e.g. homeenvironment, family–child interaction) and school characteristics(e.g. classroom processes, school climate, teacher motivation) tomaximize the amount of variance explained in academic achieve-ment among the urban poor. In addition, this study suggests thatstructural equation modeling techniques can be used to explorethe complex and reciprocal relationship among family-, indivi-dual-, and school-level variables related to academic achievementof urban poor primary-school students.

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Factors influencing the academic achievement of the Turkish urban poor