metadata: authors: 0: author: Lockheed, Marlaine E.
1: author: Fuller, Bruce
2: author: Nyirongo, Ro
count: Malawi,Thailand
docna: 0: docna: Family background and student achievement
docty: Policy Research Working Paper
subtopic: Labor Markets,Educational Sciences,Educational Institutions & Facilities,Educational Populations,Energy Policies & Economics,Education for Development (superceded),Educational Policy and Planning - Textbook,Effective Schools and Teachers,Education For All
teratopic: Gender
abstracts: cdata!: Past research from Third World countries
            shows that school related factors have stronger effects on
            student achievement than do family background factors.
            However this paper finds that prior work suffered from
            conceptual and methodological flaws, and it suggests that
            once these shortcomings are addressed, the influence of
            pupil background may be greater in developing countries than
            was earlier indicated. The first section of the paper
            reviews the literature on family effects on student
            achievement in developing countries. The second and third
            sections are studies on Thailand and Malawi, and the final
            section discusses the findings in relation to educational
            policy. In sum, these findings indicate that researchers
            should be more careful in their modeling of family and
            school characteristics in the developing world. Failure to
            recognize the family's early and apparently lasting
            influence is a failure to accommodate education programs to
            indigenous realities.
geo_reg_key: 517198,517195,517191
repnme: repnme: Family background and student achievement
display_title: Family background and student achievement
listing_relative_url: /research/1988/07/700690/family-background-student-achievement
topicv3: Teachers Management m1326119 1523,Textbooks m1326802 2129,Education m1327048 470,Power and Electricity Sector m1327094 515,Jobs m1503931 2670
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Gender
origu: Policy Plan & Prog Review Dept
no_of_pages: 41
model_extractions: t **Policy, PlannIng, and Re_arch**

# **Eduoatlon and Employm nt|**

Past research in developing countries has shown that school-related influences have a greater effect on student achievement than does family background, a finding that contrasts sharply with research in industrialized countries. This has led to the conclusion that schools in developing countries are more effective than schools in industrialized countries.

But the earlier work suffers from conceptual flaws. It has defined family background in material terms and failed to consider other motivational factors. Earlier research has also used measurements (such as level of parental education and occupational status) more appropriate to the industrialized world than to the class structure of the country being studied.

These variables were more consistently related to pupil achievement than were the conventional indicators, parental education and occupation.

If, as these two studies indicate, family background is as important to students in developing countries as in industrial ones, two types of action are suggested. First, education programs could be designed to take into account family background characteristics of students. They might include early intervention programs, such as preschool or a change in school schedules to better meet patterns of child labor. Second, education systems could work to improve student motivation and parental support directly by promotg the importance of education.

Two studies of student motivational behavior in Thailand and Malawi address these shortcomings. In the Thailand study, conventional measures of family background (parental education and occupation) were kept constant. Student achievement in both urban and rural settings was related to such motivational variables as educational expectations, attitudes and effort.

The Malawi study employed definitions of family background more relevant to a developing country: labor demands placed on children, basic attributes of houses, and mother tongue.

In sum: Researchers should be more careful in their modeling of family and school characteristics in the developing world. Failure to recognize the family's early and apparently lasting influence is a failure to accommodate education programs to indigenous realities.

This paper is a product of the Population and Human Resources Department, Education and Employment Division. Copies are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Rosemarie Rinaldi, room S-6027, extension 33278.

The PPR Working Paper Series disseminates the findings of work under way in the Bank's Policy, Plaming, and Research Complex. An objective of the series is to get these findings ou. quickly, even if presentations are less than fully polished. The findings, interpretations, and conclusions in these papers do not necessarily represent official policy of the Bank.

Copyrignt 0 1988 by the International Bank for Reconstruction and Development/he World Bank
# Table of Contents

|Family Background and Student Achievement|3|
|---|---|
|A Broader Conception of Pupil Background|5|
|Study 1: Thailand|8|
|Study 2: Malawi|17|
|Conclusions|21|
family Effects on Stndent Achievement **In Thailand and** Malawi

# INTRODUCTION

Past research from Third World countries shows that school-related factors have stronger effects on student achievement than do family background factors. This finding contrasts sharply with evidence from industrialized countries, where family background characteristics explain substantially larger proportiors of variation in educational. This has led to the optimistic inference that Third World schools &re more effective than schools in industrialized countries, both in raising achievement and in providing routes for social mobility.

However, prior work suffers from conceptual and methodological flaws. Two important conceptual shortcomings are: (a) limiting the concept of family background to material aspect of class, and failing to consider other aspects of family background, such as motivational variables, that influence student performance, and (b) using measures of family background (such **as** parental educational attainment and occupational status) useful in for industrialized settings rather than indicators of class that **are** more culturally valid for the country in which the study is conducted. Methodologically, prior research suffers from: (a) being limited to cross-sectional data that are incapable of distinguishing initial level of achievement from achievement gain over time and that tend to confound the effects of school and family characteristics, and (b) seldom analyzing school and family effects separately for different regions within countries; specifically, past research has rarely included non-urban samples. We suggest that once these conceptual and methodological shortcomings are addressed, the influence of pupil background may b¢ greater in

-1 -
developing countries than the modest effects suggested by earlier findings.

This paper presents **the** results of two studies of family background **offacts** on student achievement that, taken together, address the shortcomings of past research. We argue, first, that attention ahould be given to a greater variety of student background variables that may affect achievement by mediating, supplemknting or substituting for conventional background variables. In particular, we are interested in perceptions held by children that may motivate higher school performance. The first study, **an** analysis of longitudinal data from Thailand, explores the effects of **several** such motivational variables in explaining how family background influences student achievement over **time.** Second, we raise the question of whether the influence zfi stadent background on achievement can be adequately tested in the Third World by relying on conventional measures of class, borrowed from industrialized societies. Culturally specific indicators may show distinctly greater influence over student achievement than such imported indicators as parents' occupational status and formal educational attainment. The second study, an analysis of crossectional data from Malawi, examines how estimates of student background effects on learning can be improved by utilizing material indicators of class that are more relevant to local conditions.

The paper is organized as follows. In this section, we review the literature on family effects on student achievement in developing countries. In the second section, we present Study 1 on Thailand, and in the third section we present Study 2 on Malawi. In the final section, we discuss our findings in relation to educational policy.

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# **FI dly** background **and** student achiev_nt

Education advocates in Third World governments and international agencies have been buoyed **in recent years** by evidence that the offect of school characteristics on student achievement, when compared with the effect of student family background, **appears** to be greater in Third World countries than within industrialized countries. For example in their widely cited reanalysis of International Education Association (IEA) and other data from 29 countries, Heyneman and Loxley (1983) report that--taken altogether--characteristics of schooLs in developing countries explain a greater share of the variance in student achievement than is explsined by student background characteristics. In addition, a significant negative correlation **was** found between the percentage of variance explained by school characteristics and the nation's level of wealth. As a case in point, they note that 27 percent of the variance in achievement among children in India was attributable to school factors while only 3 percent -as explained by variation in background characteristics. In contrast, achievement levels within industrialized countries were explained mostly by student background. Similarly, a recent review of approximately 60 empirical studies of determinants of achievement in developing countries found that school characteristics were related to student achievement in the vast majority of studies, after holding constant student social class background (Fuller, 1986).

Yet there is strong evidence that student family background contributes significantly to both educational attainment and achievement in developing countries. Family background affects the probability that children enroll in, attend, and complete various levels of education. For example, analyzing historical data from the

**-3-**
philippines, Smith and Choung (1986) fou,nd that parental occupational **and** educational **level** shaped children's school attainment, with the **some** level of magnitude, **since** the **early** 20th century. Similarly, using household income **as** a rough proxy for student social class, Chernichovsky and Meesook (1985) found significant educational attainment effects in Indonosia. In Nepal, Jamison and Lockheed (1987) found that parental and grandparental social class (landholding, ca-te, schooling) strongly determined child school participation. Adult literacy **was** *lso measured, and found to **be** strongly associated with **years** of schooling, a finding recently repeated in Brazil (Psacharopoulos and Arriagada, 1987). This study underscores tho importance of separating school attainment (enrollment and persistence) from level of academic achievement while in school **as** two distinct outcomes.

Students' family background also affects lkarning while in school. For example, Schiefelbein and Simmons (1981) found that social class significantly helped predict achievement in 28 of 37 Third World studies reviewed. Moreover, family background may be quite salient for familiar subjects, such **as** reading, and less so for subjects relatively less familiar to many Third World communities, such as science. On this point, Schiefelbein and Simmons noted that student family characteristics accounted for a higher proportion of variance in reading achievement than in science achievement in multivariate stu .ies from India, Peru, and Malaysia. And Heyneman and Loxley's findings, while widely celebrated, applied only to achievement in science.

Third, family background appears more strongly to deternine student achievement within urban schools, whereas school factors have

- 4 -
greater influence on the achievement of rural and va-y poor children (Brazil, Wolff 1970; Iran, Ryan 19731 Indonosia, Haron 1977). This pattern may result from less variation in social class within rural **azdas** or to the fact that Western measures of class **are** even less valid in rural **areas** (compared to Third World urban areas).

In sum, family backgro appears to be more influential in developing countries when (&, **the** formal school is highly institutionalized, (b) class structures **are** more defined, and (c) in subjects that are familiar or linked to parentO' own knowledge. In contrast, when the school is foreign to the setting and teaches unfamiliar areas of knowledge (such **as,** a rural school providing science instruction), school characteristics appear to **be** more efficacious than family background.

# A Broader Conception of Pupil Background

Studies of family background effects on student achievement in Third World settings would be improved by the inclusion of two types of variables: (a) a broader range of family background indicators, and (b) more culturally valid indicators of social and material background.

Broader range of indicators. Most fundamentally, the construct of "pupil background" should be broadened to include other aspects of parents and the child that may operate independently of material aspects of class. We focus on two sets of factors in this regard. First, the value placed on staying in school and achieving well has been found to vary among parents within several societies, including the United States, Japan (Hess and Holloway 1984), Mexico (holloway et al. 1986), and Taiwan (Stevenson et al. 1985). Parents' own reports

-5-
of value placed on schooling and the frequency with which they communicate this priority is *s*ociat*d with higher achievement in reading and mathematics independent of parents' occupational and educational own schooling (at least among young children in Japan and the U.S.; Hess et al. 1980). This communication of value may take the form of expectations for higher levels of school attainment, greater support (both material and non-material) for learning, or communication regarding the relevance of education for adult occupational attainment. Yet these factors have received slight attention from researchers working within developing countries. A notable exception is Jamison and Lockheed's (1987) research on determinants of child schooling in Nepal, which examined a number of such variables, including p_..atal attitudinal modernity and demand for child education; both were found to have strong and posit..ve effects on child school participation. In a parallel study undertaken in Thailand, Cochrsne and Jamison (1982) found that parental aspiration for educa,-ion was the most important predictor of male educational attainment, while parental landholding (an indicator of wealth) was the most important predictor of female educational attainment. Another example is provided by a study of urban Grade 10 students from Sri Lanka, (Niles, 1981) which found that family social class (parental education and occupation) and parental interest in the child's progress and parental aspirations were strongly associated with student achievement, and taken together with material possessions in the home (non-significant) and school factors (only modestly significant) accounted for 49% of the variance in student achievement.

Second, pupils vary in the effort they expend on school work and the extent to which they feel efficacious in performing well. This is

-6-
an old idea in **the** school **effects** literature. Coleman et al (1966), for instance, found that students who perceived that their achievement **was** due to their own efforts, end not to **their** teachers or school, achieved **at** higher levels (controlling for their class background). More recently, Brookov-r *t **al.** (1979) found that pupils achieved **at** higher levels when they felt that their effort on school work **was** recognized **and** rewarded by their teachers (again, independent of pupils' social class). Natriello (1987) also found that whera students' work **was** more frequently and carefully evaluated, achievement levels were higher. For a recent review **of** factors related to mathematics and science achievement, **s*e** Lockheed et al. (1985).

Relevant social class indicators. Most studies of family background characteristics in developing countries **have** employed two indicators of social **class:** parental educational attainment **and** occupational status. As H-yneman has noted, in Third World settings there may be little variation in terms of education or occupation; educational levels of adults **are** uniformly low, and occupations are preponderantly related to rural agrici lture (at least in the lowest income countries). Yet social class differences are quite pronounced, and have been found to strongly effect child school participation and performance. For example, in the Jamison and Lockheed study, which employed indicators of parents' social class that were relevant to the Nepalese setting -- amount of land owned by the father, his level of literacy, caste membership, and district of residence, capturing inter-regional differences in wealth -- child school participation was strongly determined by these social class elements.

- 7-
In sum, the true influence of pupil background on achievement **can** be better **estirated** if we take into account: (a) those family background characteristics -- **garental** values **and** press to achievement **and** the child's own effort and perceived efficacy -- that appear to operate independently of conventional aspects of class (for **the** few countries in which **theme** factors have been studiedi, **and** (b) better indicators of **material and** *octal **aspects** of class.

# STUDY **1:** THAILAND

Our first analysis **examines** family effects on Grade 8 mother **s achievement** gain in Thailand, and focuses on a broader range of background indicators, specifically motivational variables.

# Method

Sample. Data **were** drawn from the Second Interntional Mathematics Study, conducted under the auspices of the International Association for the Evaluation of Educational Achievement. The IEA SIMS sample comprised 99 mathemathics teachers and their 4030 eighth-grade students and was derived from a two-stage, stratified random sample of classrooms. The primary sampling units were the twelve national educational regions of Thailand plus Bangkok. Within each region, a random sample of lower-secondary schools was selected, with replacements. At the second **stage,** a random sample of one class per school was selected from a list of all eighth grade mathematics classes within the school. The esulting sample represented a 12 sample of eighth grade mathematics classrooms within each region.

At both the beginning and end of the school year, students were administered a mathematics test covering five curriculum content areas

-8-
(agrithmetic, algebra, geometry, **statistics and** measurement). ftudents also completed a short background questionnaire at the pretest **and a** longer **ort at** the poattest administration. In the following sections, a description of each of the variables analyzed in **this** paper **is** provided; definitions of **variables and** summary statistics **are** presented **in Table 1.** Mathematicn achievement **measures.** The **IE** developed five mathematics testi for is in SIMS, one forty-item instrument (the core test) and four thirty-five item instruments (rotated forms A through D). The five test instrtments contained roughly equal proportions of items from **each** of five mathematics curriculum content **areas.** In Thailand, students were pretested using the core test and or. rotated form. At posttest, students again took the core test and one rotated form, but **were** prevented from repeating the rotated form taken at pretest. In this analysis, we created formula scores from the four rotated forms, after they were equated (through the core form) to adjust for differences in test length and difficultys scores were adjusted for guessing. A complete description of the equating and score development procedure is provided in Lockheed, Vail and Fuller (1987).

Family backzround indicators. Basic information about each student included his or her sex, age, number of older siblings, paternal and maternal education, paternal and maternal occupational status, and home language. Parental occupation was classified into four international categories: (a) unskilled or semi-skilled worker, (b) skilled worker, (c) clerical or sales worker, and (d) professional or managerial worker. Because paternal and maternal occupational status - were highly correlated (r .39) we analyzed the effects of paternal

-9-
occupational status only in this paper. Highest parental education was **also** classified into four categories: (a) vary little or no schooling, (b) primary school, **(c)** secondary school, **and** (d) college, university or some form of tertiary education. **Because** paternal and maternal educational attainment **were** also highly correlated (r - .58), we aaalyzed the *affects of maternal educational attainment only. District level per capita income **was** derived from World Bank estimates.

Student educational expectations were measured by a single item that asked about the number or year more of full-time education the student expected to complete.

Parental encouragement was measured by a four-item index composed of Likert-type statements a-king students to describe their parent's intarest in and encourageme for mathematics achievement, for example "My parents encourage me to learn **as** much mAthematics as possible"; response alternatives ranged from "Exactly like" the student's parent (- 1) to "Not at all like" the student's parent (- 5). The four items comprised a single factor, with principal component factor loadings ranging from .72 to .83 and communality of 2.43. A low score represented greater perceived parental support.

Student attitudes. Three indices of student attitudes were analyzed: (a) perceived mathematics ability, (b) perceived usefulness of mathematics, and (c) motivation toward mathematics achievement. All were developed from a factor analysis of the student attitude survey, which contained Likert-type items having response alternatives ranging from "Strongly disagree (- 1)" to "Strongly agree ( 5)." Factors were initially identified through varimax factor analyses, and then confirmed through principal component analyses, from which factor scores were constructed. Perceived mathematics ability (or mathematics

- 10 -
self-efficacy) **was** formed from five items (e.g.: **"I** am not so good **at** mathamatics") having principal component factor loadings ranging from .63 to .79 and communality of 2.55; a low value represtnted a positive attitude, due to the reverse wording of the items. Perceived usefulness of mathematics was formed from eight items **(e.g.:** "Mathematics is important to get a good job") having principal component factor loadings ranging from .37 to .61 and communality of 2.26. Motivation was measured by three items (e.g.: "I want to do well in mathematics") having principal component factor loadings ranging from .71 to .81 and communality of 1.77.

Stu.dent effort was measured by the number of hours the student reported spending on homework during the previous week.

# Results

This section is divided into four sections. First, we report the effects of family background on pretest mathematics achievement, using a conventional cross-sectional approach, and on achievement gain, taking advantage of the longitudinal design of the study. Second, we examine family background effects on the mediating variables of student educational expectations, perceived parental encouragement, attitudes and effort; this analysis is conducted first without statistically controlling for student pretest achievement and then second with such statistical controls. Third, we report the effects of family background and mediating variables on achievement gain. Finally, we report differences for rural and urban schools.

Family back2round effects on student achievement. Cross-sectional analyses of family background effects on student achievement typically find statistically significant, albeit modest, effects. Our
cross-sectional analyses of determinants of mathematics achievement in Thailand are consistent with previous findings. We found statistically significant effects on both pretest and posttest scores for paternal occupation, maternal education and district-level per capita income and less strong but statistically significant effects for use of language of instruction at home and for its interaction with district-level income (Table 2, columns 1 and 2).

Students having fathers with more professional occupations and mothers with higher levels of education had higher levels of eighth grade mathematics achievement. Students in wealthier districts and those in families using the language of instruction at home also scored higher on both tests. The interaction between district wealth and use of language of instruction at home was statistically significant, with the negative sign on the coefficient indicating that these two variables substitute for one another. The total variance in achievement explained by family background variables, however, was modest, with 7Z explained at both pretest and posttest.

Our longitudinal analysis, moreover, showed little effect of family background effects on posttest, once pretest achievement was statistically controlled. Of the family background factors examined, only district-level per capita income exerted further influence on student achievement gain (Table 2, column 3). In the next section, we examine why this apparent lack of effect is misleading.

Family backiround effects on parental support, student attitudes and effort. In the previous section **we** noted that conventional measures of family social class background, although correlated with initial and final levels of eighth grade mathematics achievement, contributed little to student achievement Rain over time. Presumably,

> - 12 -
this was **because** by the eighth grade, family characteristics **had** completed their influence over achievement. However, families continue to influence student achievement by providing material and non-material support for learning activities, by raising children's educational expectations, and by reinforcing student motivation and effort. In this section, we examine the extent to which such important motivation variables **are** affected by family background.

Family background effects on six motivation variables **are** reported in Table 3. Overall, little variance in parental support, student attitudes or effort was explained by conventional social class background variables (variance explained ranged from 0 to 62). However, several effects were statistically significant, and are reported here. First, we found significant gender-related. effects. Boys reported lower educational aspirations, **less** parental encouragement, lower valuing of mat!hematics and less motivation in mathematics than did girls. However, they reported higher perceived mathematics ability than did girls, although in actuality, there were no **sex** differences in achievement. Second, conventional social class measures were significantly related to the mediating variables. Higher paternal occupational status and maternal educational attainment levels were positively related to higher levels of student educational aspirations, perceived parental encouragement, and. motivation. In addition, paternal occupational status was positively related to student perceptions of mathematics as useful, and maternal education was positively related to greater student effort. Finally, district per-capita income was positively related to educational aspirations.

- 13 -
Effects of backaround factors on motivation variables, with initial achievement held constant. After the effect of initial mathemtics achievement was statistically controlled, family background variables continued to affect five of the **six** student attitudes and perceptions; they had no effect on student effort (Table 5). With protest achievement held constant, boys still reported higher level of perceived ability than girls, and lower levels of perceived parental encouragement, educational expectations, motivation and p-rce-ved utility. With initial achievement held constant, paternal occupation and maternal education were still significantly related to student *ducational expectations, perceived parental support and motivation. Surprisingly, the higher the district-level per-capita income, the less students reported mathematics **as** being relevant to their future employment.

Effects of motivation variables on student l1arnint zain. As **we** noted previously, the main impact of family social status and student background characteristic **was** through initial performance levell once established, background characteristics had little additional effect on achievement gain (Table 2, column 3). By comparison, student educational expectations, student attitudes and student effort were positively related to learning zain (Table 4).

Controlling for the effects of pretest achievemont and family characteristics, five of the six motivation variables--the exception was perceived parental support--were positively and significantly related to posttest student achievement. The fact that perceived parental support is unrelated to achievement gain is surprising. It may be the students are unaware of parental support or that parents

- 14 -
may not have specific opinions about mathematics (as compared with **reading,** for example).

These findings have important implications for understanding achievement among students in developing countries, where many students come from rural low-income families lacking material supports for learning.

Most research has attended to differences in material support between low-incomee and higher income children. The argument is made that greater material support is available to students from wealthier, better educsted families and less to students from poorer, less educated families. This difference in material wealth has been claimed to explain the clear differences in achievement between the two groups. The evidence of this study, however, suggests that there may **be** a different explanation. Students from wealthier and more educated families, who are largely urban residents, may perceive that stchooling is more important for thu5r futures than do students from rural settings. Schooling is more compatible with urban students' goals, and therefore parental support and student attitudes have more positive effects for them. To explore this question further, we analyzed the effects of family background on student achievement gain, separately for urban and rural students.

Urban rural differences. To test the hypothesis that parental support and student attitudes would have stronger effects for urban students than for rural students, we separatesd the sample into two groups, those from urban districts and those from rural districts. All analyses were reconducted, but only selected ones are reported in Tables 6 and 7.

> - 15 -
Family background accounted for relatively little protest achievement variance in either type of school **(62** for students in urban schools **and** 7X for **students** in rural schools). The effects of maternal education, paternal occupation, **sex** and district per-capita income **were** statistically significant, although not consistent for the two groups (Table 6, columns 1 and 2). For both urban and rural children, maternal education **was** strongly associated with pretest achievement. For urban children only, paternal occupational status **was** associated with pretest achievement, while for rural children only, district-1. **el** per capita income was positively associated with pret it achievement.

The failure to find significant sex differences in achievement for the total sample may **be** explained by the rural-urban differences. In urban schools, girls outperformed boys by 1.2 points, but in rural schools, boys outperformed girls by 1.0 points. Since the urban and rural samples were approximately equal in size, these effects would cancel each other out.

Holding constant stadent background characteristics, we found that student educational expectations, attitudes, motivation and effort were positively related to student achievement gain in both urban and rural settings; also, in both settings, perceived parental encouragement was unrelated to learning gain (Table 7). In both urban and rural settings, family background characteristics that were significantly related to initial levels of achievement were unrelated to gain, except insofar as they operated through other variables.

- 16 -
# STUDY 2: MALAWI

Our second analysis examines social class effects on achievement among a modest sample of 105 primary school students in **the** east African nation of Malawi. Here we focus on material facets of class that are relevant to a particular Third World setting, moving beyond Western indicators.

# Method

Samle. Fourth- and seventh-grade students from 11 urban and 10 rural primary schools (most Malawi primary schools include 8 grades) were randomly selected and interviewed, **as** part of a project evaluation conducted by World Bank staff. Interviews were conducted in the local tribal language, although government staff doing the interviews did not necessarily come from the local tribe. Schools selected were spread across the country's three administrative regions. Given resource constraints, selected schools tended to be close to paved roads, which biased the sample, and under-represented children of remote subsistence farmers. Nevertheless, variation in class background was great, as detailed below.

Achievement measures. Students were tested in both mathematics and in Chichewa, the state-sanctioned national language. Each exam consisted of ten items, developed by a group of primary schools teachers and reflecting the curriculum they covered in their own classes. Items from the pool developed by the teachers were field tested and a final set of items, with a reasonable range of difficulty were selected for inclusion in the final instrument. The Chichewa exam included prima-ily vocabulary items. The mathematics exam included seven one-step computational problems and three, more

- 17 -
difficult, word problms. Since students from **grades** 4 and 7 were included, raw test scores were converted to standardized scores, and grade-level **_was_** included as **a** control variable in the regression models.

Setting-specific indicators of social class. In the Malawi study, we focused on material aspects and measures of class that are more relevant to Third World settings, moving beyond the global constructs historically used within industrialized nations. For instance, we asked pLpils about seven different work tasks they might engage in after school. Four dealt with farm-related activities (feeding livestock, carrying fodder or water). Other tasks wore more general, taking care of siblings or preparing meals, for instance. We also asked pupils and their headmasters about housing conditions, particularly whether families lived in thatched-roof huts or in Western structures. Students were asked whether their houses had electricity and whether their parents owned a radio. Students also identified their mother tongue. We were especially interested in whether their parents spoke Chichewa, the dominant tribal language, or one of the more than 35 other tribal languages spoken in Malawi. In addition to these situation-specific measures of class, conventional indicators were also used: parents' occupation and schooling levels.

Analysis. Our analysis examined the influence of these indigenous measures of class on math and language achievement. OLS estimates were run for all students, then separately for students in rural and urban schools. Regression models for all students included a control on whether he or she attended an urban or a rural school. In some instances, attendance at an urban school was neaatively related to achievement. Thus, while urban children generally come from families

- 18 -
of higher social class, the over-crowded and under-staffed nature of urban primary school may offset the (urban) advantages of family background. A full analysfi of this issue is beyond the scope of the present paper. But this effect did necessitate **at** least controlling on the type of school attended.

# Results

Table 8 reports on definitions and mean levels of all variables included in the analysis. The sample included an over-representation of families in skilled, modern-sector jobs. Nationwide, only 32 percent of all adults **are** engaged in non-farm occupations nationwide, and this includes household heads that **have** small plots but commute" to the city to work **as** street vendors or in semi-skilled wage jobs. Yet a disproportionate number of sampled students reported that their fathers were employed in skilled occupations, a mean of 2.7 on the occupational scale that ranged from white-collar professional (-4) to subsistence farmer (-1). Headmasters estimated that 42.7 percent of all families came from farming households and that 56.2 percent lived in thatched-roof houses. The strength of this sample is that variation is substantial. A representative sample would have yielded a distribution heavily skewed toward subsistence farmers, constraining the normality of distributions. Nevertheless, caution is warranted in generalizing broadly from our results.

Note the mean scores on the mathematics and Chichewa exams (our dependent measures). For Chichewa, the mean was 5.5 with a standard deviation of 2.3; for mathematics, the mean was 3.8 with a standard deviation of 2.1. Below you will see that our findings are

- 19 -
more robust in explaining variation in Chichews achievement. This may be due, **in** part, to the better distribution of , it scores. Table 9 reports alternative specifications for estimating pupil achiovement from our various indicators of social class. The first column reports **a** regression of the total test score on *11 measures of class. Pupils coming from houses with electricity did better on the achievment exams. The interaction of having more work tasks after school and living in a thatched-roof structure negatively influenced achievement. Curiously, th poercent of families coming from farming backgrounds (as estimated by the headmaster) was positively related to achievement. The direction of this effect is difficult to explain. It may indicate that parents who own their land, compared to farmhands on estates or unskilled urban workers, provide stronger encouragement of school achievement. This variable might also be a stronger proxy for attendance at a rural school, which are typically smaller and display **a** lover student:te*cher ratio than urban schools. In sum, the full model explains 21 percent of the variance in achievement with moderate derees of freedom. Statistically insignificant (p).10) exogenous variables were then allowed to step out of the model, to test for stability in the coefficients held by the significant predictors. As expected the r-squares dropped following this procedure.

Similar models were run for the Chichewa and mathematics scores separately. For Chichewa, family background explained a larger share of the variance. The full model explained 27 percent of the variance. The strong negative effect from urban-school attendance arises here. The region's wealth and housing with electricity exerted a positive influence on Chicheva achievement. The interaction of after-school

- 20 -
work **tasks** and residing in a thatched-roof hut **again was** negatively related to achievement. Models estimating mathematics achievement were **less** efficacious in explaining **variation.** Table 10 reports reduced models, splitting the sample between students attending urban and rural schools.<sup>In general, social class</sup> factors more strongly explain achievement<sup>in rural schools. This is</sup> especially true with regard to performance<sup>on the Chichewa exam.</sup> Rural pupils whose mother tongue was Chichewa, not surprisingly,<sup>did</sup> better on the language test. Rural pupils<sup>from homes with electricity</sup> and radios also performed at higher levels. R-squares<sup>reached 35</sup> percent in explaining variation in rural pupils'<sup>performance, although</sup> th, degrees of freedom **are** quite low for the split<sup>sample.</sup> In sum, indicators of class more relevant to the<sup>Third World</sup> setting -- labor demands placed on children, basic attributes<sup>of</sup> houses, and mother-tongue -- were more consistently<sup>related to pupil</sup> achievement than were global, Western proxies.<sup>This study does not</sup> inform us **as** to how **these** largely-material facets of class operate on the child to lower school achievement. However,<sup>the consistent</sup> effects of situationally-relevant measures of class suggest that researchers working in Third World settings<sup>have inadequately</sup> specified family background factors in the past.<sup>Studies that employ</sup> only constructs of class from Western industrialized settings may retsult in underestimating the actual achievement effects of class.

# CONCLUSIONS

This paper has examined the effects of two<sup>types of social class</sup> background factors on enhancing the academic<sup>achievement of children:</sup> (a) motivational characteristics of families that add to, mediate or

- 21 -
substitute for material background **character±sties, and** (b) more valid and culturally relevant indicators of social class and mAterial family background characteristics of children.

The Thailand study provide strong evidence that motivational variables influence achievement. Holding constant conventional indicators of student backgtound (gender, parental education and occupation) we found that student educational expectations, attitudes, motivation and effort were positively related to student achievemsnt gain in both urban and rural settings. In both urban and rural settings, conventional family background characteristics that were significantly related to initial levels of achievement were unrelated to gain, except insofar as they operated through the motivational **variables.** The Malawi study demonstrates that indicators of family background more relevant to the Third World setting, such as labor demands placed on children, basic attributes of houses, and mother-tongue, were more consistently related to pupil achievement than were conventional indicators of parental eduzation and occupation.

If family background is as salient in developing countries as it is in industrialized countries, what implications does this have for educational policy makers or development advocates in planning aducation programs in the Third World? These two studies suggest at least two important avenues for action.

First, education programs could be designed that specifically take into account the family background characteristics of students. This might involve early intervention programs, such **as** preschools; in-school intervention programs, such as changing school hours and calendars to better meet local patterns of child labor; or

- 22 -
alternative school programs, such **as** distance education. Second, education systems could undertake to improve student motivation<sup>and</sup> parental aupport directly, through local informational **meetings and** other mechanism to promote awareness of the importance **and** benefits<sup>of</sup> education. In general, these types of interventions<sup>have been tried,</sup> with **various** degree of success, in developing countries,<sup>particularly</sup> with respect to the education of girls (Lycette,<sup>1986). The specifics</sup> of appropriate interventions will undoubtedly be t_ermined by local conditions, but a clearer understanding of how families<sup>affect</sup> achievement in Third World settings will better<sup>inform appropriate</sup> educational decisions.

Finally, researchers should more carefully model<sup>the influence of</sup> family **and** school characteristics of achievement in the Third World. Misspecification of family background antecedents will **lead** to over-estimates of the school's real effect, especially when<sup>levels of</sup> class and school quality are colinear. Optimism<sup>about the school's</sup> potential influence in the Third World need<sup>not</sup><sup>**be**dampened. But if</sup> we fail to recognize the family's early and apparently<sup>lasting</sup> influence, we will unknowingly fail to accommodate<sup>educational</sup> programs to indigenous family and class<sup>realities.</sup>

- 23 -
Tabim 1: Variable Namms. oniaMrtiam. mmm andi Standard Owatiamlow Thluiland. 1291-2

|||||S<br>|amie<br>|||
|---|---|---|---|---|---|---|---|
|Variable|Oescriptiona|To<br>|talb<br>|Ru<br>|ralC<br>|Ur<br>|band<br> <br>|
|||Iban|S.D.|Mean|S.O.|Mean|<br>S.D.|
|YROT|Posttestmthscore|11.89<br>|<br>4.46<br> <br>|0.52<br>|4.32<br>|13.09<br>|<br>4.50<br> <br>|
|XROT<br>|Pretest mth scare<br>|8.58<br>|<br>3.77<br> <br>|7.38<br>|3.57<br>|9.71<br>|<br>3.85<br> <br>|
|XSEX<br>|Sex (lufemale; 2Ie)<br>|1.53<br>|<br>.24<br> <br>|1.54<br>|.25<br> <br>|1.52<br>|<br>.24<br> <br>|
|XAGE<br>|Age (In amnths)<br>|171.13<br>|<br>4.48<br> <br>|172.15<br>|<br>4.31<br>|170.20<br>|<br>4.53<br> <br>|
|YFOCCI<br>|Father's occupatlonal status (11low;**4hil0g)**<br>|2.39<br>|<br>**.45**<br> <br>|2.25<br>|.40<br>|2.52<br>|<br>.48<br> <br>|
|YMEDUC<br>|Mother'seducatlonal attalrunt (1.10w; 4h10Ih)<br>|1.95<br>|<br>.38<br>|1.80<br>|.33<br>|2.09<br>|<br>.41<br> <br>|
|HCALC<br>|Calculator at hore (lbyes)<br>|.23<br>|.22<br>|.21<br>|.20<br>|.38<br>|<br>.23<br>|
|SPCI81<br>|01st, Iet Per Capita lnOr (In bhats)<br>|13495.0<br>|8 2547.38<br>|9208.07<br>|1247.U<br>|17363.0<br>|1839.15<br> <br>|
|YHLANG<br>|Lse langme of Instructlon at hame (1 yes)<br>|.52<br>|.24<br> <br>|.47<br>|.25<br>|.56<br>|<br>.24<br> <br>|
|YMOREE<br>|D Educatloai elaectatlos (1-low)<br>|3.71<br>|<br>.46<br> <br>|3.59<br>|.50<br>|3.82<br>|<br>.42<br> <br>|
|YPAREN<br>|C Parental mncouragnt (1uhlgi)<br>|2.14<br>|<br>**.4**<br> <br>|2.11<br>|.47<br>|2.16<br>|<br>.46<br> <br>|
|YPERCE<br>|V Perceived math ability (1uhi0g)<br> <br>|4.06<br>|<br>.43<br> <br>|4.08<br>|.42<br>|4.04<br>|<br>.44<br> <br>|
|YFUTUR<br>|Percolved future importance<br>of math (1ulo)<br> <br>|2.08<br>|<br>.42<br> <br>|**2.08**<br>|.43<br>|2.05<br>|<br>.42<br> <br>|
|YDESIR|E Motivatlon to suceed Inmath<br>(1low)|5.60|<br>.35|5.53|.37|5.61|<br>.34|

Notes: (a) For a complete descriptl')n of variables, coult text. (b) MlninA sample size for total sample is 3747. (c) MIninA sample size for rual saiple Is 1893. (d) MinInu sample size for urban sample Is 2054.

- 24 -
# Table **2:** The effect of student background characteristics on Grade 8 protest **and** posttest mathematics achievement Thailand, 1981-82

|Independent<br>variables|Protest|Poattest|<br>Poattest|Posttest|
|---|---|---|---|---|
|Pretest score|--|--|.82***<br>(59.04)|80***<br>(54.05)|
|Sex (2-<br>boy)|-.17<br>(.68)|.18<br>(.62)||.32<br>(1.45)|
|Age<br>Age squared<br>Father's occupation<br>Mothers education|.26<br>(1.01)<br>.00<br>(1.38)<br>.69***<br>(4.82)<br>.89***<br>(5.30)|.36<br>(1.14)<br>-.00<br>(1.59)<br>.59***<br>(3.41)<br>*97***<br>(4.79)|<br>|.14<br>(.61)<br>.00<br>(.89)<br>.03<br>(.24)<br>.26<br>(1.70)|
|Calculator**at**home|.46<br>(1.63)|.62<br>(1.84)||.25<br>(1.00)|
|District per capita ircome (1000|bh) .28***|*35***||12**|
||(7.11)|(7.36)||(3.55)|
|Lang. of inst. at home|1.57*<br>(2.18)|2.33**<br>(2.70)||1.08<br>(1.67)|
|Dist. PCI x Lang of inst.|-.13*<br>(2.48)|-.00**<br>(3.10)||-.09*<br>(2.01)|
|Constant|-12.57|-14.87|4.71|4.05|
|Adjusted R-squared|.07|.07|.48|.49|
|_N_|3642|3627|3801|3625|

***p < .001, **p < .01, * p < .05.

Note: Unstandardized regression coefficients; t-statistics in parentheses.

- 25 -
**Table** 3t **The** effect of student background characteristic* on student expectations, perceived parental support, perceived ability, attitudes **and** effort in Thailand, 1981-82

|Independent<br>variab<br>les|YMOREED|PARENC|YPERCEV|<br>YFUTURE|<br>YDESIRE|<br>YMWHKL|
|---|---|---|---|---|---|---|
|Sex (2- boy)|-.14***|<br>.27***|-.10**|-.09**|-.21***|<br>.04|
||(4.35)|(8.54)|(3.19)|(2.99)|(8.78)|(.31)|
|Age|-.00|-.02|.03|.02|.03|.00|
||(.08)|(.66)|(.88)|(.55)|(1.36)|(.03)|
|Age squared|-.00|.00|-.00|-.00|-.00|-.00|
||(.34)|(.84)|(.8_)|(.66)|(1.51)|(.15)|
|Father's occupation|.12***|<br>-.06**|.00|.04*|.05**|<br>-.09|
||(6.66)|(3.30)|(.24)|(2.39)|(3.28)|(1.20)|
|Mothers education|.12***|<br>-.07**|<br>-.03|.02|.06***|<br>.23*|
||(5.91)|(3.30)|(1.50)|(1.14)|(3.68)|(2.54)|
|Calculator at home|.05|.00|-.02|.03|.01|.13|
||(1.31)|(.10)|(.48)|(.84)|(.21)|(.85)|
|District PCI (1000 bh)|.01*|.01|-.00|-.00|.01|.02|
||(2.07)|(1.44)|(1.94)|(1.26)|(1.37)|(.85)|
|Lang. of inst. athome|.00|-.16|-.21*|-.07|.03|-.52|
||(.01)|(1.77)|(2.39)|(.85)|(.39)|(1.35)|
|Dist. PCI x Lang of inst.|.00|.00|.00*|.00|-.00|.00|
||(.01)|(1.95)|(2.50)|(.42)|(1.46)|(.83)|
|Constant|3.72|3.24|1.83|.89|2.99|4.61|
|Adjusted R-squared|.06|.04|.00|.01|.04|.00|
|N|3628<br>3|597<br>3|599|3582|3617|3574|

***p < .001, ** p < .01, * p <.05.

Note: Unstandardized regression coefficients; t-statisties in parentheses.

- 26 -
Table 4: **The** effect of student background characteristics on student expectations, perceived parental support, perceived ability, attitudes and effort, with pretest achievement controlled, in Thailand, 1981-82

|Independent<br>variables|YHOREED|PARENC|YPERCEV|<br>YFUTURE|<br>YDESIRE|<br>YMWHK|
|---|---|---|---|---|---|---|
|Pretest<br>Sex(2 -<br>boy)|.02***<br>(11.89)<br>-.13***|<br>-.01***<br>(3.40)<br> <br>.27***|-.04***<br>(18.60)<br>-.10***|.03***<br>(14.04)<br> <br>-.08**|<br>01***<br>(9.35)<br>-.21***|<br>.06***<br>(6.40)<br> <br>.05|
||(4.28)|(8.50)|(3.50)|(2.90)|(8.77)|(.40)|
|Age|-.00|-.02|.04|.01|.03|-.01|
||(.13)|(.59)|(1.24)|(.34)|(1.22)|(.07)|
|Age squared|-.00|.00|-.00|-.00|-.00|-.00|
||(.06)|(.76)|(1.28)|(.37)|(1.31)|(.02)|
|Father's occupation|10***|<br>-.05**|<br>.03|.02|.04**|-.13|
||(5.84)|(3.03)|(1.82)|(1.30)|(2.58)|(1.71)|
|Mothers education|.10***|<br>-.06**|<br>.00|-.00|.05**|<br>.18*|
||(4.96)|(3.01)|(.05)|(.04)|(2.88)|(1.99)|
|Calculator at home|.04|.01|.00|.02|-.00|.10|
||(1.01)|(.19)|(.09)|(.52)|(.07)|(.67)|
|District PCI (1000 bh)|.00|.01|.00|-.01**|.00|-.03|
||(.68)|(1.84)|(.15)|(2.97)|(.26)|(1.60)|
|Lang. of inst.**at**home|-.04|-.15|-.15|-.12|.00|-.61|
||(.44)|(1.65)|(1.86)|(1.42)|(.03)|(1.59)|
|Dist. PCI x Lang of inst.|.00|.00|.01|.01|-.01|.03|
||(.53)|(1.80)|(1.90)|(1.06)|(1.05)|(1.10)|
|Constant|4.05|3.12|1.35|1.22|3.19|5.11|
|Adjusted R-squared|.10|.04|.09|.06|.06|.01|
|N|3626<br>3|595<br>3|597|3580|3615|3572|

***p < .001, ** p < .01, * p <.05.

Note: Unstandardized regression coefficients; t-statistics in parentheses.

- 27 -
Table **5:** The effect of student background characteristics, pretest achievement, student expectations, perceived ^rental support, perceived ability,<sup>attitudes</sup> and effort on Grade 8 mathemat..cs poattest achievement in Thailand, 1981-82

|||Alt|ernative sp|ecificatio|ns||
|---|---|---|---|---|---|---|
|dependent<br>ariables|(1)|(2)|(3)|(4)|(5)|(6)|
|etest math achievement|<br>.78***|<br>.80***|<br>.75***|<br>.77***|<br>.78***|<br>.79*|
|x (2- boy)|(51.94)<br>.43|(53.51)<br>.35|(49.06)<br>.14|(50.93)<br>.42|(52.52)<br>.61**|(53.04)<br>.36|
||(1.93)|(1.56)|(.63)|(1.89)|(2.72)|(1.61)|
|e|.16|.10|.23|.03|.10|.16|
||(.69)|(.44)|(1.01)|(.14)|(.45)|(.68)|
|e squared|-.00|-.00|-.00|-.00|--.00|-.00|
||(.95)|(.74)|(1.31)|(.42)|(.73)|(.96)|
|ather's occupation|-.05|.04|.08|.03|-.01|.09|
||(.41)|(.29)|(.64)|(.27)|(.09)|(.71)|
|thers education|.19|.24|.23|.23|.19|.21|
||(1.28)|(1.59)|(1.60)|(1.54)|(1.29)|(1.3,|
|Calculator at home<br>District PCI (1000 bh)|.22<br>(.89)<br>.12***<br>(3.45)|.23<br>(.89)<br> <br>.13***<br>(3.61)|.26<br>(1.03)<br> <br>.13***<br>(3.63)|.21<br>(.84)<br> <br>.14***<br>(4.13)|.26<br>(1.04)<br> <br>.12***<br>(3.57)|.27<br>(1.05<br> <br>.14*<br>(3.89)|
|.ang. of inst. at home|<br>1.09|1.13|.96|1.27*|1.10.|1.31*|
||(1.70)|(1.74)|(1.51)|(1.99)|(1.72)|(2.02)|
|Dist. PCI x Lang of inst.|<br>-.00*|-.00*|-.00|-.00*|-.00|_.00*|
||<br>(2.06)|(2.10)|(1.77)|(2.26)|(1.91)|(2.35)|
|Educational<br>expectations|<br> <br>.80***<br>(6.58)|<br> <br>--|<br>--|--|--|--|
|arental<br>encouragement||-.02<br>(.83)|--|--|--|--|
|'erceived<br>math ability|||-1.47***<br>(11.47)|<br>__|||
|Future importance of math||||1.22***<br>(9.45)|<br>--|--|
|Motivation|||||1.10***<br>(7.06)|<br>--|
|Student effort||||||.13***<br>(4.74)|
|Constant|-8.78|-.71|-5.37|2.41|-7.53|-6.53|
|Adjusted R-squared|.49|.49|.51|.50|.49|.49|
||3609|3579|3581|3564|3599|3555|

***p < .001, ** p < .01, * p <.05.

Note: Unstandardized regression coefficients; t-statistics in parentheses.

- 28 -
Table 6s Effect of hom background, parental support, Student educational expectations, student attitudes, **and** student offort on Grade 8 mathematics pretest **achievement in** urban **and** rural schools, **Thailand,** 1981-82

|Ind-pondent<br>Variables|School L<br>Urban|ocation<br>Rural|
|---|---|---|
|Sex (2- boy)|-1.22***<br>(3.43)|1.03**<br>(2.94)|
|Age|.19|.46|
||(.59)|(1 00)|
|Age**squared**|.00|.00|
||(.92)|(1.18)|
|Father's occupation|.84***|.36|
||(4.47)|(1.62)|
|Mothers education|.77***|98***|
||(3.52)|(3.65)|
|Calculator at home|.39|70|
||(1.03)|(1.62)|
|District PCI(1000bh)|.00|27*|
||(.05)|(2.23)|
|Lang.ofinst. at home|-3.07|.68|
||(1.64)|(.41)|
|Dist. PCI x Langofinst.|.15|.27|
||(1.34)|(.04)|
|Constant|.55|-32.57|
||(.02)|(.81)|
|Adjusted R-squared|.06|.05|
|_N_|1995|1646|

*** p < .001, ** p < .01, * p <.05.

Note: Unstandardized regression coefficients; t statistics in parentheses.

- 29 -
# Table 7s Family background effects on Grade 8 mathematics achievement gain in Thailand, 1981-82a

|Independent|School|Location|
|---|---|---|
|<br>Variables|Rural|Urban|
|YMOREEDC|71***|92***|
||(4.31)|(5.14)|
|YPARENC|.01<br>|- 05<br>|
||(.04)|(.30)|
|YPERCEV|-1.30***|-1.66***|
||(6.76)|(9.62)|
|YFUTURE|1.17***|1.27***|
||(6.21)|(7.21)|
|YDESIRE|*75***|1.47***|
||(3.38)|(6.76)|
|YMHWXL|.11**|16***|
||(2.74)|(3.92)|

Notes

- (a) This table summarizes the results of 12 regression analyses, identical in design to those reported in Table 2.

- (b) Numbers are parameter estimates with t-statistics in parenthesis.

- (c) Effects controlling for student age, sex, paternal occupation, maternal education, household calculator ownership, household language use, and district per-capita income.

- 30 -
Table 8s Malawi Studys Variable Definitions and Descriptive Statistics

|Variable|Moan|SD|
|---|---|---|
|Raw Pupil Exam Scores<br>|||
|Chichewa (10 items)<br>|5.5<br>|2.3<br>|
|Maths (10 items)|3.8|2.1|
|Pupil Exam Z-Scores<br>|||
|Chichewa<br>|0.00<br>|0.99|
|Maths|0.00|1.00|
|Exogenous Predictors<br>|||
|Urban school (2-urban)|1.54|__|
|Region's wealth,Zlabor force<br>employed in non-agricultural<br>jobs|32.0|4.4|
|Pupil sex (2-girl)|1.49|__|
|Pupil's grade-level|5.5|1.5|
|Pupil's work tasks, five possible<br>farm related jobs (e.g. fted animals)|3.1|0.5|
|Pupil's mother tongue is Chichewa,<br>language of high-status tribe (2-yes)|1.6|--|
|Pupil's father's work<br>(4-point scale by skill level)|2.7|1.1|
|Pupil's mother's schooling level<br>(2-yes, completed standard 4)|1.7|0.5|
|Pupil's mother's reading practices<br>(10-point scale, e.g. reads books)|6.6|1.2|
|Pupil's house has electricity<br>(2-yes)|1.4|--|
|Pupil's parents own radio<br>(2-yes)|1.8|--|
|Headmaster's estimate I pupils from<br>farming families|42.7|32.9|
|Headmaster's estimate I pupil living<br>in thatch-roof huts|56.2|37.0|

Note: Standard deviations not reported for dichotomous variables.

- 31 -
Table 9: lnfluhI of Couitry-Specific Social **Class Mseures** on PUplI Achleveuent In Malawi

||ToT|AL TiiTSCE||CH|INCHE1A<br>STSAR|E||MATH<br>ITSTS|CaE|
|---|---|---|---|---|---|---|---|---|---|
||(1)",|(2)"|(3)0|(1)a|(2)"|(3)|(1)a|(2)||
|Jrban school<br>control)|-.33<br>(10.54)d|-.10<br>**(**0.03)e|-|-0.81<br>(-2.31)'|-.88<br>(-11.14)"|-|.49<br>(1.28)|.64<br>(3.38)|_|
|on's wealth|-. 005<br>(-0.15)|||.03<br>(1.52)|.04<br>**(**3.85)0||_.03<br>(-1.18)|||
|(girl.l)|-.28|||-.07|||-.22|||
||(-0.87)|||(-0.37)|||(-0.88)|||
|rade level|<br>-.05|||<br>-.02|||a.02|||
||(-0.48)|||(-0.37)|||(-0.39)|||
|other tongue|.51|||.21|||.30|||
|hichewa|( 1.56)|||( 1.07)|||(1.38)|||
|er's work|.17<br>(0.95)|||.15<br>( 1.3)|||.02<br>**(**0.18)|||
|er's<br>schoolI|ng.18<br>|||.41<br>|.35<br>||-. 23<br>|||
||( 0.46)|||( 1.72)|( 2.62)||(-0.88)|||
|er's readIng|-.15|||**-.10**<br>|||-. 03|||
|tices|(-0.82)|||(-1.05)|||(-0.11)|||
|**I's**<br>work<br>**tasks**<br>thatch**roof**|-.005<br>(-2.24)'|**-.005**<br>(-5.68)'|-.002<br>(-4.92)*|-.003<br>(-1.84)+|-.001<br> **(4.38)"**|-.001<br>(-5.71)'|-.003<br>(-1.69)|-.003<br>(-4.92)'|-.003<br>(-5.46)*|
|**Nuse**<br>w/electric|ity<br>1.01<br>|1.08<br>|1.13<br>|.59<br>|.42<br>|.78<br>|.43<br>|||
||( 2.16)*|( 8.07)**|( 9.39)"s|( 2.05)'|C 2.85)|(10.50)"|( 1.38)|||
|**idio**<br>In**house**|<br>.37|||<br>.26|||<br>.12|||
||( 0.89)|||( 1.02)|||( 0.42)|||
|s estimate<br>fathe|<br>rs.02|.02|.02|<br>.01||.01|<br>.02|.01|.01|
|Ing|(2.75)"|( 7.42)"0|(12.39)*'|( 1.52)||(11.46)08'|<br>( 2.78)"|( 7.09)"|(3.62|
|s estimate<br>homes|<br>.02|.02||.006|||.02|.02|.02|
|'thatch<br>roofs|(1.53)|(2.93)||(0.70)|||(1.67)|(5.17)'|4.50|
|cept|-2.13|-1.69|-1.93|-1.36|-.67|-1.25|-.77|-1.58|-.20|
||13,88|5,96|3,98|13,88|5,98|3,100|13,88|4,99|3,100|
|*square|.21|.16|.14|.27|.20|.14|.17|.10|.07|

:e: Lhnstandardlzed regression **coefficlients** reported. Full **model**

**Redjced** model with urban control **Reduced** model without urban control

T-values are reported for **full** models F-values repwrted for **reduced** models where backward elimination of non-slIgnlflcant exogenous variables was **run.** + pc.07 * pc.05 **p.01 "** p<.001 x.10 used as criterion for variable to remain In the equatlon.

- 32 -
# Table 10: lnfluence Of CoUntry-Specif ic Social Clans ksasures on PLPII Achlevewet In Urban and Rural Schools In alawl

||TOTAL<br>TE<br>Urban|<br>ST SCORE<br>Rural|CHICH<br>Urban|ENA<br>TEST SCOR<br>Rural|E<br>MATH<br>T<br>Urban|<br>EST SCORE<br> <br>Rural|
|---|---|---|---|---|---|---|
|RegIon's wealth|||.09<br>(8.00)"||||
|Sex (girl-1)||||-.59<br>(-5.37)0|||
|Grade<br>level|||||||
|Mother<br>tongue<br>Chichewa||1.22<br>(7.90)*||.56<br>(5.19)'||.65<br>- (6.06)-|
|father's<br>work|||||||
|Mother's school Ing||||.55<br>(4.30)'|||
|Mother's readIng<br>practloes|||||||
|Pupil's<br>work tasks||||||-. 004|
|xthatch roof||||||( 5.57)*|
|House w/electrIcity|1.21<br>(8.28)"||.52<br>(4.16)'|1.06<br>(5.74)'|||
|Radio In house||||.52<br>(4.23)*|||
|H's estlaato fathers<br>farmlng|.02<br>(6.15)'||||.013<br>(5.21)'||
|H's estIlate ho es|||-. 01|||.04|
|w/thatch<br>roofs|||(5.95)|'||( 5.49)*|
|Intercept|-2.40|1.80|-3.54|-2.82|-0.23|-2.03|
|Of|2,55|1,42<br>|3,58<br>|5,38<br>|1,56<br>|2,42<br>|
|R-sqyare|.16|.16|.26|.35|.09|.22|

# Note: Lhstandardized regresslon coeffIcIents and f-values reported.

PN.05 used as crIterIon for varlable to remain In equatlon.

-

p<.05 " pc.01 *- P<.C.O1

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