Explaining learning gaps in Namibia: The role of language proficiency

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    International Journal of Educational Development 31 (2011) 223233


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    e lsrapidly led to a world-wide growth of interest in the application oflarge-scale scientic survey research techniques to the study ofissues related to improving the productivity of workers through anincrease of the number of literate people, among which Husens(1969) work and the international research ran by the Associationfor the Evaluation of Education and Achievement (IEA) in the early-1970s which encompassed 23 countries (see Elley, 1992, 1994;Lundberg and Linnakyla, 1993; Postlethwaite and Ross, 1992). Thistrend spread progressively to developing countries. In the 1980sthe focus of these surveys slowly moved from an increase ofquantity of education to an improvement of quality of education.Most occidental countries and an increasing number of developingcountries are now applying such techniques to undertakesystematic studies of the conditions of schooling and studentachievement levels.

    Summarizing the results of the IEA and other studies fordeveloping countries, Alexander and Simmons (1975) note the lackof consistency across studies and the conicting nature of theresults. For instance, school-related variables, such as class size,school size, and teacher characteristics, appeared to be signicantin some countries and non-signicant (or negatively signicant) inothers. Finally, although non-school variables appeared of highimportance in all the studies, home background seemed to haveless inuence on pupils performance in developing than indeveloped countries.

    and 13 high-income countries. They observed that the inuence offamily background varied signicantly with national economicdevelopment between countries, and that the percentage ofachievement variance explained by school and teacher variableswas negatively correlated with the level of a countrys develop-ment. This result was conrmed by Saha (1983) and Fuller (1987)who examined the effects of school factors on student achievementin the Third World. Fuller concluded that much of this empiricalwork suggests that the school institution exerts a greater inuenceon achievement within developing countries compared toindustrialized nations, after accounting for the effect of pupilbackground (pp. 2556; italics in original).

    Yet, more recent works based upon more sophisticated surveydata have questioned the sustainability of these results (seeGameron and Long, 2007, for a detailed discussion of the evolutionof the debate on equality of educational opportunity in the pastfour decades). For instance, Baker et al. (2002), who examined datafrom the Third International Mathematics and Science Study(TIMSS) of 1995 and 1999, concluded that Heyneman and Loxleysndings for the 1970s were not observable anymore two decadeslater. Baker et al. (2002) attributed the HeynemanLoxley effectto the lack of mass schooling investments in most developingcountries back in the 1970s. They argued that the expansion ofeducation systems in developing countries during the 1980s and1990s was likely to have generated better educated cohorts ofparents. Thus, developing countries had beneciated from acatching-up effect towards developed countries relative compo-sition of family and school effects on student outcomes. Theauthors conjectured, however, that the HeynemanLoxley effect

    * Tel.: +39 0332 78 5407; fax: +39 0332 78 5733.

    E-mail address: christelle.garrouste@jrc.ec.europa.eu.

    0738-0593/$ see front matter 2010 Elsevier Ltd. All rights reserved.doi:10.1016/j.ijedudev.2010.06.016Explaining learning gaps in Namibia: T

    Christelle Garrouste *

    European Commission - Joint Research Centre (EC - JRC), Institute for the protection a

    TP361 - Via Enrico Fermi 2749, I-21027 Ispra (VA), Italy

    1. Introduction

    The need for reconstruction after the Second World War has

    A R T I C L E I N F O




    Educational policy

    Comparative education

    A B S T R A C T

    In a multilingual context,

    of instruction in the hom

    Namibian schools. The ou

    year 2000. Hierarchical

    achievement into its with

    role of low language skills

    and equity of the current

    journa l homepage: www.role of language prociency

    ecurity of the Citizen (IPSC), Unit G.09 Econometrics and Applied Statistics (EAS),

    In the early-1980s, Heyneman and Loxley (1983a,b) examinedthe effects of socio-economic status and school factors on studentsscience achievement in primary school in 16 low-income countries

    study investigates the role on mathematics achievement of the provision

    anguage. It compares characteristics of 5048 Grade 6 learners in 275

    me variable is the standardized SACMEQ mathematics score collected in

    ar modeling is used to partition the total variance in mathematics

    and between-school components. The results do conrm the signicant

    the overall lowmathematics scores, which may question the effectiveness

    ngual policy.

    2010 Elsevier Ltd. All rights reserved.

    ucational Development

    ev ier .com/ locate / i jedudev

  • might persist in countries where extreme poverty or socialupheaval such as civil war or epidemics slowed down massschooling.

    Chudgar and Luschei (2009) also revisited the HeynemanLoxley hypothesis, using the 2003 TIMSS data from 25 countries.They found that in most cases, family background was more

    C. Garrouste / International Journal of Educational Development 31 (2011) 223233224important than schools in understanding variations in studentperformance, but that, nonetheless, schools were a signicantsource of variation in student performance, especially in poor andunequal countries.

    Focusing exclusively on Southern and Eastern African countries,the survey by the Southern and Eastern Africa Consortium forMonitoring Educational Quality (SACMEQ) revealed corroborativeresults. In 2005, the SACMEQ II1 national reports showed thatmostcountries were demonstrating large between- and within-schoolvariations. While within-school variation is an indication ofdifferences in abilities among learners within each school,between-school variations are an indication of equity problemswithin the education system. South Africa, followed byUganda andNamibia, demonstrated then the highest percentage of between-school variation (see, for instance, Gustafsson, 2007, for a detailedanalysis of the South African case).

    More specically, the Namibian results displayed very poorlearners and teachers reading and mathematics scores, a denitedecline in reading scores between the rst SACMEQ study of 1995and the second one of 2000 and considerable variation amongregions (Makuwa, 2005). These results deserve further investiga-tion in view of the high resource allocation efforts made by theNamibian authorities to launch substantial education reformssince independence in 1990, which included the adoption of abilingual language-in-education policy aiming primarily at facili-tating the cognitive development and, hence, the learning processof pupils (Skutnabb-Kangas and Garcia, 1995).

    Hence, after a short review of the status of Namibian schoolsand political agenda at the time the SACMEQ II was conducted (i.e.year 2000) (Section 2), this paper attempts to investigate the mainfactors explaining the poor scores of Namibian Grade 6 learners.More specically, the objective is to see whether the homelanguage and prociency in English constitute signicant discrim-ination factors in mathematics achievement to explain the within-school and between-school variations.

    This focus is geared by ndings from other studies that havehighlighted the signicant role of language prociency onacademic achievement. For instance, Geary et al. (1996) foundthat the language structure of Asian numbering assisted Chinesechildren in developing meaningful early number concepts.Valverde (1984) noted that differences in the English and Spanishlanguages contributed to Hispanic Americans poor performanceand involvement in mathematics (see also Bush, 2002, for similarconclusions). Howie (2002, 2005) applied multilevel analysis(2002, 2005) on South African TIMSS data to show that signicantpredictors of between-school variations include pupils perform-ance in the English test, their exposure to English and the extent towhich English is used in the classroom.

    The method used in our work is a specic type of multilevelanalysis called Hierarchical Linear Modeling (HLM). This paperfollows the theoretical steps enounced by Raudenbush and Bryk(1988) and Hox (1995) for the use of the HLM method foreducation analyses (see Section 3 for a description of the model

    1 The International Institute for Educational Planning (IIEP) designed the

    Southern Africa Consortium for Monitoring Educational Quality (SACMEQ) in

    1991-1993, together with a number of Ministries of Education in the Southern

    Africa Sub-region. In 1995 the rst SACMEQ survey project was launched in six

    Southern African countries. The SACMEQ I project was completed in 1998 followed

    by the SACMEQ II project launched in 2000 in 14 Southern and Eastern African

    countries.and data). The results are then presented in Section 4 andconclusions drawn in Section 5.

    2. Namibias school structure and policy agenda at the time ofthe study

    The Republic of Namibia is situated on the south west coast ofAfrica and is bordered by the Atlantic Ocean to the west, therepublics of Angola and Zambia to the north and north-east,respectively, and the republics of Botswana and South Africa to theeast and south, respectively. It obtained national independencefrom former apartheid South African government on March 21,1990, after many years of political, diplomatic and armed, nationalliberation struggle. Even if the country is well endowed with gooddeposits of uranium, diamonds, and other minerals as well as richshing grounds, there are wide disparities in the distribution ofincomes. With a per capita income of US$2000 Namibia may beregarded as a middle income country. Yet, the richest 10% of thesociety still receives 65% of the incomes. As a consequence, theratio of per capita income between the top 5% and the bottom 50%is about 50:1 (Makuwa, 2005). This provides a brief understandingof the socio-economic context under which the education systemhas to develop in Namibia.

    Since independence, Namibia has made strides in the provisionof basic education, which by 2001 had resulted in a primaryeducation net enrolment of 94% of all children aged 713 (in Grades17), and by 2006 Namibia ranked among the top eight Africancountries in term of primary completion rate (>80%) (Vespoor,2006).Whilemuchseemstohavebeenachieved intermsofaccess toschooling, the quality of education, efciency and equity issues aresince the late-1990s at the center of political preoccupations.

    Because Article 20 of the Constitution of the Republic ofNamibia provides for free and compulsory education for alllearners between the ages of 6 and 16 or learners from Grade 1 upto the end of Grade 7; and because the government has declarededucation to be a priority among all other priorities in Namibia,education has received the largest share of the national recurrentbudget since independence. For instance, out of the estimated totalgovernment current expenditure of N$8.35 billion for the 2001/2002 nancial year, N$1.86 billion, i.e. about 20% of the budget,was earn-marked for basic education only. Of the total amountallocated for basic education, N$986.56 million was earn-markedfor primary education and the rest for secondary education. Yet,almost 90% of the money allocated for primary education wasspent on personnel costs (e.g., salaries and/or subsidies to teachersin a number of private schools), leaving only about 10% for all theother services and school supplies (Makuwa, 2005). As aconsequence, the nancial allocation per learner ratio is morefavorable to regions with more qualied staff and fewer learnersthan to rural regions with more unqualied teachers and largepupilteacher ratios. Finally, the fact that schools are authorized tocollect school development funds directly from parents is againmore favorable to schools located in urban areas where parentshave an income than to schools in more remote areas.

    In addition to these resource allocation issues, it is also importanttohighlight themanychanges that tookplace in theeducationsectorbetween 1995 and 2000. As explained in Makuwas (2005) report,therewere for instancemore learners andmore schools in2000 thanin 1995; the department of Sport was added to theMinistry of BasicEducation and Culture; and, more important, the HIV/AIDSpandemic became a national problem affecting infected adminis-trators, teachers, learners and/or parents. In view of these newcontextual settings, the Ministry of Basic Education, sports andCulture (MBESC) dened eight new national priority areas in itsStrategic Plan for the period 20012006: equitable access;education quality; teacher education and support; physical facili-

  • C. Garrouste / International Journal of Educational Development 31 (2011) 223233 225ties; efciency and effectiveness; HIV/AIDS; lifelong learning; andsports, arts and cultural heritage.

    Finally, to understand the context framing the data used in thisstudy, it is also essential to give an overview of the structure of theNamibian primary school system. The primary phase consists of theLower Primary (Grades 14), duringwhichmother tongue is used asmedium of instruction, and Upper Primary (Grades 57), duringwhichEnglishbecomes themediumof instructionuptoGrade12.Bythe year 2000, there were 998 primary schools hosting a total of406,623 learners, of which 952 were government schools and therest were private schools. Nearly two thirds of all primary schoolswere located in the six most populated northern regions namely,Caprivi, Kavango, Ohangwena, Oshikoto, Oshana and Omusati.

    It is in the abovemilieu that the second SACMEQ survey used inthe present paper was collected and it is therefore in that framethat the results of the analysis should be interpreted.

    3. Model and data

    The methodological approach applied in this study is ahierarchical linear modeling. The HLM framework was developedduring the 1980s by Aitkin and Longford (1986), DeLeeuw andKreft (1986), Goldstein (1987), Mason et al. (1983) and Rauden-bush and Bryk (1986). As explained by Raudenbush and Bryk(1995), these procedures share two core features. First, they enableresearchers to formulate and test explicit statistical models forprocesses occurring within and between educational units,thereby resolving the problem of aggregation bias under appro-priate assumptions. Second, these methods enable specication ofappropriate error structures, including random intercepts andrandom coefcients, which can solve the problem of misestimatedprecision that characterized previous conventional linear modelsand hindered their capacity to test hypotheses. Hence, Lynch et al.(2002) conrm the strength of HLM models compared to othermultilevel models to produce superior unbiased estim...


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