Differences in pupil achievement in Kenya: Implications for policy and practice
Introduction
The main purpose of this study was to identify the key pupil-, class- and school-related factors that contributed to differences in mathematics and reading achievement among Grade 6 pupils in Kenya. It is of interest to identify and understand the key factors that contribute to differences in pupil achievement so that the Ministry of Education in Kenya and development partners can focus on policies that could improve education quality for all children in Kenya regardless of the children's background characteristics (such as socioeconomic background, age and gender) and their school's characteristics (such as school location, school type and school size). This purpose is in line with goal 2 of the EFA Dakar Final Framework which emphasised that countries should “ensure that by 2015 all children, particularly girls, children in difficult circumstances and those belonging to ethnic minorities, have access to, and complete, free and compulsory primary education of good quality” (UNESCO, 2000).
In order to achieve the above purpose, a three-level model (between schools, between classes and between pupils) was hypothesised and the data analysed using multilevel analysis procedures for each of the two outcome measures (mathematics and reading). These data were collected from 3299 pupils in 320 classes in 185 schools in eight provinces in Kenya as part of the Southern and Eastern Africa Consortium for Monitoring Educational Quality (SACMEQ) II project in 2002. The SACMEQ II Project sought to examine the quality of the education provided in primary schools in Kenya and another 13 African countries.
The structure of this paper is as follows. A section is included in which the educational context of Kenya is outlined followed by a section in which pioneer studies that linked pupil achievement to family background and school factors are outlined. These are followed by sections in which the data, the hypothesised multilevel models and the multilevel analyses are described. Finally, sections are included in which results of the analyses are presented and interpretations of the results and their implications are discussed.
Section snippets
Educational context
Kenya has a land area of around 582,646 km2 and a population of about 38.5 million persons. The country has 40 indigenous ethnic groups, each with it own language. English is the official medium of instruction in schools but Kiswahili and other local languages are also used especially in lower primary school grade levels.
The country is divided into eight administrative regions (known as provinces) namely: Coast, Central, Eastern, Nairobi, Rift Valley, Western and North Eastern. The capital
School, family background and pupil achievement
A study by Coleman et al. (1966) is among the earliest influential works on the effect of school factors and family background on pupil achievement. One controversial finding of the Coleman report was that school factors had little effect on academic achievement after taking into account family background of the pupils. Although controversial, the Coleman study has been credited for “the debate it provoked about the relative effects of school resources [factors] and family background on
The data
The SACMEQ II Project focused on pupil scores (on Rasch scales) in mathematics and reading tests at Grade 6 level. The project included surveys of Grade 6 pupils, teachers, school principals and parents. The findings from the SACMEQ II Project are presented in individual country reports (e.g. Kulpoo and Soonarane, 2005, Leste et al., 2005, Onsomu et al., 2005).
The SACMEQ II tests were developed by a panel of subject specialists from all 14 SACMEQ countries. The subject specialist identified
Hypothesized models
Two separate three-level models were hypothesised and examined, one for factors influencing achievement in mathematics and the other for factors influencing achievement in reading. The outcome variables of interest in these models were pupils’ scores in mathematics (ZMALOCP) and reading (ZRALOCP) tests, both with a mean of 500 and a standard deviation of 100. The hierarchical structures of these models were pupils at level-1, classes at level-2 and schools at level-3.
The variables that were
Analyses
Before the commencement of the multilevel analyses, the correlations between the variables were examined to avoid problems associated with multicollinearity and suppressor variable relationships in the model (Keeves, 1997).
A preliminary task in three level HLM analyses was to build two sufficient statistics matrix (SSM) files, one for mathematics and the other for reading. No pupils, classes or schools were dropped because of insufficient data in the construction of these SSM files. Therefore,
Results
Estimates of fixed effects (also known as path or regression coefficients) of the variables included in the final three-level models for mathematics and reading are given in Table 1. It should be noted that all the metric coefficients displayed in Table 1 are significant at p ≤ 0.05 because their values taken in absolute terms are more than twice their standard errors.
The variance components from the final and null models are presented in Table 2 in rows ‘a’ and ‘b’, respectively. From the
Discussions
In the following three sub-sections, summaries of the effects recorded in Table 1 on achievement in mathematics and reading among Grade 6 pupils in Kenya at the various levels of hierarchy are discussed. In these paragraphs, it is assumed that pupils differed only in the factor being considered and all other factors were equal. The results of variance partitioning and variance explained recorded in Table 2 are discussed later in a separate sub-section.
Summary and conclusions
The purposes of this study were to identify the key pupil-, class- and school-related factors that contributed to differences in mathematics and reading achievement among Grade 6 pupils in Kenya. Multilevel analyses procedures using HLM were employed to achieve this purpose.
Based on the magnitudes of effect sizes of the variables in the final mathematics model, it was found that the key predictors of mathematics achievement among Grade 6 pupils in Kenya were age in months (−0.16), pupil's sex
References (33)
- et al.
Educational expectation and school achievement of urban African-American children
Journal of School Psychology
(1999) - et al.
Retrospective vs. prospective analyses of school inputs: the case of flip charts in Kenya
Journal of Development Economics
(2004) - et al.
Efficiency and equity in schools around the world
Economics of Education Review
(2003) Nutrition status, education participation, and school achievement among Kenyan middle school children
Nutrition
(2003)- et al.
Socioeconomic status, school quality, and national economic development: a cross-national analysis of the “Heyneman–Loxley effect” on mathematics and science achievement
Comparative Education Review
(2002) Grade repetition. Education policy series 6
International Academic of Education & International Institute for Educational Planning
(2006)- et al.
Hierarchical Linear Models: Applications and Data Analysis Methods
(1992) - et al.
Equality of Educational Opportunity
(1966) Gender differences in a psychological model of mathematics achievement
Journal for Research in Mathematics Education
(1992)- et al.
Equity and segregation in the Spanish education system
Prospects
(2006)