Differences in pupil achievement in Kenya: Implications for policy and practice Njora Hungi a, *, Florence W. Thuku b a International Institute for Educational Planning, 7-9 rue Eugene-Delacroix, 75116 Paris, France b Ministry of Education, Kenya 1. 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 Educa- tional 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 multi- level 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. 2. Educational context Kenya has a land area of around 582,646 km 2 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 province, Nairobi, has a population of about 5 million; it is entirely urban and cosmopo- litan. The North Eastern province is mainly arid and its inhabitants are mostly nomads. It is arguably the least developed province in Kenya. Each province has a Provincial Director of Education office, responsible for all education activities in the province. Literacy, as well as primary school enrollment, varies from province to province. Adult literacy ranges from 8% in North Eastern province to 87% in Nairobi province (Kenya National Bureau of Statistics, 2007). Net enrollment ratios ranges from 82.8% in Central province to 14.5% in North Eastern province (Onsomu et al., 2005). International Journal of Educational Development 30 (2010) 33–43 ARTICLE INFO Keywords: Pupil achievement Kenya education Multilevel models Education equity ABSTRACT In this study the authors employed multilevel analyses procedures to examine pupil, class and school levels factors that influenced pupil achievement in Kenya. Pupil’s age, pupil’s socioeconomic background and pupil–teacher ratio were important factors in the prediction of pupil achievement. The provinces with the largest between-school variation were Eastern and Rift Valley. Low social equity was evident in Nyanza, Nairobi and Western while large gender inequities were evident in North Eastern. Implications of the findings for policy and practice are outlined. ß 2009 Elsevier Ltd. All rights reserved. * Corresponding author. Permanent address: P.O. Box 12987, Nakuru, Kenya. E-mail address: hungi05@yahoo.com (N. Hungi). Contents lists available at ScienceDirect International Journal of Educational Development journal homepage: www.elsevier.com/locate/ijedudev 0738-0593/$ – see front matter ß 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijedudev.2009.05.001