DETERMINANTS OF ABSENTEEISM AMONG PRIMARY SCHOOL PUPILS
IN UGANDA
BY
MAYANJA EDISON
BSc.Educ (Hons), MUST
2008/HD15/12980U
A DISSERTATION SUBMITTED IN PARTIAL FULFILMENT OF
THE REQUIREMENTS FOR THE AWARD OF THE DEGREE OF MASTER OF
STATISTICS OF MAKERERE UNIVERSITY
MAY 2011
DECLARATION
I, Mayanja Edison , hereby declare that the work presented in this dissertation is my
original work and has never been submitted to any academic institution for an academic
award.
Signed:……………………………….
Date:……………………………..
Mayanja Edison
i
APPROVAL
This dissertation has been submitted for examination with the approval of the following
supervisors:
1. Signed…………………………………. Date…………………………..
Dr. L.K. Atuhaire
School of Statistics and Applied Economics
Makerere University, Kampala
2. Signed…………………………………. Date…………………………….
Dr. William Kaberuka
School of Statistics and Applied Economics
Makerere University, Kampala
ii
DEDICATION
I dedicate this work to my dearest mum Mrs.Zamu Bukenya.
iii
ACKNOWLEDGEMENTS
I would like to extend my sincere gratitude to my supervisors; Dr.William Kaberuka and
Dr. L.K. Atuhaire of the School of Statistics and Applied Economics Makerere
University, Kampala whose supervision, motivation, guidance and advice at each stage of
the course made it possible for the research work to score its value. I am sincerely
grateful for all the time and energy they have invested in me and may the Almighty God
reward them abundantly.
I owe my gratitude to the staff of the School of Statistics and Applied Economics
Makerere University, Kampala for their cooperation that made the study worthwhile.
I would like to extend my appreciation to all my classmates but special appreciation go
to Ssekasanvu Joseph, Tumugumye Philip, Ssettuba absalom, Nalukenge Betty, Kunihira
Andrew, Kuteesa Andrew and Sibenda Sadoke for their support in varied forms.
I also express my indebtedness to my Mum, Bulime Paul, Sseremba Freddie, Kivumbi
Eddie and Dr.Nsubuga Angel for the financial support and encouragement they offered to
me. Completion of this work was a result of both the explicit and implicit support of my
sisters and brothers; Daulah, Mayimunah, Fatuma, Hadjah, Shamim, Susan, Edith,
Racheal, Eddie and Hassan to whom I am grateful.
The support provided by my fiancée Fortunate Tumwebaze was enormous that I have no
words to use but to say thank you.
It is impossible to remember all and I apologize to those I have inadvertently left out.
May God bless you all.
iv
ABSTRACT
The broad objective of this study was to identify the factors that explain absenteeism
among primary school pupils in Uganda. This study employed secondary cross-sectional
data on absenteeism among primary school pupils from 2006 Uganda Demographic and
Health Survey which was a descriptive statistical survey. The analysis was done at three
levels, that is, at Univariate analysis descriptive statistics was used; at Bivariate analysis
cross-tabulations were done to establish the relationship between absenteeism among
primary school pupils and the indepedent categorical variables ,the results were discussed
using Pearson’s Chi-Square test and at Multivariate analysis, a complementary log-log
model was fitted to establish the most significant factors determining absenteeism among
primary school pupils in Uganda.
The study revealed that household size, type of place of residence and disability stati of
the pupil were the significant determinants of absenteeism among primary school pupils
in Uganda. It was found out that absenteeism among pupils with one type of disability
was 1.204 times that of those without any disability. It was also established that
absenteeism among pupils with two types of disabilities was 1.925 times that of those
without any disability. Absenteeism among pupils residing in rural areas was found to be
1.522 times that of those residing in urban areas. Absenteeism among pupils from
households with more than 7 members was found to be 0.879 times that of those from
households with 7 members and below.
The study recommends sensitization of rural parents/guardians on their roles and
responsibilities so as to fulfill their primary parental responsibility of monitoring their
v
children’s school attendance, providing them with school requirements and doing
everything possible to ensure that their children are regular at school.
vi
TABLE OF CONTENTS
DECLARATION ................................................................................................................. i
APPROVAL ....................................................................................................................... ii
DEDICATION ................................................................................................................... iii
ACKNOWLEDGEMENTS ............................................................................................... iv
ABSTRACT ........................................................................................................................ v
TABLE OF CONTENTS .................................................................................................. vii
LIST OF TABLES ............................................................................................................. ix
ACRONYMS ...................................................................................................................... x
CHAPTER ONE: INTRODUCTION ................................................................................. 1
1.1 Background to the study ........................................................................................... 1
1.2 Statement of the problem .......................................................................................... 3
1.3 Objectives of the study.............................................................................................. 4
1.4 Hypotheses of the study ............................................................................................ 4
1.5 Significance of the study........................................................................................... 5
1.6 Scope of the study ..................................................................................................... 6
1.7 The conceptual frame work of determinants of absenteeism among primary school
pupils. .............................................................................................................................. 7
CHAPTER TWO: LITERATURE REVIEW ................................................................... 10
2.2 Socio-Demographic factors .................................................................................... 10
2.3 Socio-economic factors ........................................................................................... 16
CHAPTER THREE: METHODOLOGY ......................................................................... 19
3.2 Data source.............................................................................................................. 19
3.3 Data analysis ........................................................................................................... 22
CHAPTER FOUR: DETERMINANTS OF ABSENTEEISM AMONG PRIMARY
SCHOOL PUPILS ............................................................................................................ 26
4.3 Univariate analysis and Bivariate analysis ............................................................. 26
4.4 Multivariate analysis ............................................................................................... 31
vii
CHAPTER FIVE: SUMMARY OF THE FINDINGS, CONCLUSIONS AND
RECOMMENDATIONS .................................................................................................. 35
5.1 Summary of the findings ......................................................................................... 35
5.2 Conclusions ............................................................................................................. 36
5.3 Recommendations ................................................................................................... 36
References ......................................................................................................................... 39
viii
LIST OF TABLES
Table 4.1: Percentage distribution of absenteeism among primary school pupils………25
Table 4.2: Percentage distribution of Socio-Demographic factors and Cross
tabulations of Absenteeism by Socio-Demographic factors…………………27
Table 4.3: Percentage distribution of Socio-Economic factors and Cross
tabulations of absenteeism by Socio-Economic factors……………………..29
Table 4.4: Results of the Complementary log-log regression model of absenteeism among
Primary school pupils according to the independent variables………………31
ix
ACRONYMS
FAWE: Forum for African Women Educationalists
MDGs: Millennium Development Goals
MoES: Ministry Of Education and Sports
NGOs: Non-Governmental Organizations
PLE: Primary Leaving Examination
UBOS: Uganda Bureau of Statistics
UDHS: Uganda Demographic Health Surveys
UNEB: Uganda National Examination Board
UNHS: Uganda National Household Survey
UPE: Universal Primary Education
UWESO: Uganda Women’s Effort to Save Orphans
x
CHAPTER ONE
INTRODUCTION
1.1 Background to the study
Millennium Development Goals (MDGs) 2 and 3 aim at achieving universal primary
education and to promote gender equality and empower women respectively, educating a
nation remains the most vital strategy for the development of the society throughout the
developing world (Aikaman & Unterhalter, 2005). Many studies on human capital
development agree that it is the human resources of a nation and not its capital or natural
resources that ultimately determine the pace of its economic and social development. The
principal institutional mechanism for developing human capital is the formal education
system of primary, secondary, and tertiary training (Nsubuga, 2003). Since education is
an investment, there is a significant positive correlation between education and
economic-social productivity. Educated people are likely to have improved standards of
living, since they are empowered to access productive ventures, which will ultimately
lead to an improvement in their livelihoods. The role of education therefore, is not only to
impart knowledge and skills that enable the beneficiaries to function as economies and
social change agents in society, but also to impart values, ideas, attitudes and aspirations
important for natural development. The straightforward linkage between education is
through the improvement of labor skills, which in turn increases opportunities for well
paid productive employment. This then might enable the citizens of any nation to fully
exploit the potential positively.
1
The structure of primary education in Uganda is such that at the age of about 6 years a
child enters school for 7 years, at the end of 7 years he/she is expected to take Primary
Leaving Examinations (PLE) conducted by the Uganda National Examinations Board
(UNEB).
To fully improve the literacy in Uganda, the government introduced Universal Primary
Education (UPE) in 1997 so as to achieve the educational related MDG 2 (that by 2015,
all children, boys and girls should be able to complete a course of primary schooling) this
has greatly increased the primary school pupil enrollment from around 3 million pupils in
1997 to about 7.5 million in 2003 and over 7.6 million in 2005/06 (UNHS, 2005/2006).
At present both under age and over age pupils are enrolled as education is free.
Though education is free, research findings have revealed that pupil absenteeism is
increasing. According to Nakanyike, Kasente and Balihuta (2003), on average, a child
misses 23 days in a year. This rate is much higher than the 13 days a year that was
reported by Uganda Bureau of Statistics (UBOS) and Macro International Inc. (2001). In
a week the average number of days missed is 2 days as revealed by UBOS and Macro
International Inc. (2007)
Hunger, poor nutrition and UPE related fees have been mentioned to be the key causes of
absenteeism among UPE school pupils (UWESO, 2008). Although UPE is supposed to
be free, it is known that there are other costs related to school attendance like uniforms,
stationery, transport, boarding fees, etc, which may be prohibitive to the households.
2
Indifference to education (which includes parents’ not favoring education and pupils not
willing to attend further) and schools being too far are also a major reason why children
are likely to be absent from school (UNHS, 2005/2006).
Factors noted why absenteeism occurs in Uganda primary schools are illness, domestic
work, pupils don’t want to go to school, working for a family farm/business or other
employer, attending a funeral or other ceremony, problems with school uniform, and
having no stationery (UBOS and Macro International Inc,2007).
1.2 Statement of the problem
Despite the Uganda government’s effort of introducing UPE in 1997 that is completely
free and abolition of all kinds of fees in UPE schools, absenteeism among primary school
pupils is on an increase. Kagolo (2009) cites Atima (2009) from directorate of education
standards of Ministry Of Education and Sports (MoES) who reported that only 55 percent
of the pupils attend school at the beginning of the term and during examinations and this
is worse in Government aided schools that are free compared to private ones that are not
free.
A pupil that is frequently absent fails to master a minimum of skills and competences and
is likely to be forced to repeat the grade, this not only doubles the cost to educate that
pupil but also reduces the pupil’s morale to continue schooling hence eventual dropping
out of school this lets down government’s policy of attainment of MDGs 2 and 3 that aim
at educating all children to the end of primary level and promoting gender equality by
2015 respectively. Absenteeism has been noted as one of the major cause of school
3
dropouts in Uganda (Nakanyike et al., 2003). Therefore there was need to identify major
determinants of absenteeism among primary school pupils so as more absenteeism
control measures could be developed and existing ones could be strengthened to slow
down the increasing rate of pupil absenteeism in Uganda.
1.3 Objectives of the study
1.3.1 General objective
The general objective of this study was to identify the factors that explain absenteeism
among primary school pupils in Uganda.
1.3.2 Specific objectives
The specific objectives of this study were the following;
i)
To determine whether socio-demographic factors influence absenteeism
among primary school pupils.
ii)
To determine whether socio-economic factors influence absenteeism among
primary school pupils.
1.4 Hypotheses of the study
In order to achieve the above objectives the following hypotheses were considered;
i)
Sex of the primary school pupil has no effect on his/her absenteeism.
ii)
Age of household head has no influence on the primary school pupil’s
absenteeism.
iii)
Sex of household head has no effect on primary school pupil’s absenteeism.
4
iv)
Relationship of pupil to the household head does not affect primary school
pupil’s absenteeism.
v)
Survivorship status of the parent of the primary school pupil has no influence
on the pupil’s absenteeism.
vi)
Absenteeism of the primary school pupil is independent of the pupil’s
disability status.
vii)
Residence of the pupil has no effect on primary school pupil’s absenteeism.
viii)
Household size has no influence on primary school pupil’s absenteeism.
ix)
Highest education level attained by household head has no effect on primary
school pupil’s absenteeism.
x)
Absenteeism of the primary school pupil is independent of the household
socio-economic status.
1.5 Significance of the study
Pupils who are absent frequently or for long periods are likely to have difficulty in
mastering the material presented in class, making absenteeism a critical education issue.
Absenteeism is one of the reasons for pupil’s poor grades. Since the researcher intended
to identify and estimate the determinants of pupil absenteeism in primary schools this
will help to provide information to the relevant authorities to enable them come up with/
strengthen existing policies regarding appropriate reduction on pupil absenteeism.
In addition the findings of this study will also be of great importance to academicians, it
will serve as a study guide and it is intended to add to the knowledge of the researchers in
this field of study.
5
1.6 Scope of the study
The study focused on determinants of absenteeism among primary school pupils in the
whole of Uganda. In this study all data with missing values and don’t know were not
considered.
6
1.7 The conceptual frame work of determinants of absenteeism among primary
school pupils.
Figure 1.1
Socio-demographic factors
 Sex of the pupil
 Age of household head
 Sex of the household head
 Relationship of the pupil to the
household head
 Survivorship status of the parents
of the pupil.
 Disability status of the pupil (any
difficulty in; seeing, hearing,
walking or climbing stairs,
remembering, self-care and
communicating.
Pupil absenteeism
Socio-economic factors
 Type of place of residence
 Size of the household
 Highest education level attained by
household head
 Household Socio-economic status
Independent variables
dependent variable
The conceptual frame work in figure 1.1 is based primarily on one developed by Manuel
Crespo (1984). The model explains the effect of socio-economic and socio-demographic
factors on absenteeism among primary school pupils. Relationship of the pupil to the
household head, survivorship status of the parent of the pupil determines whether/or not
the pupil will be provided adequately with basic school requirements like stationery,
uniform and fees, hence affecting pupil’s absenteeism. Sex of the pupil determines the
7
opportunity cost to education and who will do what type of domestic work and hence
determine absenteeism. Disability status of the child determines the ease a child finds in
going to school and hence determine absenteeism. Sex and age of the household head
determines the magnitude of control over the children this influences pupil’s willingness
to go to school.
Household Socio-economic status determines the ability to provide a child with basic
school requirements and ability to control illness for example buying mosquito nets,
having protected water sources like taps and better toilet facilities hence affecting pupil
absenteeism. Size of the household can increase or reduce on the domestic work
available, financial burden hence determine the level of absenteeism. Education level of
the household head determines the value he/she holds to education and the inspiration for
education pupils in the household derive from him since a household head is a role model
to the members of the household. This influences attainment of school requirements,
children’s willingness to attend school and hence absenteeism. Residence influences
accessibility of schools, pressure on children to engage in petty business to support the
household (e.g. in domestic and agricultural duties) hence influencing absenteeism.
1.8 Structure of dissertation
This study is organized into five chapters. Chapter one deals with introduction of the
study, that is, background to the study, statement of the problem, objectives of the study,
hypotheses of the study, significance of the study, scope of the study and the conceptual
frame work of determinants of absenteeism among primary school pupils. Literature
review is presented in chapter two. Chapter three is on methodology that was used in the
8
study, which includes: source of data, description of variables and methodology of data
analysis. Determinants of absenteeism among primary school pupils are discussed in
chapter four. Chapter five gives the summary of findings, conclusions and
recommendations.
9
CHAPTER TWO
LITERATURE REVIEW
2.1 Introduction
This chapter reviews the literature on primary school pupil absenteeism. There has been
quite a considerable amount of literature on primary school pupil absenteeism both in
Uganda and on the international scene. The chapter attempts to shade some light on what
has been said on primary school pupil absenteeism.
2.2 Socio-Demographic factors
Sex of the pupil
Boys absent themselves from school more than girls despite the fact that in Ugandan
primary schools there are more boys than girls this was revealed by the rapid head count
in primary schools (MoES, 2009). According to UBOS and Macro International Inc.
(2007) report, it showed that male pupils missed school more than female pupils.
However this is in contradiction with the findings of the research done by Runhare and
Gordon (2004) in Zimbabwe that found out that there was higher absenteeism among
girls than boys because of economic hardships, negative cultural and socializations
factors, HIV/AIDS related factors and over burdening household chores.
Studies have indicated the preference many households have for the education of boys
over girls, with girls’ education often deemed less important ( Admassie, 2003; Boyle,
Brock, Mace & Sibbons, 2002; Nekatibeb, 2002; Rose & Al Samarrai, 2001). Boyle et al.
(2002) suggest that households in their study tended to see boys’ education bringing
10
greater future economic rewards, which was not to be the case with girls. Indeed,
educating a girl is often seen as a poor investment because the girl will marry and leave
home, bringing the benefits of education to the husband’s family rather than to her own.
Similarly, in Guinea parents mentioned that primary schooling was irrelevant to girls’
future roles. In such cases girls will not be facilitated with schooling necessities like boys
and will end up being more absent than boys.
Research highlights a number of important points with regard to education and rites of
passage ceremonies which mark the move from childhood to adulthood. The ceremony
and preparations for it may overlap with the school calendar, which can increase
absenteeism (Boyle et al., 2002; Kane, 2004; Nekatibeb, 2002). Boys in Guinea
undertaking initiation ceremonies had primary schooling disrupted, with ceremonies
sometimes taking place in term time, absenteeism lasting up to one month, while for girls
it was often considered ‘shameful’ for them to return to school (Colclough et al., 2000).
This move into adulthood at times means that ‘new’ adults can think themselves too
grown up for schooling. Nekatibeb (2002) describes how communities in Ethiopia accept
these girls as ‘adults’, but teachers or schools continue to consider them as children and
this may create tension.
Girls as they grow, they experience puberty changes that are more likely to increase
absenteeism than boys for example getting attracted to men and using school time to meet
them since it is the only chance they have as they are still staying with their
parents/guardians. It is during primary schooling when girls start their menstruations.
11
UNICEF (2005) estimates that 1 in 10 school-age menstruating African girls skip school
four to five days per month or drop out completely because of lack of sanitation facilities.
In Uganda, many disadvantaged menstruating primary school girls who lack sanitary
towels decide to stay at home for the days the menstrual cycle lasts due to fear of
inconveniences. This means that these girls are absent from school for about four days
per month (FAWE Uganda, 2004). This absenteeism leads to poor academic performance
and subsequent dropping out of school.
Age of house hold head
Household head’s age contributes to absenteeism in away that absenteeism is high in
households where the head is child or very old unlike in those ones headed by mid-adults.
This is because household heads that are children or grandparents don’t usually exert
enough control over the children. A study done in Malawi by Chimombo et al. (2000)
revealed that in some areas a lot of night activities such as dances and initiation
ceremonies contributed to absenteeism from school. It was noted that some girls and boys
as young as 15 years would spend the whole night out with little interference from the
grandparents or these children were sleeping separately in their own huts. Such children
would get so tied that would not attend classes the following day.
Sex of the household head
Al Samarrai and Peasgood’s (1998) research in Tanzania suggests that the father’s
education has a greater influence on boys’ primary schooling and the mother’s on girls’.
Glick and Sahn’s (2000) results offer some similar outcomes to Al Samarrai and
12
Peasgood (1998): improvements in fathers’ education raise the schooling of both sons
and daughters, but mothers’ education has significant impact only on daughters’
schooling. Therefore if the household head is a male, then, boys and girls are likely to
have similar school attendance patterns whereas in those headed by females, boys are
likely to be more absent than girls.
Men tend to exert enough control on children as far as school attendance is corned more
than women. Therefore if the household head is a male, pupil absenteeism is likely to be
low compared to female headed households.
Relationship to the household head
If a child is a daughter or son to the household head is likely to get all schooling
requirements and his/her school attendance will be high unlike for his/her counterparts.
Research done by Konate, Gueye and Nseka (2003) reveals that relationship to the
household head has an impact on pupil’s school absenteeism in away that children of the
head of household are usually favored over others in the household (i.e. those fostered,
entrusted to the family and those living in it with parents other than the heads of
household).
Survivorship status of the parents of the pupil
Presence of a pupil’s parents alive has an impact on his/her absenteeism, particularly in
poorer communities. Grant and Hallman’s (2006) research on education access in South
Africa shows children living with mothers were significantly less likely to have absented
13
from school relative to those whose mothers were living elsewhere or whose mothers
were dead.
Orphan hood often exacerbates financial constraints for poorer households and increases
the demands for child labor and absenteeism (Bennell, Hyde & Swainson, 2002;
Ainsworth, Beegle & Koda, 2005). In Uganda though there is UPE, orphans are working
even on school days so as to get money to buy scholastic materials hence absenting from
school.
Recent studies done in Burundi show that attendance rates vary by category of orphan
(Guarcello, Lyon & Rosati, 2004). Paternal orphans attended schools in greater
proportions than maternal orphans; male orphans were more likely to attend school than
female orphans. Double orphans less likely to attend school full-time in combination with
work than non orphans. Being a single orphan reduced the probability of attending school
full-time by 11 percentage points, and of attending school in combination with work by
four percentage points. However, research done in Tanzania by Ainsworth et al. (2005)
attempted to measure the impact of adult deaths and orphan status on primary school
attendance and hours spent at school. There was no statistically significant difference in
attendance rates by orphan status. Often children dealing with bereavement have to move
into foster care. Not only are they dealing with the trauma of this bereavement, but they
often have to move households and schools. This disrupts schooling patterns and can be
linked to periods of absenteeism.
14
In many societies, in Africa in particular, a large number of children are fostered
estimated to be 25% of children (Zimmerman, 2003). There can be both positive and
negative effects of fostering on educational access. In many cases children are fostered in
order to allow them greater educational opportunities. However based on an analysis of
black South African children, Zimmerman (2003) claimed foster children were no less
likely than non-orphans to attend school. School attendance is highest for fostered
children in Burundi (Guarcello et al., 2004), compared to children living with their
immediate family. This suggests that children are often being fostered in order to get
better educational opportunities.
Disability status of the child
Because of their status, persons with disabilities are vulnerable and suffer from social
exclusion, stigma, and discrimination (UBOS and Macro International Inc, 2007); this
leads to reduction of their morale of attending school. Pupils with difficulties in seeing,
hearing, walking or climbing stairs, in remembering or concentrating, in self-care, and in
communicating need a conducive environment for participation effectively and friendly
service delivery. For example if the child has a difficulty in walking and he has to walk
for a long distance to get to school, this child is likely to be more absent.
Chimombo et al. (2000) cites Peter’s (2003) claims that ‘the vast majority of children
with disabilities have mild impairments. These children most likely constitute a
significant percentage of grade-level repeaters’, this reduces the pupil’s morale for
schooling and hence an increase in absenteeism.
15
2.3 Socio-economic factors
Type of place of Residence of the pupil
The rate of absenteeism is higher in rural areas than in urban areas as reported by UBOS
and Macro International Inc (2007). Households in rural areas tend to be poorer, schools
more inaccessible, household members less educated and pressures on children to work
to support the household (e.g. in domestic and agricultural duties), greater. While in
urban locations, there tend to be more schools and the choice of options available to
households are greater. However, findings of Eoghan (2008) reveal that in Ireland rates of
non-attendance in primary schools are higher in towns and cities than they are in rural areas.
Research points to distance to school being an important factor in educational access,
particularly for rural populations (Boyle et al., 2002; Mfum-Mensah, 2002; Nekatibeb,
2002; Porteus et al., 2000). In research carried out in Ethiopia and Guinea, ‘as elsewhere,
the greater is the distance from home to school, the more likely it is that a child will be
absent (Colclough, Rose & Tembon, 2000); for younger children, particularly if the
journey is deemed too far (Juneja, 2001); for girls where parents/guardians are afraid of
sexual harassment, especially as they grow older (Colclough et al., 2000; Nekatibeb,
2002; the PROBE Team,1999); and for girls who are seen as being ‘weaker’ than boys
(Colclough et al., 2000). Therefore in rural areas where schools are far from pupil’s
homes, pupils are more likely to be absent than urban pupils were schools are near to
pupils’ homes and means of transport to school like taxis are in plenty.
16
Household size
How many members are within the household is important in many cases and can be a
‘significant determinant’ of absenteeism. But research differs on the impact of household
size on absenteeism. Some studies indicate that with larger household sizes (and in
particular numbers of children) the financial burden/potential workload is greater;
children are less likely to attend school. However, with more children in the household,
jobs can be spread between them and siblings more likely to attend, e.g. in Ethiopia
(Colclough et al., 2000). Research in Pakistan indicates that while an increase in family
size reduces a girl child’s household work, the presence of younger children appears to
increase their workload (Hakzira & Bedi, 2003). As in other studies, the number of
siblings under 5 years of age has a strongly negative impact on older girls’ schooling and
leads to absenteeism.
Highest education level attained by the household head
Literate household heads are not only more likely than illiterate ones to enroll their
daughters and sons in school, but also to ensure that the school attendance of their
children is regular. Literate household heads feel it is profitable to educate their children
and look at sending their children to school as a wise investment for the future unlike
illiterate ones. Literate household heads will do whatever is required for the child not to
miss school like providing scholastic materials, paying fees in time. To illiterate parents
education is perceived to be of limited worth when after completion of schooling
(Primary), there is no substantial difference between someone who has been to school
and one who hasn’t. Some researchers indicate that non-educated parents cannot provide
17
the support or often do not appreciate the benefits of schooling (Juneja, 2001; Pryor &
Ampiah, 2003), children of such parents/household heads will be more absent than those
of educated ones.
The household head is a role model to the rest of the household members (Hunter & May,
2003); heads that are educated are likely to inspire schooling children to attain high
qualifications like theirs’ and one way to achieve this is regular attendance of school.
Therefore pupils from households headed by uneducated heads lack education role
models and are more likely to be absent from school than those from households of
educated heads.
Household socio-economic status
Ownership of a radio and television leads access to efficient communication this can help
pupil’s to see and listen to highly qualified people like doctors and be inspired to study to
be like them, refrigerator ownership as an indication of the capacity for hygienic storage
of foods to control illness, ownership of a means of transportation as a sign of the
household’s level of access to public places like schools, ownership of a farm of animals
that increases the demand for the child labor and type of water source that can contribute
to water contamination that leads to illness hence absenteeism. Therefore there is a
positive correlation between household’s wealth index the pupil’s rates of absenteeism.
18
CHAPTER THREE
METHODOLOGY
3.1 Introduction
This chapter discusses the methodology that was employed to obtain the results of this
study. It reflects the source of data, description of variables and data analysis.
3.2 Data source
This study employed secondary cross-sectional data on absenteeism among primary
school pupils from 2006 Uganda Demographic and Health Survey which was a
descriptive statistical survey.
2006 UDHS was designed to allow separate estimates at the national level and for urban
and rural areas of the country. Portions of the northern region were over sampled in order
to provide estimates for two special areas of interest: Karamoja and internally displaced
persons (IDP) camps. A sample of 9,864 households was selected for the 2006 UDHS
survey. This sample was selected in two stages. In the first stage, 321 clusters were
selected from among a list of clusters sampled in the 2005-2006 Uganda National
Household Survey that was carried out by UBOS. This matching of samples was
conducted in order to allow for linking of 2006 UDHS health indicators to poverty data
from the 2005-2006 UNHS. The clusters from the Uganda National Household Survey
were in turn selected from the 2002 Census sample frame. For the UDHS 2006, an
additional 17 clusters were selected from the 2002 Census frame in Karamoja in order to
increase the sample size to allow for reporting of Karamoja-specific estimates in the
19
UDHS. Finally, 30 IDP camps were selected from a list of camps compiled by the United
Nations Office for the Coordination of Human Affairs (UN OCHA) as of July 2005,
completing a total of 368 clusters.
In the second stage, households in each cluster were selected based on a complete listing
of households. In the 321 clusters that were included in the UNHS sample, the lists of
households used were those generated during the UNHS listing operations April-August
2005. The UNHS sampled ten households per cluster. All ten were purposively included
in the UDHS sample. An additional 15 to 20 households were randomly selected in each
cluster. The 17 additional clusters in Karamoja were listed, and 27 households were
selected in each cluster. The selected IDP camps were divided into segments because of
their large size, and one segment selected in each camp. Then a listing operation was
carried out in the selected segment, and 30 households were selected in each camp from
the segment of the map that was listed. All women age 15-49 who were either permanent
residents of the households in the 2006 UDHS sample or visitors present in the household
on the night before the survey were eligible to be interviewed. In addition, in a subsample of one-third of all the households selected for the survey, all men age 15-54 were
eligible to be interviewed if they were either permanent residents or visitors present in the
household on the night before the survey.
3.2.1 Description of variables
i) Dependent variable
The dependent variable was absenteeism among primary school pupils. Absenteeism
from school refers to absence (non-attendance) from school. School absenteeism is of
two types, namely: authorized absence and unauthorized absence. Authorized absence is
20
an absence with permission from the teacher or other authorized representative of the
school. This includes instances of absence for which a satisfactory explanation has been
provided (e.g. illness, family bereavement, religious observance) while an unauthorized
absence is absence without permission from a teacher or other authorized representative
of the school. This includes all unexplained or unjustified absences. However students
under taking approved and supervised educational activities conducted away from the
school (e.g. educational visits) are deemed to be present at the school. In this study both
authorized absence and unauthorized absence were treated as absence from school.
ii)
Independent variables
Education level of the household head
This was a categorical variable with categories, namely: no education, primary,
secondary and more than secondary.
Survivorship status of the parents of the pupil
This was a categorical variable with categories, namely: double orphan, single orphan
and not orphan.
Sex of the pupil
This was a categorical variable with two categories, that is, males and females.
Sex of the household head
This was a categorical variable with two categories, that is, males and females.
Household size
This was categorized into two groups, namely: 7members and below and more than 7
members.
21
Age of the house hold head
This was categorized into three groups, that is, less than 30, 30-49 and more than 49.
Residence
This was a categorical variable with two categories, that is, urban and rural.
Relationship of the pupil to the household head
This was a categorical variable with categories, namely: head, other relative,
son/daughter, grand child, brother/sister, niece/nephew, adopted/foster/step child.
Household socio-economic status
This was a categorical variable with categories, namely: poorest, poorer, middle, richer
and richest.
Disability status of the pupil
This was a categorical variable with categories, namely: no disability, one type of
disability, two types of disabilities and more than two types of disabilities.
3.3 Data analysis
The data was analyzed using STATA Version 9.0 software.
Analysis was done at three levels; univariate, bivariate and multivariate analysis.
3.3.1 Univariate analysis
Descriptive statistics was used to summarize the characteristics of the household.
Frequency tables were used to summarize all the independent variables.
22
3.3.2 Bivariate analysis
Bivariate analysis was conducted to establish the associations between pupil absenteeism
and independent categorical variables. Cross- tabulations were done and the association
between absenteeism among primary school pupils and the categorical independent
variables were discussed. This was done using the Pearson’s Chi-Square test. The chisquare statistic (  2 ) that was used is of the form;
r
c
  
2
(Oij  Eij )2
i 1 j 1
Eij
……………………………………………………………(3.1)
Where;
r = number of categories of the independent variable
c = number of categories of pupil absenteeism
Oij = observed frequency in row i and column j
Eij = expected frequency in the row i and column j
With the  2 test, the analysis was based on the p-value of 0.05 as the level of
significance. The probability of rejecting/accepting the hypothesis being tested. If the pvalue was greater than or equal to 0.05, then the statistical relationship between pupil
absenteeism and independent variable under study was not significant. On the other hand
if the p-value was found to be less than 0.05, then, there was a significant statistical
relationship between the two variables such that if one of them changed, the other would
also change.
23
3.3.3 Multivariate analysis
The multivariate analysis was used to establish the relationship between absenteeism
among primary school pupils (dependent variable) and several independent variables.
Since absenteeism among primary school pupils was a binary outcome (attended all
school days during the week preceding the survey or absent from school for one or more
days during the school week preceding the interview), a complementary log-log model
was used.
Yi = 1,
pupil was absent from school for one or more days during the school week
preceding the interview.
0,
pupil attended for all school days during the school week preceding the
interview.
The Complementary log-Log model was used to establish the most significant factors
determining absenteeism among primary school pupils. The form of the complementary
log-log model is as below;
 
log  log 1 
p      x   x
i
1
1i
2
2i
 ...  
k
x
ki
…………………………….(3.2)
Where;
p
i
is the probability that the pupil i was absent from school for one or more days during
the school week preceding the interview.
 is a constant

j
for j  1,2,..., k are parameter estimates that explain the change in the absenteeism
among primary school pupils as a result of change in the independent variable.
x
ji
; i  1, 2,..., k are the independent variables
24
While fitting the model, the independent variables that were used at this level of analysis
were only those variables which had shown a strong association with absenteeism among
primary school pupils whose p-value would have been less than 0.05.
The researcher computed relative risks by first deriving the expression for
p
i
from
equation (3.2). The expression takes the form below;
p  1 e
e
  1 X 1i  .. k X ki
i
Then from the definition of relative risk RR, RR 
P1 / x 
P1 / 0
The expression for RR was derived and is of the form below;
RR 
1  e e
  j
1  e e

……………………………………(3.3)
The results of the complementary log-log model were discussed by looking at the relative
risks and the p-values corresponding to different coefficients. The p-values which were
less than 0.05 were considered statistically significant and the relative risks which were
less than one were taken to be reduced risks and those greater than one were taken to be
increased risks.
25
CHAPTER FOUR
DETERMINANTS OF ABSENTEEISM AMONG PRIMARY SCHOOL PUPILS
4.1 Introduction
This chapter presents and discusses the findings of the study. The analysis was done at
three levels, namely: univariate, bivariate and multivariate analysis.
4.2 Absenteeism among primary school pupils
The researcher summarized absenteeism among primary school pupils as indicated in
Table 4.1.
Table 4.1: Percentage distribution of absenteeism among primary school pupils
Absent
Frequency
Percentage
No
6,634
80.2
Yes
1,636
19.8
Total
8,270
100.0
19.8 percent of the pupils missed school compared to 80.2 percent who attended all the
school days.
4.3 Univariate analysis and Bivariate analysis
In this study, at the univariate analysis the researcher summarized all the indepedent
variables using frequency tables.
Bivariate analysis was done to determine and explain the relationship between; socioeconomic factors and absenteeism among primary school pupils and socio-demographic
factors and absenteeism among primary school pupils. At this level, cross tabulations of
26
the independent categorical variables and absenteeism among primary school pupils was
done and the Chi- square statistic was used to discuss the results.
4.3.1 Socio-demographic factors
Table 4.2 showed that; sex of the pupil (51.4 percent were boys and 48.6 percent were
girls), relationship of the pupil to the household head (0.1 percent were household heads,
69.5 percent were sons/daughters, 15.1 percent were grand children, 2.4 percent were
brothers/sisters, 7.2 percent were nieces/nephews, 3.1 percent were other relatives and 2.6
percent were adopted/foster/step children of household heads), survivorship status of the
parents of the pupil (6.8 percent of the pupils were double orphans, 15.6 percent were
single orphans and 77.6 percent were not orphans) and age of household head ( 8.2
percent had less than 30 years, 61.4 percent were aged from 30 to 49 years and 30.4
percent were above 49 years) were considered in the study, however, it was found out
that they had no statistical significant relationship with absenteeism among primary
school pupils.
27
Table 4.2: Percentage distribution of Socio-Demographic factors and
Cross tabulations of Absenteeism by Socio-Demographic factors
Percentage distribution
Variable
Frequency
(%)
Overall
8270
100.0
Cross tabulations of Absenteeism
by Socio-Demographic factors
2
Number %
(p-value)

absent
Absent
1,636
19.8
7,372
720
124
54
89.1
8.7
1.5
0.7
1,413
166
45
12
19.2
23.1
36.3
22.2
4,252
4,018
51.4
48.6
860
776
20.2
19.3
1.0844
(0.298)
5,751
2,519
69.5
30.5
1,101
535
19.1
21.2
4.8407
(0.028)
10
5,748
1,244
194
599
260
215
0.1
69.5
15.1
2.4
7.2
3.1
2.6
1
1,141
234
26
131
58
45
10.0
19.9
18.8
13.4
21.9
22.3
20.9
9.2053
(0.162)
565
1,285
6,420
6.8
15.6
77.6
107
265
1,264
18.9
20.6
19.7
0.8611
(0.650)
681
5,074
2,515
8.2
61.4
30.4
154
983
499
22.6
19.4
19.8
3.9810
(0.137)
Disability status of the
pupil
No disability
One type of disability
Two types of disabilities
More than two types of
disabilities
Sex of pupil
male
female
Sex of household head
male
female
Relationship of pupil
to the household head
head
Son/daughter
grandchild
Brother/sister
Niece/nephew
Other relative
Adopted/foster/stepchild
Survivorship status of
the parents of the
pupil
Double orphan
Single orphan
Not orphan
Age of household head
Less than 30
30-49
above 49
28.1162
(0.000)
28
Disability status of the pupil
In this study disability status of the pupil was considered to find out its relationship with
absenteeism among primary school pupils. Table 4.2 showed that 89.1 percent of the
pupils didn’t have any disability, 8.7 percent had only one type of disability, 1.5 percent
had two types of disabilities and 0.7 percent had more than two types of disabilities. In
determining the association between disability status of the pupil and pupil absenteeism,
it was found out that; of the pupils with no disability 19.2 percent were absent, 23.1
percent, 36.3 percent and 22.2 percent of the pupils with only one type of disability, two
types of disabilities and more than two types of disabilities respectively were absent as
indicated in Table 4.2. The association between disability status of the pupil and pupil
absenteeism was significant (p= 0.000)
Sex of household head
In this study efforts were made to determine the association between sex of household
head and absenteeism among primary school pupils. It is believed that sex of household
head is associated with pupil absenteeism. Results in Table 4.2 showed that 69.5 percent
of the household heads were males and 30.5 were females. Findings of this study in Table
4.2 showed that of those pupils from male headed households 19.1 percent were absent
and 21.2 percent from female headed households were absent. Pupils from female headed
households were more absent than those from male headed, this could be because males
tend to exert enough control on children as far as school attendance is concerned more
than females. There was a significant relationship between sex of household head and
pupil absenteeism (p=0.028).
29
4.3.2 Socio-economic factors
Household size
Table 4.3 showed that 57 percent of the households had 7 members and below whereas
43 percent had more than 7 members. Further more, 21 percent of the pupils from
households with 7 members and below were absent and those absent from households
with more than 7 members were 18.2 percent. There was a statistical significant
relationship between household size and pupil absenteeism (p= 0.001).
Table 4.3: Percentage distribution of Socio-Economic factors and Cross tabulations
of absenteeism by socio-economic factors
Percentage distribution
Variable
Frequency
(%)
Overall
8270
100.0
Cross tabulations of absenteeism by
socio-economic factors
2
Number
% absent
(p-value)

absent
1,636
19.8
1,646
5,168
1,050
406
19.9
62.5
12.7
4.9
347
1,028
189
72
21.1
19.9
18.0
17.7
4.9648
(0.174)
515
7,755
6.2
93.8
65
1,571
12.6
20.3
17.7472
(0.000)
1950
1,644
1,699
1,854
1,123
23.6
19.9
20.5
22.4
13.6
397
344
360
348
187
20.4
20.9
21.2
18.8
16.7
12.0106
(0.017)
4,711
3,559
57.0
43.0
990
646
21.0
18.2
10.4755
(0.001)
Highest education
level of household
head
No education
Primary education
Secondary education
Higher education
Type of place of
residence
urban
rural
Household socioeconomic status
poorest
poorer
middle
richer
richest
Household size
7 members and below
above 7 members
30
Type of place of residence of the pupil
The type of place of residence of the pupil was considered in the study to find out
whether it had an impact on pupil absenteeism. The results in Table 4.3 indicated that 6.2
percent of the pupils were from Urban and 93.8 percent from Rural. Table 4.3 indicated
that pupil absenteeism was 12.6 percent in urban areas and 20.3 percent in rural areas.
Further more, the results in Table 4.3 indicated that the relationship of type of place of
residence of the pupil with absenteeism among pupils was highly significant (p=0.000).
Household socio-economic status
Household socio-economic status was referred to as how rich or poor the pupil’s
household was. As indicated in Table 4.3, it was observed that 23.6 percent of pupils
came from poorest class, 19.9 percent from poorer class, 20.5 percent from middleclass,
22.4 percent from richer class and 13.6 percent from richest class. From Table 4.3,
absenteeism is high to pupils from middle class (21.2 percent), followed by pupils from
poorer class (20.9 percent), followed by pupils from poorest class (20.4 percent),
followed by pupils from richer class (18.8 percent) and less absent were pupils from
richest class (16.7 percent). It was indicated from the chi-square statistic that the
relationship between household socio-economic status and absenteeism among primary
school pupils was significant (p= 0.017).
4.4 Multivariate analysis
A complementary log-log model was fitted to examine the relationship between the
absenteeism among primary school pupils and the independent variables. This was done
to confirm the results on bivariate analysis. Household size, type of place of residence
31
and disability status of the pupil turned out to be significant; however, household socioeconomic status and sex of household head were not significant as shown by their pvalues in Table 4.4.
Table 4.4: Results of the Complementary log-log regression model of absenteeism
among primary school pupils according to the independent variables
 ( Coefficient)
Significance
RR
-0.138
0.008
0.879
0.460
0.001
1.522
Only one disability
0.201
0.015
1.204
Two disabilities
0.728
0.000
1.925
More than two disabilities
0.154
0.595
1.153
Poorest*
0.047
0.521
1.045
Poorer
0.066
0.365
1.063
Middle
-0.048
0.515
0.956
Richer
-0.090
0.332
0.919
0.093
0.085
1.090
-1.956
0.000
Variable
Household size
7 members and below*
above 7 members
Type of place of residence
Urban*
Rural
Disability status of the pupil
No disability*
Household socio-economic
status
Richest
Sex of household head
Male*
Female
Constant
*Reference category
RR = Relative risk
32
Household size
Table 4.4 showed that pupils from households with above 7 members were at a reduced
risk of absenting themselves from school compared to those ones from households with 7
members and below. This study established that absenteeism among pupils from
households with above 7 members was 0.879 times that of those from households with 7
members and below. This is in agreement with study findings of Colclough et al. (2000)
which associates increase in household size with reduction in pupil absenteeism. This
was statistically significant (p=0.008) and it confirms that absenteeism among primary
school pupils is dependent on household size.
Type of place of residence
The results in Table 4.4 confirmed that there is a significant relationship between the type
of place of residence of the pupil and absenteeism among primary school pupils
(p=0.001). Pupils that were residing in rural areas were at an increased risk of absenting
themselves from school compared to those ones that were residing in urban areas.
Absenteeism among pupils residing in rural areas was found to be 1.522 times that of
those residing in urban areas. This was in agreement with the findings of UBOS and
Macro International inc. (2007) which revealed that the rate of absenteeism is higher in
rural areas than in urban areas, however, in disagreement with the findings of Eoghan
(2008) which revealed that absenteeism is higher in urban areas than in rural areas.
33
Disability status of the pupil
Results in Table 4.4 showed that pupils with all kinds of disabilities were at an increased
risk of absenteeism compared to those without any disability. This could be because of
the status of persons with disabilities; they are vulnerable and suffer from social
exclusion, stigma and discrimination which lead to reduction of their morale of attending
school regularly. In this study it was found out that absenteeism among pupils with only
one type of disability was 1.204 times that of those without any disability. This was
statistically significant (p=0.015). It was also established that the absenteeism among
pupils with two types of disabilities was 1.925 times that of those without any disability.
This was statistically significant (p=0.000).
34
CHAPTER FIVE
SUMMARY OF FINDINGS, CONCLUSIONS AND RECOMMENDATIONS
5.1 Summary of the findings
The researcher analyzed the socio-demographic and socio-economic factors assumed to
be associated with absenteeism among primary school pupils. The analysis was done at
three levels, namely: univariate, bivariate and multivariate analysis.
From univariate analysis; it was observed that household heads included in the study
majority of them were in the age interval of 30-49, followed by those above 49 years and
least were aged less than 30 years. Households included in this study were dominated by
those of 7 members and below as compared to those ones with above 7 members.
Majority of the pupils came from the poorest households and the least came from the
richest households. Pupils from male headed households out weighed those from female
headed ones. Most of the household heads had attained primary level of education,
followed by those with no education, followed by those with secondary education and
few had attained tertiary education level. Majority of the pupils were not orphans,
however, single orphans were more than double orphaned ones. The relationship of the
pupil to the household head was dominated by sons/daughters to the household head and
the least were those pupils who were households themselves. There were more male
pupils than females in the study. Majority of the pupils were residing in rural areas.
Disability status was dominated by pupils with no disability, followed by those with only
one type of disability, two types of disabilities and the least were those with more than
two types of disabilities.
35
From the bivariate analysis, it was found out that the variables that had a significant
association with absenteeism among primary school pupils were: disability status of the
pupil, sex of the household head, type of place of residence, household size and wealth
index. These variables had p-valves less than 0.05 and were taken for multivariate
analysis.
At multivariate analysis, a complementary log-log model was fitted to examine the
relationship between the absenteeism among primary school pupils and the independent
variables. This was done to confirm the results on bivariate analysis. It was found out
that household size, type of place of residence and disability status of the pupil had a
significant impact on pupil absenteeism.
5.2 Conclusions
The study established that household size, type of place of residence and disability status
of the pupil were the significant determinants of absenteeism among primary school
pupils in Uganda. Type of place of residence and disability status of the pupil were
established to increase the risk of absenteeism among primary school pupils. However,
increase in household size was established to reduce the risk of absenteeism among
pupils.
5.3 Recommendations
Disabled pupils were found to absent from school more than those without any disability.
MoES should clearly define the various types of disabilities and sensitize
parents/guardians about them so that they can identify these children accordingly and also
36
should encourage parents to accept their children with disabilities the way they are like
any other normal child and support them in everything that can enable them to attend
school regularly. All schools should ensure that they provide a conducive environment
for disabled pupils for participation effectively and friendly service delivery. The MoES
should set up centers or schools for disabled students in every county or district, facilitate
and equip them with all that is necessary instead of enrolling them in normal schools
where their needs are usually neglected. More still the MoES should reinstate the
inspectors for special needs (disabilities) so that they carry out inspections to identify
disabled students, their unique disability requirements and plan for them accordingly.
Pupils residing in rural areas were found to absent themselves from school more than
those from urban areas. MoES, NGOs, local authorities/local government (LC III and LC
V) and community leaders of all descriptions should strengthen the sensitization of rural
parents/guardians on their roles and responsibilities so as to fulfill their primary parental
responsibility of monitoring their children’s school attendance, providing them with
school requirements and doing everything possible to ensure that their children are
regular at school. For example community leaders should take advantage of all solid
gatherings like LC meetings, speech days, religious functions, weddings etc to speak
about regular attendance of school. In addition, rural pupils should be sensitized on the
dangers of absenteeism.
37
5.4 Areas of further research
The
study
employed
secondary
data
that
did
not
follow
up
pupils’
attendance/absenteeism patterns for a reasonably enough time since data was for only one
week, other researchers can carry out a study capturing pupil’s attendance patterns for
more than one week, say a year or more. In addition, information on variables like cost of
education, distance from household to school which are believed to have an impact on the
attendance patterns of pupils were not captured in the data that was used in this study, a
further study could address itself to the relationship between pupil absenteeism and cost
of education and distance from household to school.
38
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