gender differences in learning outcome

M O N I T O R I N G L E A R N I N G A C H I E V E M E N T ( M L A ) I N R I V E R S

S T A T E P U B L I C S C H O O L S :

V O L U M E I I

Gender Differences in Learning Outcome

(Report)

Prepared for:

Rivers State Ministry of Education

BY

ARBITRAGE CONSULT LIMITED

[email protected]

http://www.google.com.ng/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&docid=N1_M2OgpLYE_LM&tbnid=lBHm1Ohii90QeM:&ved=0CAUQjRw&url=http://www.britishcouncil.org.ng/british-council-receives-funding-to-research-secondary-education-in-nigeria&ei=d49qUtX8G8zbsgarmYHgCg&bvm=bv.55123115,d.d2k&psig=AFQjCNFwOuY-8UdXb03Kih0C3WmPxTo6bQ&ust=1382801634316983

1 Table of Content | Arbitrage Consult Limited

T h e A r b i t r a g e C o n s u l t T e a m

J o y O b a l l u m

N a n c y E n e

A d e y e m i O n a f u y e

A m i n a A r o - l a m b o

B e r n a r d B a s a s o n

O l a t a y o B a b a l o l a

D a n i e l O g h o j a f o r

P r o f . O l a s e n i A k i n t o l a - B e l l o ( L e a d C o n s u l t a n t )

2 Table of Content | Arbitrage Consult Limited

Table of Content

Table of Content ......................................................................................................................................... 2

Executive Summary .................................................................................................................................... 3

CHAPTER 1 .................................................................................................................................................. 5

1.0 INTRODUCTION: CONTEXT AND DESIGN ......................................................................................... 5

1.1 Preamble ...................................................................................................................................... 5

1.3 Objectives of the Study: ............................................................................................................... 7

1.4 Significance of the Study .............................................................................................................. 7

1.6 Methodology and Analysis ............................................................................................... 7

1.6.1 Scope ......................................................................................................................................... 7

1.6.2 Data Source ...................................................................................................................... 8

1.6.3 Data analysis .................................................................................................................... 8

1.7 Organization of this work ............................................................................................................. 9

Chapter Two ............................................................................................................................................. 10

2.0 GENDER DIMENSIONS IN RIVERS STATE ........................................................................................ 10

2.1 Introduction.................................................................................................................................... 10

2.1.1. PART 1: SOCIO-ECONOMIC BCKGROUND .............................................................................. 10

2.1.2.Gender Disparity ..................................................................................................................... 13

Where does the Problem Lie? .......................................................................................................... 13

A Look at the Numbers: Gender Gap in Learning Performance ...................................................... 13

Chapter three ........................................................................................................................................... 51

Factors Associated with Gender Differences ....................................................................................... 51

Chapter Four ............................................................................................................................................ 55

Strategies for Addressing Gender Differences ..................................................................................... 55

Strategies in Relation To Learning, Teaching and Assessment ........................................................ 55

Classroom Organization ................................................................................................................... 56

Chapter Five ............................................................................................................................................. 58

Conclusion and Recommendations ...................................................................................................... 58

Recommendations: .......................................................................................................................... 59

Reference ................................................................................................................................................. 60

Appendix .................................................................................................................................................. 63

3 Executive Summary | Arbitrage Consult Limited

Executive Summary In this study, we focused on gender and learning performance in Rivers state public schools;

its aim was to examine the gender dimension of learning achievement in public primary and

secondary schools in Rivers state: A Monitoring Learning Achievement (MLA) Survey. Using

Article 26 of the Universal Declaration of Human Rights (1948), the Jomtien Declaration (1990)

and the Millennium Development Goals (2000) as conceptual framework, the paper discussed

the imperatives of gender equity in primary and secondary education against the background

of the challenges and prospects. Data on 2013 Monitoring Learning Achievement (MLA)

assessment, school enrolment, dropout rate and teaching manpower were obtained from

primary and secondary sources for the analysis. The result of the analysis show:

There are gender gaps in Rivers state public schools; these gaps exist in enrollments,

learning performance, repeaters rate, dropout rate and teaching manpower.

The Rivers state government does not discriminate against females in the field of

education. However, factors that can be directly responsible for gender disparity in

public schools include: socio-economic influences, gender themes in current

educational practices, motivational and psychological issues, school environment, and

teacher attitude.

From current enrollment statistics, Gender Parity Index (GPI) is 1.07 in 2011/2012

academic year against GPI of 0.97 in 2005. Since a GPI of 1 indicates parity between

the sexes; a GPI that varies between 0 and 1 typically means a disparity in favour of

males; whereas a GPI greater than 1 indicates a disparity in favour of females. This

implies that Rivers state has achieved the MDG’s goals of attaining gender parity Index

(GPI) of between 0.97 and 1.03.

More boys than girls are perceived to be underperforming from the results of 2013

Monitoring Learning Achievement (MLA) survey, showing that, except in numeracy

and mathematics in secondary schools; girls generally performed better than boys

across the various Local Government Areas. Also this is validated by the fact that there

are more boys than girls who are repeating a class (or more) of schooling.

Dropout rate is higher for girls in both primary and secondary schools.

There are more female to male teachers across public schools in the state.

On the basis of these findings, it was recommended that: Government should organise

workshops for capacity building and policy advocacy on gender issues, which will create the

needed awareness in this regards. Also due to the high dropout rate for female; it is important

for the state government to setup, implement, monitor an intervention programs to address

the females drop out problem. For example, a program to eradicate child labour and promote

Gender and Family values. This catch-up program should be linked to a special curriculum that

facilitates those girls and boys to finish their primary and secondary school. The use of

4 | Arbitrage Consult Limited

gender-sensitive textbooks and curriculum for girls will help bridge the gender-gap. Finally,

Rivers state government should implement a state performance assessment monitoring

system that can disaggregate performance by gender and the interaction between gender and

the assessment process itself.

5 CHAPTER 1 | Arbitrage Consult Limited

CHAPTER 1

1.0 Introduction: Context and Design

1.1 Preamble

Education is vital to advancing human capital by enabling individuals to develop their

knowledge and skills throughout their lives. Relatively high levels of education are often

related to higher earnings and productivity, better career development, health, life

satisfaction as well as to better investments in education and health of future generations.

There has been a strong case for greater gender equality across the world; this implies greater

educational and economic opportunities for both men and women. However, achieving

greater gender parity remains a big challenge despite the many gains in women’s educational

and employment outcomes.

Gender parity in learning performance has been a subject of focus in the international

community, since the Beijing conference of 1989. The main objective of the Beijing

Conference was to allocate sufficient resources for and monitor the implementation of

educational reforms; while achieving gender equality is seen fundamentally as enhancing

education performance. However, many factors impede gender equality, such as limited

access to schooling, low female enrolment and high school dropout.

Article 26 of the Universal Declaration of Human Rights (1948); the Jomtien Declaration of

1990, both stipulate that basic education should be provided for all children, youth and adults

and the Millennium Development Goals (MDGs) specifically Goal 3, also stress that the goal is

to promote gender equality and eliminate gender disparity in primary and secondary

education, preferably by 2005, and in all levels of education no later than 2015 (United

Nations Millennium Project, 2005).

Similarly, the United Nations in 1975, proclaimed the International Decade for Women in

recognition of the fact that women who constitute about 50 percent of the World’s

population have not been given a fair share of the resources and opportunities in all spheres

of life. The critical importance of gender equity in education is also underscored by the

Millennium Development Goals (MDG’s), and the Dakar goals set for Education for All (EFA)

among other platforms. Gender equity became not only a development imperative but an

essential human rights issue. The assumption is that if education is a basic human right, then

quality education should promote equality of opportunities between sexes.

The aforementioned declarations were reinforced by the Convention on the Right of the Child

(CRC) in 1989, which states that children may not be excluded from any right, including

education, based on race, sex, disability, and economic status.


The 1997 Human Development Report (HDR) of the United Nation’s Development Programme

observes that “no society treats its women as well as its men”. The report further elaborates

that gender inequality is strongly associated with Human Poverty Index (HPI), and substantial

progress in gender equality has been made in only few societies, as women suffer the double

deprivation of gender disparity and low achievement in education.

Further, the United Nations Decade of Education for Sustainable Development (DESD) is a

complex and far-reaching undertaking. The overall goal of the DESD is to integrate the

principles of sustainable development into teaching and learning. This educational effort will

encourage changes in behavior that will create a more sustainable future in terms of

environmental integrity, economic viability, and a just society for present and future

generations.

In spite of these declarations, gender equity has remained a daunting challenge. The Forum

for African Women Educationalists (FAWE) observed many years ago that many more girls

than boys are left out in the education system, and emphasized the need for countries in the

Region to identify effective strategic intervention that will enhance the improvement of girls’

participation (FAWE, 2001). The forum also identified factors such as low socio-economic

status, long walking distances, poor policies that are not gender specific, socio-cultural

attitudes and other school related factors as responsible for the disparity.

Data collected in 1999 from 154 countries showed that 115.4 million school age children were

not in school and of these, 56% were girls, (UNESCO 2002); and 94% of these came from the

LCDS while one - third were from sub-Sahara Africa. Indeed gender inequity holds back the

growth of individuals, the development of countries and the evolution of societies, to the

disadvantage of both men and women, (UNESCO; 2004).

Analysis done in 128 countries showed that despite the pursuit of the MDG’s goals for

attaining gender parity Index GPI of between 0.97 and 1.03, 56% of the countries mostly in

sub-Saharan Africa and South West Asia were far behind. As at 2000, sub-Saharan Africa stood

at the average GPI of 0.89; an indication that Gender Equity Recurrent for girls has become

increasingly significant. In countries where enrolment is high, the trend has been that the

participation and performance of girls lagged behind that of boys and thus been aggravated

by high repetition rate; high dropout rate and low retention rate.

In response to the global commitment to bridge the gender gap in education, the Rivers state

government, through the Ministry of Education, developed the Blueprint on Education and

have been implementing strategic initiatives designed to enhance the educational sector. One

of such initiatives led to the conduct of the monitoring learning achievement (MLA) survey; in

other to assess if student are actually learning; and also focusing on bridging the knowledge

and capacity gaps between males and females and sought to provide the necessary leverages

to bring about gender equity in certain critical domains of education.


1.3 Objectives of the Study:

The general objective of this study is to assess if there are gender disparities in learning

performance and to highlight which of the gender has a better learning performance based on

the 2013 MLA assessment. This paper therefore assessed the gender difference in learning

performance of Primary four pupils and JSS two students of public schools in Rivers state. The

following questions were addressed in this study: Does enrolment gap exists and is there a

gendered achievement in favor of female pupils and students? If so, is the difference

significant? This research was carried out to give a description of learning performance of

females as compared to males in the 2013 MLA assessment in Rivers state.

The following hypotheses were formulated for the study.

Ho1: There is no significant difference in the academic performance of female and male

pupils/students in the 2013 MLA assessment in Rivers state.

Ho2: There is significant difference in the academic performance of female and male

pupils/students in the 2013 MLA assessment in Rivers state.

1.4 Significance of the Study

The significance of the study is to evaluate gender equity in performance, and determine the

extent to which River state has closed the gaps. This study will help to present an evidence-

based framework that can assist stakeholders in the education policy formulation process as it

affects gender. Essentially, it should be useful to the Rivers state government, the federal

government, civil society, International communities, public and private organization and the

entire citizens of the nation. More importantly, the findings from this study will be useful for

educational policy makers as it will reveal the state of education as regards to enrolment and

gendered result of learning performance. This will in turn enable the government to direct her

effort towards sustaining of students interest, and eventually the growth and the

development of education in Nigeria and Rivers state in particular.

Methodology and Analysis

1.6.1 Scope

The research work covers the entire public primary and secondary schools in Rivers state.

Questionnaires were administered in 6 learning domains across 916 public primary schools

and 276 junior secondary schools. The study covered not only the gender aspects of

performance, but the influence of residential location (rural versus urban) as well as other

socio-economic factors that may influence pupils’ and students learning outcome. The

population of the study is a total population of 15560 pupils and students comprising of

11,862 primary four pupils and 3,698 JSS2 students across the state. The proportion of male to

female was randomly selected for the 2013 MLA assessment, and all the students were tested

in various learning domains and their sub-components; as follows:

Learning Domain for Primary Four Pupils.


Literacy

Comprehension

Grammar

Vocabulary

Numeracy

Numbers

Measurement

Quantitative

Life Skills

Health

Civic

Technology

JSS2 Student Assessments were based on the following domains:

English Language

Comprehension

Grammar

Vocabulary

Mathematics

Numbers

Algebra

Geometry

General Science

Data Source

This research study is limited to data collected from the Monitoring of Learning Achievement

(MLA) survey conducted in Rivers State between July–August 2013, and the Rivers State

Schools Census Report, for 2011/2012. It is a combination of primary and secondary sources

of data.

Data Analysis

Test scores of student from different learning were analyzed using descriptive statistics

employing frequencies, percentages, means, standard deviations, bar charts, line graphs and

t-tests and z-statistics. We then estimate the factors associated with gender differences using


single-equation regression model (ANOVA model) and dummy variables to point out

differences, if they exist, between boy’s and girl’s performance in the learning domain.

1.7 Organization of this Work

This work is organized into five chapters. Chapter one (context and design) comprises of

general introduction such as: Background to the study, statement of the problem, study

objective, significance and scope of the study, and research methodology.

Chapter two, (Gender Dimensions in Rivers state) has two parts, Part 1: Socio-Economic

Background of Rivers state; giving a brief description of socio-economic issues with emphasis

on gender status in the state, part 2: Gender disparities: Where does the problem lie?; this

part delved into the average gender gap in learning performance, asking the question: where

the problem really resides? It revealed a complex picture of gender differences and other

inequalities in education, all of which need to be taken into account.

In Chapter three (Factors associated with gender differences) we highlight the factors

associated with gender differences based on extant research analysis, by estimating the

factors associated with gender differences using single-equation regression model(ANOVA

model) and dummy variables to point out differences, if they exist, between boys’ and girls’

performance in each of the learning domains.

In Chapter four (Strategies for addressing gender differences) we look at some strategies

aimed at addressing underperformance. Strategies perceived to be successful include; study

support, mentoring, and building confidence, self-esteem and developing systems of target-

setting for individual pupils, and their implications for gender differences because more boys

than girls were perceived to be under-performing.

Chapter five concludes and makes recommendations based on the findings.

10 Chapter Two | Arbitrage Consult Limited

Chapter Two

2.0 Gender Dimensions in Rivers State

2.1 Introduction

This chapter has three parts. Part 1: Socio-Economic Background of Rivers state; is a brief

description of socio-economic issues with emphasis on gender status in the state; Part 2:

Gender disparities: Where does the problem lie? Part 3: Gender Analysis of Other Indicators of

Learning Performance.

This part is an in-depth analysis of the average gender gap in learning performance, asking the

question: where the problem lay? It revealed a complex picture of gender differences and

other inequalities in education, all of which need to be taken into account.

2.1.1. Part 1: Socio-Economic Bckground

Rivers state was created in 1967 with the split of the eastern region of Nigeria. Its capital is

Port Harcourt. It is bounded on the south by the Atlantic Ocean, to the north by Imo, Abia and

Anambra states, to the east by Akwa Ibom state, to the west by Bayelsa and Delta states.

Rivers state is home to a variety of ethnic groups, including Abua, Andoni, Ekpeye, Engenni

,Etche, Ibani, Ikwerre, Kalabari, Ogba/Egbema/Ndoni, Okrika and Ogoni. The State is the 5th

most populous State in Nigeria. The 2006 National Population Census places the population

of the state at 5,133,400, and of this population; 2,809,840 and 2,474,735 constitute the male

and female population respectively. It also has a school age children population of 1,866744.

Rivers state is currently made up of 23 local government areas. These are Abua/ Odual,

Ahoada East, Ahoada West, Andoni, Asari /Toru, Akuku/Toru, Bonny, Degema, Eleme,

Emohua, Etche, Gokana, Ikwerre, Khana, Obio /Akpor, Ogba/Egbema/Ndoni, Ogu/Bolo,

Okrika, Omuma, Opobo/Nkoro, Oyigbo, Port Harcourt, and Tai. Port Harcourt, the state’s

capital is Nigeria’s second largest commercial and agricultural centre and has the second

busiest seaport in Nigeria. Agriculture is the main occupation of the people of River State. The

strategic importance of Rivers State in the economic equation of Nigeria earned her the name

“treasure base of the nation”; due to the fact that Rivers state accounts for more than 48% of

Nigeria crude oil production and also one of the largest economies in Nigeria, mainly because

of its crude oil and heavy presence of oil and gas related industries.

Accordingly, there is an increase in the influx of people into the State from other States,

including expatriates. With the increase in population, this leads to an increase in demand for

basic education. Paradoxically, poverty is still prevalent in the state. The poverty profile of the

state is shown in a recent study by MDG (2008); Table1 below illustrates that in Rivers state,

the poverty line is N 12,500 and the poverty incidence is 31.5% this means that 31.5% of the

household in Rivers state were poor or the income of 31% of population is below the poverty

line of N 12,500. The poverty gap of 23.4% is the equivalent amount that needs to be

transferred to the poor in other to bring them to the poverty line. The estimated poverty gap


for the LGAs ranges from 0.3 percent in Eleme to as high as 41.2 percent in Degema. Other

LGAs with high Poverty Gap ratio were Ogu/Bolo and Bonny. The Gini Coefficient which gives

a more precise and quantifiable measure of inequality and also provides a solid understanding

of the direction of concentration and distribution of income among groups. The Gini

Coefficient is 0.58 in the state; this implies that the income inequality between the rich and

poor is high. However, LGAs experienced different levels of income or expenditure disparity.

While, Tai (0.19), Gokana (0.28), Eleme (0.37), Emuoha (0.40), Ikwerre (0.41) and

Abua/Oduah (0.42) have lesser income/expenditure spread than the state average; Degema

(0.82), Bonny (0.68), Ahoada East (0.62), Onelga (0.61) and Okrika (0.59) have higher

income/expenditure spread than the state average; Ogu/Bolo (0.58) has the same

income/expenditure spread as the state average. It is curious to observe that LGA, with high

poverty incidence(headcount ratio) also have high poverty gap ratio and higher than average

Gini.

Table 1: Poverty Indicators by LGAs

Source: MDG, 2008

The prevalence of poverty in the state affects the learning performance of pupils and students

in the state, as it is still classified as one of the educationally disadvantaged States in Nigeria.

In spite of the existence of 2292 public primary and secondary schools and 1244 private

primary and secondary schools (Rivers State School Census Report, 2012) – an indication that

State

Poverty Line Headcount Ratio %

Poverty gap ratio

Gini Coefficient

N 12,500 31.5 23.4 0.58

Local Government Area (LGA) Headcount Ratio % Poverty gap ratio Gini Coefficient

Abua/Odua 21.7 8.91 0.42

Ahoada East 33.3 20.02 0.62

Ikwerre 16.7 8.78 0.41

Emuoha 28.3 20.17 0.4

Onelga 12.5 12.5 0.61

Eleme 0.83 0.3 0.37

Tai 1.67 1.67 0.19

Bonny 30.8 30.83 0.68

Degema 41.7 41.67 0.82

Okrika 15.7 15.15 0.59

Ogu/Bolo 40.0 40.0 0.58

Gokana 5.8 0.96 0.28


the existing private and secondary schools cannot accommodate the increasing demand for

primary and secondary education.

Also from the baseline survey as illustrated in Volume One of this survey, we observed a high

influence of poverty on the pupils and students, which led to the deduction that poverty

keeps many children away from schools; The survey shows that 61% of school age children

don’t have breakfast before going to school, while Only about 39% of respondents were well

fed. Since hungry children are less likely to concentrate in class, this could result in poor

performance and can even result to absenteeism. Again, poverty contributes to high drop-

outs and low performance due to irregular school attendance, a study by Arbitrage Consult

(2013) on out of school children in Rivers state showed that 82.44% of dropout is due to

poverty. This further reinforces our earlier reference that “gender inequality is strongly

associated with Human Poverty Index (HPI), and substantial progress in gender equality has

been made in only few societies, as women suffer the double deprivation of gender disparity

and low achievement in education”, {Human Development Report (HDR) 1997}. This is proven

by the fact that most parents in African communities largely have preferences for educating

male children, hence family development efforts are invested in boys while girls are treated as

second fiddles. Thus, this attitude generally contributes to low enrolment, low participation

and poor performance of girls in schools. The above factors are rendered more complex by

drop outs due to teenage pregnancy and early marriages. Our baseline survey also reveals

that there is a disparity in the view of parent as regards to the education of their children,

19% of the parents believe that male child should be educated more than girl child, 38%

responded “Yes” to the question “if male child should be educated more than the female”,

while 43% were indifferent. Consequently, this leads to gender disparity (gaps) in enrollment

and eventually, performance of pupils and students.

Eliminating gender disparity is understood to mean overcoming the barriers to equal access to

and achievement in schooling for girls and boys. Thus, gender parity is measured by the

enrolment strength of boys and girls and the completion rate. That is why the Task Force on

the MDGs (2004) states “that working to achieve the stipulated targets in the MDGs should

look beyond access to forging collaboration among the various actors to adopt best practices

to improve curriculum and pedagogy”. This also involves eliminating factors that impede the

education of the girl child; these include:

Poverty and economic issues especially with girls being sent to engage in income

generating ventures.

Early marriage and teenage pregnancy, as about 30% of school age girls drop out of

school.

Inadequate school infrastructure such as classroom space, furniture, equipment and

other educational inputs.

Cultural and religious biases especially in communities predominantly Islamic


Gender bias in curricula and pedagogy, and

Inadequate and poorly trained teachers.

2.1.2. Part 2: Gender Disparity

Where does the Problem Lie?

Dissimilarities between girls and boys learning performance outcomes have been issues of

concern generally, and not only in Rivers state. There has been awareness that some aspects

of school education may contribute to the disadvantaged position of women in society and in

employment. More recently, there has been concern that the levels of attainment of boys in

school examinations have been lower than those of girls. Important issues of equality of

opportunity for females and males need to be addressed by the education system. Gender

differences in learning performance have become an increasing focus of policy over the past

few years because of their implications for strategies to raise standards of performance in

schools in Rivers state. If the State targets for raising learning performance are to be met it is

important that pupils of both genders should achieve all they can.

A peak at the Numbers: Gender Gap in Learning Performance

Primary and Secondary Education

With an enabling environment and policies in place, Rivers state has made strong progress in

improving access to education at all levels, and improving gender parity at the primary and

secondary levels, with respect to achieving the MDG goals. Despite these efforts, gender

disparities still exist in public primary and secondary schools in the state: This part went

beneath the average gender gap in learning performance, to ask the question: where the

problem really is? It revealed a complex picture of gender differences and other inequalities in

education, all of which need to be taken into account

Enrollment

The tables below show a summary of enrollment in Rivers state school. Tables 1A and 1B

provide data of the enrolment of pupils and students in primary and secondary schools in the

2011/2012 academic session. Rivers State has 23 Local Government Areas with a total of 3536

public and private schools; i.e. 2292 public schools, and 1,244 private primaries and secondary

at the time of executing this study. Table 1B further shows that in the 2011/2012 academic

session, a total of 532,000 students enrolled, and of this number, 257,505 or 48.4%

represented male enrolment, while 274495 or 51.6% represented female enrolment. The

population of the state is 5,185,400 (2006 census figure), of this figure 33% of this population

is supposed to be in schools (population of school –age-children), which translates to

1,712,591 pupils and students, ironically only 1,459,813 are in school and 252,778 children are

out of school(NPC,2009). Furthermore, figure 1 illustrates that: enrollment is highest at

Obio/Akpor and lowest at Ogu Bolo, while girls enrollment is lowest in Abua/Odua at 48.94%

and highest in Port Harcount LGA (PHALGA) with 51.9%; Similarly, for the junior secondary


school; girls enrollment is lowest in Ahoada west and highest in PHALGA, and in the senior

secondary school category, girls enrollment is lowest at Degema and highest at PHALGA.

Table 1A: Number of public schools, enrolment and teachers

Level Number of schools

Number of pupils Number of teachers

Male Female Total Male Female Total

Pre-primary and primary

912 21143 23494 44637 2756 4805 7573

Primary only

895 123440 127378 250818 2756 4805 7573

Junior secondary *

260 44175 49405 93580 2305 2670 4975

Senior secondary *

225 47627 53589 101216 1904 1064 2968

Grand total 2292 236385 253866 490251 9721 13344 23089

Source: State School Census Report 2011-2012


Table 1b: Summary Analysis of by gender and LGEA (2011-2012)

LGEA Primary School Total Junior secondary school Total total of Senior secondary school Total Total Gender grand total Gender ratio

Pupils Girls % girls Students Girls % girls Students Girls %% girls % girls Boys Girls Total

ABUA/ODUAL 7371 3607 48.94% 1770 979 55.31% 4288 2237 52.17% 6606 6823 13429 1.03 AHOADA EAST 12028 6035 50.17% 5377 2537 47.18% 5148 2693 52.31% 11288 11265 22553 0.99 AHOADA WEST 12634 6283 49.73% 2763 1235 44.70% 2152 1005 46.70% 9026 8523 17549 0.95 AKUKU-TORU 4364 2244 51.42% 1302 682 52.38% 1044 593 56.80% 3191 3519 6710 1.10 ANDONI 12237 6053 49.46% 3453 1550 44.89% 3919 1902 48.53% 10104 9505 19609 0.94 ASALGA 2746 1363 49.64% 1546 697 45.08% 1743 849 48.71% 3126 2909 6035 0.93 BONNY 8111 4065 50.12% 3142 1680 53.47% 2188 1190 54.39% 6506 6935 13441 1.07 DEGEMA 3953 1979 50.06% 1163 576 49.53% 1075 496 46.14% 3140 3051 6191 0.97 ELEME 10968 5751 52.43% 4485 2555 56.97% 3288 1750 53.22% 8685 10056 18741 1.16 EMOHUA 13535 6649 49.12% 5445 2607 47.88% 6648 3201 48.15% 13171 12457 25628 0.95 ETCHE 17263 8820 51.09% 6391 3292 51.51% 7928 3911 49.33% 15559 16023 31582 1.03 GOKANA 16298 8290 50.87% 5199 2607 50.14% 7077 3676 51.94% 14001 14573 28574 1.04 IKWERRE 11719 5935 50.64% 4669 2308 49.43% 4951 2481 50.11% 10615 10724 21339 1.01 KHANA 23348 11785 50.48% 10159 5281 51.98% 9401 4735 50.37% 21107 21801 42908 1.03 OBIO/AKPOR 37952 19751 52.04% 27077 15358 56.72% 17313 10422 60.20% 36811 45531 82342 1.24 OGU/BOLO 2476 1236 49.92% 374 191 51.07% 384 212 55.21% 1595 1639 3234 1.03 OKRIKA 9730 4929 50.66% 2473 1170 47.31% 2132 1087 50.98% 7149 7186 14335 1.01 OMUMA 5522 2855 51.70% 1703 834 48.97% 1916 924 48.23% 4528 4613 9141 1.02 ONELGA 25172 12577 49.96% 12169 6031 49.56% 11533 5743 49.80% 24523 24351 48874 0.99 OPOBO/NKORO 3614 1838 50.86% 1036 487 47.01% 333 150 45.05% 2508 2475 4983 0.99 OYIGBO 15544 7919 50.95% 8512 4456 52.35% 7766 3998 51.48% 15449 16373 31822 1.06 PHALGA 28957 15025 51.89% 4933 3170 64.26% 12995 7879 60.63% 20811 26074 46885 1.25 TAI 10649 5412 50.82% 2119 1147 54.13% 3327 1530 45.99% 8006 8089 16095 1.01 Grand Total 296191 150401 50.78% 117260 61430 52.39% 118549 62664 52.86% 257505 274495 532000 1.07 Source: State School Census Report 2011-2012


Figure 1: Graphical Illustration of School Enrollment by Gender and LGA


Gender Ratio

Gender ratio is an indicator for measuring gender balance in enrolment between boys and

girls. It is the ratio of female gross enrolment to male gross enrolment. If the ratio is 1 there is

a perfect balance in male and female participation. If the gender ratio is less than 1, there is

gender imbalance in favour of males. On the other hand, if the gender ratio is greater than 1,

the imbalance is in favour of girls. Across the state, (Figure 2), there is gender imbalance in

favour of females. Gender ratio for the 2011-2012 sessions was 1.07. This means that girls had

greater access to primary and secondary education than boys.

The picture is different when participation in the primary school is disaggregated by LGAs.

Fifteen LGAs namely: Abua\ Odua, Akuku-Toru, Bonny, Eleme, Etche, Obio Akpor, Gokana,

Ikwerre, Khanna, Ogu/ Bolo, Okrika, Omuma, Oyigbo, PHALGA, and Tai had average gender

ratios which are greater that one; suggesting imbalance in access to primary education in

these LGA in favour of females. On the contrary, the remaining 8 LGAs had gender ratios of

less than one.


Figure 2: School enrollment gender ratio by LGA

Performance

The Analysis of Gender gaps in learning performance is a very important component of the

2013 Monitoring Learning achievement (MLA) survey. The contention is that gender-equity in

public schools in Rivers State can be achieved by understanding the dimension of gender

disparity in learning performance in the schools. From the result of pupils and students

assessment in the 2013 MLA survey in Rivers state as illustrated in Tables 2 and 3, we found

that there are differences in performance of pupils and students in the different learning

domains across LGAs with respect to gender: on the average, boys perform marginally better

in Numeracy and mathematics and general science whereas girls perform better in Literacy

and English language. However, the advantage of girls in Literacy and English Language is

larger than the advantage of boys in Mathematics.


Table 2: Analysis of Primary School Performances by LGAs in Literacy, Numeracy and Life

Skills test by Gender

LGA LITERACY NUMERACY LIFE SKILL

MALE FEMALE MALE FEMALE MALE FEMALE

Abua/ODUA 67.40 67.50 58.50 57.72 79.72 80.95

Ahoada East 56.80 58.40 40.30 41.52 72.02 73.96

Ahoada West 45.70 50.60 47.80 46.00 55.36 53.91

Andoni 54.60 56.00 47.70 48.64 69.50 90.35

Akuku Toru 66.90 70.10 46.20 49.59 70.64 72.67

Asari Toru 62.50 68.50 39.70 40.09 68.52 71.95

Bonny 61.20 63.00 64.80 68.67 70.35 70.85

Degema 64.80 64.60 40.18 37.92 71.44 73.38

Eleme 56.50 56.50 57.12 57.09 71.51 71.54

Emohua 53.00 53.90 46.23 46.24 68.67 69.69

Etche 66.30 66.90 44.50 46.80 72.40 74.70

Gokana 55.40 53.70 46.67 40.59 61.66 59.02

Ikwere 65.90 61.60 60.57 54.17 74.82 78.54

Khana 56.80 59.50 48.43 48.67 69.94 69.73

Obio/Akpor 61.80 64.90 44.79 43.43 83.77 82.34

Onelga 61.90 59.90 73.26 74.29 48.58 49.82

Ogu/Bolo 67.20 69.30 62.66 60.05 72.36 70.95

Okrika 64.70 57.30 55.06 53.35 79.86 74.93

Omuma 71.70 71.80 49.55 52.84 64.52 65.39

Opobo/Nkoro 62.20 63.00 59.03 48.64 52.44 90.35

Oyigbo 68.70 70.00 50.91 50.76 69.36 69.06


Port Harcourt 60.50 61.60 48.97 50.33 72.56 73.04

Tai 64.00 65.50 41.96 42.54 70.28 46.94

Grand Mean Score 59.80 60.50 49.86 49.15 67.19 69.03

Source: MLA assessment, 2013

Table 3: Analysis of Secondary School Performances by LGAs in English, Mathematics and

General Science test by Gender

LGAs English Mathematics General science

Male Female Male Female Male Female

Abua/ODUA 55.27 59.38 37.88 46.30 70.37 78.28

Ahoada East 37.18 41.41 57.79 46.12 68.08 66.63

Ahoada West 55.22 57.34 61.87 58.84 44.46 45.87

Andoni 31.77 33.06 48.63 49.56 47.07 46.42

Akuku Toru 41.76 41.69 54.65 52.87 48.35 45.77

Asari Toru 57.59 58.09 42.25 43.72 65.59 65.81

Bonny 52.45 54.73 64.48 63.56 32.88 32.88

Degema 37.34 38.91 37.81 24.36 67.20 60.89

Eleme 51.09 51.92 48.38 48.60 72.00 69.94

Emohua 50.51 54.55 47.99 46.98 68.01 59.88

Etche 51.02 45.11 44.86 41.78 63.00 67.24

Gokana 43.85 53.82 33.55 50.17 45.89 48.98

Ikwere 49.50 43.22 53.42 45.44 37.25 35.04

Khana 36.75 36.82 43.70 41.96 51.69 53.69

Obio/Akpor 53.96 54.50 33.81 39.99 75.61 69.94

Onelga 52.64 52.02 50.02 45.70 65.33 69.29

Ogu/Bolo 54.00 63.35 53.71 59.10 68.13 73.50


Okrika 53.82 55.28 57.15 53.35 77.33 70.74

Omuma 46.40 48.13 40.92 31.43 41.70 35.50

Opobo/Nkoro 39.23 40.26 38.40 37.40 44.97 46.21

Oyigbo 60.48 58.14 33.65 35.97 70.39 63.10

Port Harcourt 72.41 71.46 38.76 38.11 72.46 71.03

Tai 47.79 48.51 41.75 46.12 57.98 59.58

Grand Mean Score 49.22 50.51 46.32 45.54 58.94 58.10


Primary School

From the performance of the pupils across the Local Government Areas in the three learning

domains: Literacy, Numeracy and Life Skills, we observed that in:

Literacy

Figures 1 and 2 below show that, Female pupils scored an average of 60.53 marks or 50.3%

against 59.79 marks or 49.7% scored by males. Apparently from the charts, females

performed slightly better than their male counterpart in Literacy domain test across the LGAs.

From table 2 we can claim that, although there is a difference between the two group means

and substantial difference in performance in some LGAs, the difference is not statistically

significant. This implies that the difference may be caused by chance since the t- test value of

0.8 at 95% confidence limit is lesser than t-critical value of 1.68. So, the null hypothesis which

states that there is no significant difference in the academic performance of female and male

in the 2013 MLA assessment was accepted.


Figure 1: Mean scores of pupils by sex and LGA in the Literacy domain

0

10

20

30

40

50

60

70

80

Literacy

Male

Female



Figure 2: Group Mean scores of pupils by sex in the Literacy domain


Table 2: Mean rating, standard deviation and t-analysis of Literacy mean score

Literacy Gender N Mean Std df t-cal t-crit Ho

Female 23 60.53 9.65 44 0.7958 1.68 Accept

Male 23 59.79 9.7


Numeracy

In figures 3 and 4, we observed that female scored an average of 49.2 marks or 49.6% against

the 49.9 marks or 50.4% scored by the males in Numeracy domain test. As expected, males

performed marginally better than their Female counterpart in Numeracy domain test across

the LGAs. From table 3 we can claim that, although there is a difference between the two

group means and substantial difference in performance in some LGAs, the difference is not

statistically significant. This implies that the difference may be caused by chance since the t-

test value of 0.6343 at 95% confidence limit is lesser than t-critical value of 1.68. So, the null

hypothesis which states that there is no significant difference in the academic performance of

female and male in the 2013 MLA assessment was accepted.


Figure 3: Mean scores of pupils by sex and LGA in the Numeracy domain

0

10

20

30

40

50

60

70

80

Numeracy

Male

Female



Figure 4: Group Mean scores of pupils by sex in the Numeracy domain


Table 3: Mean rating, standard deviation and t-analysis of numeracy mean score


Female 23 49.14 14.001 44 0.6343 1.68 Accept

Male 23 49.90 11.946


Life Skill

In the Life skill domain, figures 5 and 6 show that averagely, female scored 69.02706 marks or

50.7% against 67.18843 marks or 49.3% scored by the males, thus females performed

marginally better than their male’s counterpart in Life skill domain test across the LGAs. As

observed from Figure 5; females performed far better than their male counterpart in Adoni

and Opobo/Nkoro LGAs.From table 3 we can claim that, although there is a difference

between the two group means and substantial difference in performance in some LGAs, the

difference is not statistically significant, thus implying that the difference may be caused by

chance since the t- test value of 0.51 at 95% confidence limit is lesser than t-critical value of

1.68. So, the null hypothesis which states that there is no significant difference in the

academic performance of female and male in the 2013 MLA assessment was accepted.


Figure 5: Mean scores of pupils by sex and LGA in the Life Skill domain

0102030405060708090

100

Life Skill

Male

Female



Figure 6: Group Mean scores of pupils by sex in the life skill domain


Table 4: Mean rating, standard deviation and t-analysis of Life skill mean score


Female 23 69.03 14.001 44 0.6343 1.68 Accept

Male 23 67.19 11.946


Secondary School

The MLA tests for secondary schools were administered in 3 learning domains and their sub-

components. These domains are: English Language, Mathematics and General science. From

the performance of students from schools across the Local Government Areas in the three

learning domains, we observed as follows:

English Language

Figures 7 and 8 below show that, Female students scored an average of 50.51 marks or

50.65% against 49.22 marks or 49.36 scored by males. Apparently, the females performed

slightly better than their male counterpart in this domain test. A t- test value of 0.638991 at

95% confidence limit is lower than the t-critical value of 1.6, thus we can conclude that

although there is a difference between the two group means, the difference is not statistically

significant; this difference can be attributed to chance. Hence the null hypothesis that there is

no significant difference in the academic performance of female and male in the 2013 MLA

assessment English Languageis accepted.


Figure 7: Mean scores of students by sex and LGA in the English Language domain

0

10

20

30

40

50

60

70

80

English Language

Male

Female



Figure 8: Group Mean scores of students by sex in the Literacy domain


Table 5: Mean rating, standard deviation and t-analysis of numeracy mean score

English

Language Gender N Mean Std df t-cal t-crit Ho

Female 23 50.51 9.16

44 0.63899 1.68 Accept

Male 23 49.22

9.33


Mathematics

The performances of students across the Local Government Areas in the Mathematics

domains are shown in Figures 9 and 10 below. It can be observed that Female students scored

an average of 45.55 marks or 49.6% as against 46.3 marks or 50.4 % by male students,

showing females performed slightly lower than their male’s counterpart in this domain test. A

t- test value of 0.83 at 95% confidence limit is lower than the t-critical value of 1.68. We can

conclude that although there is a difference between the two group means, the difference is

not statistically significant; and can be attributed to chance. Therefore, we accept the null

hypothesis that there is no significant difference in the academic performance of female and

male in the 2013 MLA Mathematics assessment. However the average performance in

mathematics as compared to other learning domains average at the secondary school level is

low.


Figure 9: Mean scores of students by sex and LGA in the Mathematics domain

0

10

20

30

40

50

60

70

Mathematics

Male

Female



Figure 10: Group Mean scores of studentss by sex in the Mathematics domain


Table 6: Mean rating, standard deviation and t-analysis of Mathematics mean

score

Mathematics Gender N Mean Std df t-cal t-crit Ho

Female 23 45.54

8.98

44 0.7711

1.68 Accept

Male 23 46.32

9.15


General Science

The performance of students across the Local Government Areas in General Science domains

is illustrated in Figures 11 and 12 below; Female students scored an average of 58.01 marks or

49.6 % against males’ 58.94424 marks or 50.4 %. Apparently the females performed slightly

lower than their male counterpart in this domain test. A t- test value of 0.83 at 95%

confidence limit is lower than the t-critical value of 1.68. We can conclude that although there

is a difference between the two group means, the difference is not statistically significant; and

can be attributed to chance. Therefore we accept the null hypothesis that there is no

significant difference in the academic performance of female and male in the 2013 MLA

assessment in General Science as a learning domain.


Figure 11: Mean scores of students by sex and LGA in the General Science domain

0

10

20

30

40

50

60

70

80

Ab

ua/

OD

UA

Ah

oad

a E

ast

Ah

oad

a W

est

An

do

ni

Aku

ku T

oru

Asa

ri T

oru

Bo

nn

y

De

gem

a

Ele

me

Em

oh

ua

Etc

he

Go

kan

a

Ikw

ere

Kh

ana

Ob

io/A

kpo

r

On

elga

Ogu

/Bo

lo

Okr

ika

Om

um

a

Op

ob

o/N

koro

Oyi

gbo

Po

rt H

arc

ou

rt

Tai

General Science

Male

Female

S

ource: MLA assessment, 2013


Figure 12: Group Mean scores of students by sex in the General Science domain

57.6

57.8

58

58.2

58.4

58.6

58.8

59

Male

Female

General Science


Table 7: Mean rating, standard deviation and t-analysis of General Science mean

score

General

Science Gender N Mean Std df t-cal t-crit Ho

Female 23 58.10 13.47

44 0.8317 1.68 Accept

Male 23 58.94

13.45



Gender Analysis using Criterion-Referenced Assessment

Criterion-referenced assessment is an assessment where an individual’s performance is

assessed based on a specific learning objective or performance standard and not compared to

the performance of other students or test takers as in norm-referenced assessment. It tends

to evaluate how well students are performing on specific goals or standards rather than how

their performance compares to a norm group of test takers. In criterion-referenced

assessment, each person is their own unique individual and is only compared to them. It

involves teaching students based on their needs with respect to a set standard/objective; and

assessing them based on their knowledge of such target standards. Thus, measuring against

such fixed goals can be used to examine the success of an educational reform program which

seeks to raise the achievement of all students unto new and improved standards. Hence,

instead of comparing them to their peers of same age or class; they are simply compared to

their prior performance.

For this study, the Minimum Mastery Level (MML) and Desired Mastery Level (DML) will be

used as a performance standard; the MML and DML were derived using statistical methods.

The MML and DML in each learning domain are specified as the sum (in the case of DML) or

difference (in the case of MML) of the mean score and thrice the standard deviation divided

by the square root of the number of LGAs. This corresponds to the upper control limit of the

control charts in each learning domain. Therefore, scoring above the upper limit signifies a

mastery of the subject whereas scoring below the lower limit signals a failure in learning but

though within the control limits but indicating a possibility to attain the minimum mastery

level. We will assess the performances of boys and girls against a set performance standard

MML and DML.

Table 7: Mean rating, MML, DML, and State Mean Score

Pupils Students

S/N Learning

Domain

Boys

Mean

Score

Girls

Mean

Score

MML DML State

Mean

Score

Learning

Domain

Boys

Mean

Score

Girls

Mean

Score

MML DML State

Mean

Score

1 Literacy 59.78 60.53 57.2 64.9 57.7 English 49.22 50.51 43.7 55.7 49.7

2 Numeracy 49.90 49.14 44.9 54.4 49.6 Mathematics 46.32 45.54 40.0 50.0 45.2

3 Life Skill 69.03 67.17 66.9 74.8 70.9 General

Science

58.10 58.94 50.5 66.3 58.4


Figure 13: Mean Scores of Pupils Disaggregated by Sex and Locational Residence Relative to Mastery Levels: Literacy domain

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

Axi

s Ti

tle

Literacy

Male

Female

STATE MEAN SCORE

MML

DML


Fig.13, Shows that in the Literacy learning domain, about 65 percent of the Boys from 15 LGAs

achieved the Desired Mastery Level, while 60 percent of Girls from 14 L.G.As achieved the

Desired Mastery Level. Although, 5 and 8 LGAs have their boys and Girls fall respectively

within the control limits; this implies that they have achieved the Minimum Mastery Level in

literacy learning domain. But, 2 LGAs each have their boys and Girls achieved below the lower

control limit1.

1 See Appendix for Table 14: LGAs Mean rating, MML, DML, and State Mean Score in Literacy learning

domain


Figure 12: Mean Scores of Pupils Disaggregated by Sex and Locational Residence Relative to Mastery Levels: Numeracy domain

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0NUMERACY

Male

Female


Fig.13, Shows that in 35 percent of the LGAs, Boys achieved the Desired Mastery Level in

Numeracy domain while Girls from only 22 percent of the LGA performed at the Desired

Mastery Level.

The Minimum Mastery Levels in numeracy were achieved by Boys from 9 and Girls from 12 LGAs. And

in 26 percent of the LGAs, both boys and Girls performed below the Minimum Mastery Level2.

2 See Appendix for Table 15: LGAs Mean rating, MML, DML, and State Mean Score in Numeracy learning domain


Figure 12: Mean Scores of pupils Disaggregated by Sex and Locational Residence Relative to Mastery Levels: Life Skill domain

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Life Skill

Male

Female

STATE MEAN SCORE

MML

DML


Fig.13, Shows that performance below the Minimum Mastery Level was recorded for both Boys and Girls from 22 percent or 5 LGAs.

Girls from 6 LGAs achieved the Desired Mastery Level in Life Skills whereas performance at the Desired Mastery Level was recorded for Boys

from only 4 LGAs. A greater number of Boys from 14 LGAs achieved the minimum mastery Level while Girls from 11 LGAs achieved the

Minimum Mastery Level3.

3 See Appendix for Table 15: LGAs Mean rating, MML, DML, and State Mean Score in Life Skills learning domain


Figure 12: Mean Scores of Students Disaggregated by Sex and Locational Residence Relative to Mastery Levels: English Language domain

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0 ENGLISH

Male

Female


Fig.13, Shows that the Desired Mastery Level was achieved by Boys from only 3 LGAs in

contrast to Girls from 6 LGAs achieving the Desired Mastery Level in English Language.

Boys from 14 LGAs achieved the Minimum Mastery Level compared to Girls from 10 LGAs

achieving the MML in English Language. Girls from 7 LGAs performed poorly below the MML

while boys from 6 LGAs performed similarly4.

4 See Appendix for Table 16: LGAs Mean rating, MML, DML, and State Mean Score in English Language learning domain


Figure 12: Mean Scores of Students Disaggregated by Sex and Locational Residence Relative to Mastery Levels: Mathematics domain

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0MATHEMATICS

Male

Female


Fig.13, Shows that Boys from 7 LGAs achieved the desired mastery level in Mathematics while

girls form 5 LGAs performed at the Desired Mastery Level. Girls from 12 LGAs achieved the

Minimum Mastery Levels compared to Boys from 9 LGAs achieving the MML. Again, Boys

from 7 LGAs achieved below the MML whereas Girls from 6 LGA similarly performed so

poorly-below the MML5.

5 See Appendix for Table 17: LGAs Mean rating, MML, DML, and State Mean Score in Mathematics learning domain


Figure 12: Mean Scores of Students Disaggregated by Sex and Locational Residence Relative to Mastery Levels: General Science domain

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

GENERAL SCIENCE

Male

Female

STATE MEAN SCORE

MML

DML


Fig.13, Shows that 44% or 9 LGAs have their Boys and Girls achieved the Desire Mastery Level.

5 LGAs have their boys fall within the control limits and 6 LGAs have their girls fall within the

control limits, this implies that they have achieved the minimum mastery level in literacy

learning domain corresponding to 22% and 26% respectively. But, 8 LGAs have their boys

achieved below the lower control limit, and 8 LGAs have their girls achieved below the lower

control limit corresponding to 34% and 34% respectively6.

2.1.1. Part 3: Gender Analysis of Other Indicators of Learning Performance

In addition to the learning outcome from the administered test questions, other indication of

performance can be inferred from the School Census Report (administrative data) when

disaggregated along gender lines. A peek into the data on repeaters and dropout pattern or

trend can reveal more information about gender difference in learning performance.

REPEATERS

In Figure 13; we observed that there are more boys than girls who are repeating a class (or

more) of schooling. The repetition of a school class can be considered as a form of support for

low performance as it seeks to adapt the curriculum to pupil/student performance. The

requirement for a particular student to repeat a class usually follows a formal assessment or

informal decision by the teachers when pupil/student has poor results in crucial subjects.

Statistics from the State school census report 2011-2012 shows that the number of repeaters

is higher for both males and females in the primary than in the secondary schools, figure 13

shows that the number of repeater gradually decline as students’ progress from one

education level to another or from a lower class (year) to a higher class (year).

6 See Appendix for Table 18: LGAs Mean rating, MML, DML, and State Mean Score in General Science learning domain


Figure 13: Public Repeaters by Gender and Grade

Source: State school census report 2011-2012

Dropout Rate

There are few noteworthy gender distinctions with respect to participation rates in primary

and secondary education. The differences emerge at the end of compulsory education.

Despite significant progress in increasing primary and secondary enrolment; completion rates

continue to be low. In Figure 14, it can be observed that more girls than boys are dropping

out, with the exception of primary 1. As observed from the figure more girls dropout from

primary 2, 4, 5 and 6. Similarly, in the same pattern occurred at the secondary school levels

except SS1 and 2. A 2013 study by Arbitrage consult on Out-Of-School children in Rivers state

reveals that poverty and teenage pregnancy are the most significant reasons responsible for

pupils and students dropping out of school; accounting for 91 percent of school dropout7.

Some interesting pilot programs to address the drop out problem should be introduced for

possible replication.

7 See Out-Of School Children in Rivers State by Arbitrage Consult Limited


Figure 14: Dropout rate by class and gender

0

100

200

300

400

500

600

700

PRY1 PRY 2 PRY 3 PRY 4PRY 5

PRY 6JSS 1

JSS 2JSS 3

SSS 1SSS 2

Drop out rate by Class and Gender

Boys

Gils

Source: State school census report 2011-2012


Teachers

The staff strength of the public schools in Rivers state as captured in the State School Census Report 2011-2012 stood at 7,573 teachers for primary school, 4,975 teachers for junior secondary and 2,968 teachers for senior secondary, giving a total of 15516 teachers. 8This Statistics also show that there more female teacher than male, with a total of 8540 accounting for 55% as against 6976 or 45% for males’. However, table 8 and Figure 15 showed that there are more male teachers in 8 LGAs at the primary school level, 15 out of 23 LGA have more male teachers at the Junior Secondary Level, and 18 out of 23 LGA have more male teachers at the Senior Secondary School levels. This disparity in the number of teachers employed with emphasis on their gender can significantly affect the performance of students. Basu and Chakroborty (1996) reported that student taught by male teacher achieve higher than those taught by female teachers.

Table 8: Distribution of Public School Teachers by LGAs and Gender

8 See Appendix, TABLE 12A and 12B: Staff Strength of Public Schools by LGAs and Gender

Primary School teachers

Junior secondary school teacher

Senior Secondary School teachers

LGEA M Male

Fem Female

ale

Total

Totl

Male

Male

Fem Female

ale

Total

Total

Male Fem Female

ale

Total

Total

ABUA/ODUAL 194 175 369 93 26 119 62 16 78

AHOADA EAST 100 246 346 126 105 231 64 15 79

AHOADA WEST 140 126 266 113 60 173 100 22 122

AKUKU-TORU 38 82 120 86 64 150 24 11 35

ANDONI 135 95 230 101 24 125 38 8 46

ASALGA 51 124 175 33 25 58 31 30 61

BONNY 33 106 139 14 13 27 39 32 71

DEGEMA 85 150 235 76 67 143 27 17 44

ELEME 57 149 206 58 135 193 67 44 111

EMOHUA 196 166 362 191 164 355 122 32 154

ETCHE 298 205 503 181 76 257 149 42 191

GOKANA 201 131 332 132 52 184 143 27 170

IKWERRE 102 358 460 159 177 336 105 25 130

KHANA 413 177 590 190 63 253 178 38 216

OBIO/AKPOR 50 644 694 139 682 821 239 301 540

OGU/BOLO 49 53 102 14 21 35 9 3 12

OKRIKA 52 191 243 65 115 180 42 17 59

OMUMA 75 119 194 45 14 59 24 5 29



ONELGA 180 255 435 228 209 437 170 78 248

OPOBO/NKORO 59 68 127 39 17 56 2 1 3

OYIGBO 38 247 285 39 65 104 38 32 70

PHALGA 80 856 936 121 475 596 155 253 408

TAI 128 80 208 62 21 83 76 15 91

Grand Total 2756 4805 7573 2305 2670 4975 1904 1064 2968


Figure 15: Distribution of Public School Teachers by LGAs and Gender

0

200

400

600

800

1000

1200

1400

1600

1800

Distribution of Public School Teachers by LGAs and Gender

Male

Female

51 Chapter three | Arbitrage Consult Limited

Chapter three

Factors Associated with Gender Differences

Rivers state has demonstrated commitment in promoting Gender equity, as demonstrated in

her educational policy. However, a number of social and institutional barriers remain, which

impair boys’ and girls’ performance in school, and combine to prevent girls from completing

primary and secondary school in equal numbers to boys or young women from reaching

university in equal numbers to young men. Girls continue to lag behind their male classmates

in terms of completion rates and in some cases; their overall performance in school.

Attendance rates for girl students are generally lower, which could translate into lower scores

on national examinations. We will examine the causes of this disparity, which persist despite

the strong policy framework in place, by estimating the factors associated with gender

differences using single-equation regression model (ANOVA model) and dummy variables to

point out differences, if they exist, between boys and girls performance in the learning

domain.

Table 9: Some Selected Factors that Influence Learning Performance by Gender

S/N Factors Categories Total Score of

Boys with

respect to a

factor

Total Score of

Girls with

respect to a

factor

1 REGION Urban=1

Rural=0

180.5

(0)

184.8

(1)

194.2

(0)

186.6

(1)

2 Home Learning

Environment

Going to library

or attending

extra-mural

lession=1

Others=0

182.7

(0)

182.1

(1)

188.5

(0)

193.2

(1)

3 Feeding Yes=1

No=0

177.5

(0)

188.4

(1)

191.1

(0)

189.1

(1)

4 Teacher Attitude Liking

teacher=1

Other=0

182.2

(0)

187.4

(1)

185.9

(0)

244.5

(1)


Table 9 above illustrates gender disparity in learning with respect to some selected factors;

the factors are regressed against total score of students, the essence is to show clearly the

disparity in boy and girls performance (total score) relative to these factors using dummy

variables. For example, from the table we can observe that urban boys and girls perform

relatively better than their rural counterpart, and girls perform better than boys with respect

to this factor in the respective urban and rural categories; implying that these factors impact

on the performance of boys and girls differently, and could be a reason for the disparity in

performance.

Social and Economic Factors which Influence Girls’ and Boys’ Performance and Behavior

In Rivers state, socio-economic factors affect pupil and students performance in schools.

Studies have shown that students with better parental background tend to perform better

than students from poor homes. Other factors such as ethnic origin and language intersect

with gender to influence educational performance and indeed, these factors become more

significant as students grow older.9 Obstacles to high academic performance include poverty,

family size and parents in unskilled or low skilled employment, while enhancements include

higher social class level, being a girl and having educated parents (Sammons, 1995). In table 9

above and Volume IV (Determinants of learning performance), we highlighted that

pupils\student parental background such as parental education can influence the

performance of pupils. Interestingly, membership of a minority ethnic group can be

advantageous or disadvantageous, depending on its specific cultural disposition towards

education. Nevertheless, other factors or combination of factors are also significant; such as

the influence of both gender and home learning environment (HLE) on the pupil performance,

where HLE involves frequency of reading to the child, visiting the library, teaching songs,

nursery rhymes, playing with letters and numbers, drawing/painting etc.

Gender Themes in Current Educational Practice

Gender equity can only be achieved through in-depth curriculum adjustment that gives

credence to Gender equality. The official curriculum concerns the subjects that are taught in

schools and their contexts. Rivers state adopted the National curriculum based on the concept

of basic education for all. Curriculum theorist Paechter (2000) points out that though official

curricula tend rarely to address gender equality, they tend to imply certain gender

assumptions; for example, that ‘power’ subjects (e.g. Numeracy, mathematics and science)

will attract males and others (e.g. languages, literature) females. This means that the content

of different subjects attracts boys and girls on the basis that’ ‘this is what proper girls or boys

do’. A number of recurrent themes or topics are to be found in the literature on gender and

education which deal primarily with educational practice (or what goes on in schools). These

are the curriculum (official and hidden). The Official curriculum is concern with school reading

materials, subject preference and choice, motivational and psychological factors of students,

school organization and management, teacher attitudes, assessment, teaching as a 9 See Determinants of Learning Performance


profession, co-education and single-sex settings, and the problem of boys. On the Hidden

curriculum, on the other hand, concerns everything that happens in the school that is not

‘official’, for example, social relations in the classroom or playground, friendships,

relationships between teachers and pupils, levels of bullying and harassment and so on.

Motivational and Psychological Issues

Self-esteem and confidence is a major determinant of gender parity in pupils and student

performance, although this issue is psychological, it has played a major role in determining

how pupils performed thus, studies of gender difference in student ‘self-concept’ have been

of much interest. However, research evidence is inconclusive with findings ranging from little

evidence of difference to males having far higher self-images. Student ‘motivation’ to do well

at school is also an important factor. For example, a study suggests that (some) boys’

underperformance is associated with their generally negative attitudes towards schools, in

particular their less positive relationships with teachers, lack of feeling of well-being while in

school, and their poor attitude towards schoolwork. In Table 9 and Volume IV of this study,

we established that pupils attitude toward their teachers could affect their performance, it

was stated that, “when a pupil likes his or her teacher, it enhances his/her performance by 2

percent and this is statistically significant at 5 percent”.

School Environment

Evidence has emerged that students’ achievement levels are much influenced by the school

environment and, in particular, the daily management and organisational procedures of

schools which are frequently reliant on gender as a management tool. Girls and boys may be

separated for classroom registers, classroom activities and team sports, for example. Dress

codes may be different for boys and girls (trousers for boys, skirts for girls) and also for

members of staff (Scott, 2007). Such practices are criticized because they have little

educational benefit save as deliberate ‘marker’ of gender difference. On the other hand,

investment of time in the development of institutional policies and associated staff

development (SEED, 2006) which address, for example, bullying and sexual harassment have

been shown to be effective in raising pupil and staff consciousness that such behaviour is

demeaning and unacceptable.

Teacher Attitudes

Teachers as basic tool in curriculum implementation remain a very crucial factor that influence students’ experience and achievement, and continuing educational development. These is no longer achievable since teachers are accorded with little or no respect in the society due to insufficient fund, lack of motivation incentives, delay in salary payment among others all these affects teachers activities, causing psychological and emotional trauma which in turn affect his output. Simpsom and Troost (1982) found out that teacher attitude is an important factor that determines achievement and enrolment of students. The argument is that teacher attitudes influence student attitudes (Aiken 1970, Larson 1983), and that student attitudes have a powerful influence on learning (Evans 1965, Khan and Weiss 1973). Indeed a


number of researchers have found a significant correlation between teacher attitude and student achievement (Begle 1979, Bishop and Nickson 1983, Schofield 1981). The influence exacted by the teachers on their students as a gender implication, since when teachers believe that they treat their students equally, they are more likely to chastise male students and pay them more attention, while at the same time creating greater dependency in their female students. Hence, a variety of countries studies or studies in other countries have shown that both male and female teachers tend to encourage passivity and conformity in their female pupils and students while at the same time valuing independence and individuality in their male students (Golombok & Fivush, 1994). They thus allow boys to be naughtier because they think it natural and, for the same reasons, expect girls to take up ‘domestic’ related activities such as caring for others or cleaning-up in the classroom. Girls are generally perceived to be more cooperative and malleable, and boys more confident and able.

55 Chapter Four | Arbitrage Consult Limited

Chapter Four

Strategies for Addressing Gender Differences

In other to achieve the MDG’s goals of attaining gender parity Index GPI of between 0.97 and

1.03, Rivers state in recent times has put in place, policies aimed at reducing Gender

inequality and enhancing learning performance in public schools in the state. In spite of these

policies, gender equity has remained a daunting challenge, as it is rare to find public schools

with written policies on gender equality. In this chapter, we highlight some strategic

interventions aimed at addressing underachievement. Some of these strategies include:

Study support

Mentoring

Building confidence

Self-esteem

Developing systems of target-setting for individual pupils

And their implications for gender differences because more boys than girls are perceived to

be under-achieving.

Strategies in Relation To Learning, Teaching and Assessment

Teaching and Learning Processes

The reason why boys and girls learn in different ways may be due to their physiological

pattern; which may explain the variations in males and females performance in various

learning domains. Understanding some broad patterns that are evident in the way in which

girls and boys prepare themselves for learning and engage in learning in the classroom is

fundamental to addressing gender issues. (Noble and Bradford 2000) state that “a range of

approaches can be used to confront issues such as boys’ work habits, their need to be fully

engaged in the classroom and their reported limited concentration”. Such approaches include:

using activity-based and experiential tasks in learning; the understanding and development of

specific skills such as reading and literacy and revision and study skills; focused, clear and

time-bound; less written and more oral work, also using competitive dimension such as:

quizzes and games, ICT and audio visual support and a variety of formats, e.g. diagrams and

images to supplement text. It is essential to use cooperative/interactive methods of learning

to support girls in their learning. In addition, understanding female pupils and students

response mechanism is paramount, due to the fact that girls respond better to feedback that

is exciting but gives precise guidance for improvement as well as praise.


Assessment Practices

To effectively reduce gender inequality in learning performance in Rivers state, the

government may need to implement a state performance assessment monitoring systems

disaggregated by gender and the interaction between gender as well as the assessment

process itself.

Interaction Patterns in the Classroom

To effectively address gender difference in learning performance, it is essential to study and

understand the interaction pattern of gender and classroom. The key issues that will emerge

include: how the relative Silence of boys and girls affects classroom dynamics; differences in

the nature and quality of interaction, with teachers tending to have more negative

interactions with boys; and teachers’ reinforcement of gender stereotypes, both through the

formal curriculum and informal interactions.

Pupils and Students Attitude and Motivation

In the classroom pupils\students have gender-differentials patterns of interaction and

motivation styles and how this pattern affects the students and pupils has to be recognised. It

is important to note that this gender-differential pattern of interaction has implications for

school behavior and overall policies; (Galloway, 1998) states that “girls tend to have higher

levels of task orientation (where the focus is on the achievement itself), particularly in English,

than boys. While boys have higher levels of ego orientation (the concern is their standing with

other people) in both English and mathematics. Identifying these gender-differential patterns

will enable policy makers to implement policy that will reduce gender inequality in learning

performance in public schools.

Classroom Organization

Two complementary classroom organizational strategies have been developed to manage

gender inequality in various learning domains: the use of mixed gender groupings and single

gender groupings/classes.

Mixed-Gender Groups

Seating arrangement in the classroom is a critical factor in addressing gender inequality in

learning performance; some classroom seating arrangement prevents boys and girls from

interacting; particularly detaching the boys from the girls. (Raphael Reed, 1999) reveals that

the function of girls is to exercise their ‘civilizing’ influence in ‘supporting’ boys’. Also, (Epstein

1998) states that “it is important to use girls to police, teach, control and civilise boys”. The

expectation that at least some girls should play this role raises questions about their own

opportunities. The use of girls as a tactic in the control of boys is implicit in a range of

strategies such as seating policies, mixed gender pairs and groups.

Single Gender Groups and Classes

To tackle boy’s low performance in public schools, the use of single gender and classes’

strategy has been suggested. According to Woodhead, (1996), “during adolescence boys are


distracted by the presence of girls and they can engage in behaviours that detract them, from

their learning”. However, in some instances, this strategy has been adopted to support the

learning of both boys and girls. The importance of adopting single gender teaching includes:

improving girls’ opportunities, addressing boys’ low performance and behavior problems. The

impact of this strategy depends to a certain extent on whether the focus is on pupils in the

‘top’ or ‘bottom’ sets.

Role Models

Statistics from the Monitoring Learning Achievement 2013 survey reveals that there are more

female than are male teachers in public schools in Rivers state. Interestingly, women have

always been in the majority in primary schools. This has raised the issue of a lack of male role

models for boys at various levels in the education system. Efforts have to be made to attract

more men into teaching, especially into primary Schools.

Mentoring

Mentoring is an effective approach in managing boys’ low performance in primary and

secondary schools. This is because at that stage pupils and student are easily influenced by

what they see, feel and sense. Mentoring comes in different forms, such as the practice of

peer counselling (Ryder, 1998), using reading partners and groups (Noble, 1998) and subject-

specific support (Penny, 1998). Studies have shown that mentoring can be adopted for a

range of reasons, such as: focusing on specific pupils, frequently low performance by boys, to

tackle motivation and confidence and to support pupils on specific exams and expected

results. Applying mentoring approach can result in a number of positive outcomes for both

boys and girls. Nonetheless, there were limitations, most especially relating to structure, time,

lack of sufficient numbers of trained mentors and high mobility rate of teachers from one job

to another.

School Culture and Participation in Development

School culture is an important factor in promoting gender equity in learning performance.

Government and policy makers must be active in promoting the development of whole school

strategies to establish and enhance a positive culture. In the Monitoring Learning Survey of

2013, most pupils complain of bullying and harsh academic environment. Approaches to

promote positive behaviour and to create greater pupil participation in the School community

life style and decision-making processes of school should be encouraged. Pupils and their

parents need to be involved in both the decision making process and in discussing policy

formulation for the school. Parents should also be seen as having an important role to play

both in supporting pupil learning and in contributing to public activities to raise the awareness

of gender equity.

58 Chapter Five | Arbitrage Consult Limited

Chapter Five

Conclusion and Recommendations

Developing gender policies and practices requires that gender issues are considered in

all aspects of school development, as well as being a specific focus pursued through

discrete strategies. Such eclectic or all-embracing approaches might be mirrored in

local Government and the state education initiatives. The invisibility of gender in many

policy documents has been surprising, given the highly gendered patterns of pupil

experience. Our findings showed that:

There are gender gaps in Rivers state public schools; these gaps exist in enrollments,

learning performance, repeaters rate, dropout rate and teaching manpower.

The Rivers state government does not discriminate against females in the field of

education. However, factors that can be directly responsible for gender disparity in

public schools include: socio-economic influences, gender themes in current

educational practices, motivational and psychological issues, school environment, and

teacher attitude.

From current enrollment statistics, Gender Parity Index (GPI) is 1.07 in the 2011/2012

academic against GPI of 0.97 in 2005. Since a GPI of 1 indicates parity between the

sexes; a GPI that varies between 0 and 1 typically means a disparity in favour of males;

whereas a GPI greater than 1 indicates a disparity in favour of females. This implies

that Rivers state has achieved the MDG’s goals of attaining gender parity Index GPI of

between 0.97 and 1.03

More boys than girls are perceived to be underperforming; this is evidenced by the

fact that there are more boys than girls who are repeating a class (or more) of

schooling. Also results from the 2013 Monitoring Learning Achievement (MLA) showed

that except in numeracy and mathematics; generally, girls performed better than boys

across the various Local Government Areas.

Dropout rate is higher for girls in both primary and secondary schools


Recommendations:

Government should organise workshops for capacity building and policy advocacy on

gender issues, which will create the needed awareness in this regards. Also due to the

high dropout rate for female; it is important for the state government to setup,

implement, monitor an intervention programs to address the females drop out

problem. For example, a program to eradicate child labour and promote Gender and

Family values. This catch-up program should be linked to a special curriculum that

facilitates those girls and boys to finish their primary and secondary school.

Use of gender-sensitive textbooks and curriculum for girls will help bridge the gender-

gap.

River state government schools implement a state performance assessment

monitoring system that can monitor performance by gender and the interaction

between gender and the assessment process itself.

60 Reference | Arbitrage Consult Limited

Reference

Aiken, L.R. (1970) Review of Educational Research, 40, 551-596

Arnold, R (1997) Raising Levels of Achievement in Boys. Slough: NFER EMIE.

Basu,J and Ghakroboty,U.(1996). Effect of sex role, identity on academic achievement of late adolescents in Indian. Journal of social psychology,41,586-598.

Begle, E.G. (1979) Critical Variables in Mathematics Education, MAA-NCTM, Washington DC.

Bishop, A.J. and Nickson, M. ( 1983) A Review of Research in Mathematical Education, Part B, NFER-Nelson, Windsor.

Frater, G (1998) ‘Boys and Literacy’. In K Bleach (1998) (ed.) Raising boys’ achievement in

schools. Stoke-on-Trent: Trentham Books.

Galloway, D, Rodger, C, Armstrong, D and Leo, E (1998) Motivating the Difficult to Teach.

London: Longman.

Epstein, D (1998) Real boys don’t work: ‘underachievement’, masculinity and the harassment

of

‘sissies’. In D Epstein, J Ellwood, V Hey and J Maw (eds.) Failing boys? Issues in gender

and achievement. Buckingham: Open University Press.

Evans, K.M. (1965) Attitudes and Interests in Education, RKP, London.

Golombok, S. & Fivush, R., 1994. Gender development. Cambridge: Cambridge University

Press.

Khan, S.B. and Weiss, J. (1973) in Travers, R.M.W. (ed.) Second Handbook of Research on Teaching, Rand McNally, Chicago, 759-804.

King, M.C. (1988). Localism and Nation Building. Ibadan: Spectrum Books Leavitt, R.R (1972).

“Women in Other Cultures” in Vivian G. and Barbara K M (eds). Women inSexist Society. New

York: Basic Books p. 413.

Larson, C.N. (1983) Arithmetic Teacher, 8-9.

Noble, C (1998) Helping boys to do better in their primary school. In K Bleach (1998a) (ed.)


Raising boys’ achievement in schools. Stoke-on-Trent: Trentham Books

Noble, C and Bradford, W. (2000) Getting it Right for Boys ….and Girls. London: Routledge

Osakwe, G. (1999). “The Role of Women in Nation Building” being a paper presented at a

Seminar Organized by Girls’ Power Initiative (GPI) South-West Zone in Association with the

Public Administration Students Association of Nigeria Uniben Chapter. Benin City.

Paechter, C., 2000. Changing school subjects: Power, gender and the curriculum. Buckingham:

Open University Press.

Penny, V (1998) Raising Boys’ Achievement in English. In K Bleach (1998a) (ed.) Raising boys’

achievement in schools. Stoke-on-Trent: Trentham Books.

Paul, R (2001). “Every Girl Counts: Development, Justice and Gender. Girl Child Report.

Monrovia (USA)

Raphael Reed, L (1999) Troubling boys and disturbing discourses on masculinity and schooling:

a feminist exploration of current debates and interventions concerning boys in school.

Gender and Education 11 (1), 93-110

Rivers State School Census Report 2011-2012.

Ryder, J (1998) Peer counselling at the Boswells School, Chelmsford. In K Bleach (1998a) (ed.)

Raising boys’ achievement in schools. Stoke-on-Trent: Trentham Books

Scott, S., 2007. Uniform and dress codes. In K. Myers, H. Taylor, S. Adler & D. Leonard, eds.

Genderwatch: …still watching. Stoke-On-Trent: Trentham, pp. 82-84

Sammons, P., 1995. Gender, ethnic and socio-economic differences in attainment and

progress: A longitudinal analysis of student achievement over 9 years. British Educational

Research

Journal. 21(4), pp. 465-485.

SEED (Scottish Executive Education Department), 2006. Insight 31: Review of strategies to

address gender inequalities in Scottish schools. [pdf] Edinburg: Scottish Executive Education

Department. Available at: http://www.scotland.gov.uk/Resource/Doc/113682/0027627.pdf

[Accessed 26 October 2009

Toumbara-Diawara, A (2002). ICT possibilities as tools for collecting and disseminating

Information on Women Echo, 10-11, 2-6.

UN (2009), World Survey on the Role of Women in Development, United Nations, New York


The United Nations (1948): Universal Declaration of Human Rights. Article 26

UNESCO (2002). The Challenge of Achieving Gender Parity in Basic Education, UNESCO – Paris.

UNICEF (2006). Girls Education in Nigeria.

UNESCO (2004). Why Are Girls Held Back? Gender and Education for all The Leap to Equality.

Global Monitoring Report, New York.

United Nations (1989). Convention on the Right of the Child.

Van de Gaer, E., Pustjens, H., Van Damme, J. & De Munter, A., 2006. Tracking and the effects

of

school-related attitudes on the language achievement of boys and girls. British Journal of

Sociology of Education, 27(3), pp. 293-309.

Women in Nigeria (WIN) (1992). Women Education: proceedings of the Third Annual Women

in Nigeria Conference, Zaira pp 5-14

Woodhead, C (1996) Boys who learn to be losers. The Times, 6th March

World Bank (2002). Integrating Gender into the World Bank. Work A Strategy for Action

Washihgton D.C.

63 Appendix | Arbitrage Consult Limited

Appendix

Table 9: TABLE SUMMARY FOR PRIMARY SCHOOLS L.G.A SAMPLE

D LITERACY

NUMERACY

LIFE SKILLS

TOTAL AVERAGE

TOTAL AVERAGE

TOTAL AVERAGE

1 ABUA UDUA 685 45,959 67.09343 39,368 57.47153 51,487 75.1635

2 AHOADA EAST 538 29,976 55.7175 21,070 39.164 35,708 66.372

3 AHOADA WEST 712 33,718 47.3567 33,683 47.3076 39,132 54.9607

4 AKUKU-TORU 256 15,561 60.7852 11,938 46.6328 18,071 70.5898

5 ANDONI 719 35,038 48.7316 34,540 48.0389 56,275 78.2684

6 ASA 319 20,391 63.9216 12,248 38.395 22,426 70.3009

7 BONNY 317 19,922 62.8454 21,332 67.2934 22,253 70.1987

8 DEGEMA 284 16,724 20.2262 10,054 35.4014 20,454 72.0211

9 ELEME 300 16,837 56.1223 17,340 57.8 21,387 71.29

10 EMOHUA 713 38,143 53.4965 32,960 46.2272 49,392 69.2735

11 ETCHE 593 14,827 25 10,021 17 16,504 28

12 GOKANA 617 36,182 58.6418 30,284 49.0827 33,813 54.8023

13 IKWERE 653 41,410 63.415 37,271 57.0766 49,913 76.4364

14 KHANA 1168 67,092 57.4418 56,538 48.4058 81,230 69.5462

15 OBIO/AKPOR 709 44,770 63.1453 31,077 43.8322 58,532 82.5557

16 OGU/BOLO 114 7,785 68.2895 6,989 61.307 8,166 71.6316

17 OKRIKA 509 31,068 61.0373 27,637 54.2967 39,447 77.499

18 OMUMA 208 14,928 71.7692 10,744 51.6539 13,536 65.0769

19 ONE 688 41,684 60.5872 33,835 49.1788 50,671 73.6497

20 OPOBO NKORO 209 13,131 62.8278 11,692 55.9426 14,817 70.8947

21 OYIGBO 341 24,228 71.0499 17,224 50.5103 24,778 72.6628

22 PORT-HARCOURT 763 46,692 61.195 37,509 49.16 55,033 72.127

23 TAI 447 28,727 63.3848 18,792 42.179 32,646 73.1876

STATE TOTAL 11862 684793 564146 815671

STATE MEAN SCORE

57.72998 47.559096 68.76336


Table 10: TABLE SUMMARY FOR SECONDARY SCHOOLS L.G.A ENGLIS

H MATHEMATIC

S GENERA

L SCIENCE

SAMPLED

TOTAL AVERAGE

TOTAL AVERAGE

TOTAL AVERAGE

1 ABUA UDUA 8,884 55.8742 6,361 40.006 11,469 72.132 159

2 AHOADA EAST 7,450 38.8021 7,977 41.547 12,569 65.464 192

3 AHOADA WEST 14,170 66.8396 8,268 39 11,770 55.519 212

4 AKUKU-TORU 3,969 44.5955 5,446 61.191 4,389 49.315 89

5 ANDONI 4,868 29.503 8,107 49.133 7,708 46.715 165

6 ASA 7,578 56.9774 5,719 43 8,738 65.699 133

7 BONNY 4,935 53.6413 5,880 64 2,809 30.533 92

8 DEGEMA 4,326 38.2832 3,719 32.856 7,383 65.336 113

9 ELEME 3,658 51.5211 3,443 48.493 5,138 72.366 71

10 EMOHUA 16,307 52.266 14,841 47.567 20,200 64.744 312

11 ETCHE 9,085 47.8158 8,206 43.19 12,407 65.3 190

12 GOKANA 8,152 49.1084 7,065 42.56 7,856 47.325 166

13 IKWERE 5,513 45.4594 5,868 48.9 4,320 36 120

14 KHANA 11,255 36.7811 13,110 42.843 16,014 52.333 306

15 OBIO/AKPOR 15,349 54.0458 10,492 36.944 20,657 72.736 284

16 OGU/BOLO 2,563 58.25 2,471 56.159 3,105 70.562 44

17 OKRIKA 4,927 55.3596 5,287 59.405 6,584 73.978 89

18 OMUMA 3,625 47.0779 2,866 37.221 3,025 39.286 77

19 ONE 13,918 52.3233 12,723 47.831 17,713 66.59 266

20 OPOBO NKORO 2,707 39.8088 2,573 37.838 3,105 45.662 68

21 OYIGBO 10,524 50.596 8,511 40.918 12,629 60.716 208

22 PORT-HARCOURT

14,135 72.8608 6,958 35.866 12,999 67.005 194

23 TAI 6,953 46.9797 6,436 43.487 8,617 58.223 148

STATE TOTAL 184,851 162,327 221,204 3,698

STATE MEAN SCORE

54.836 48.154 65.62


Table 11: MEAN PERFORMANCE BY GENDER AND LGAs

Abua/ODUA

Ahoada East

Ahoada West

Andoni Akuku Toru

Asari Toru Bonny Degema

Literacy Male 67.396552

56.811245

45.702703

54.61686391

66.89655172

62.5 61.166667

64.75

Female 67.535714

58.385542

50.581897

56.005068 70.08181818

68.49685535

62.952756

64.634615

Numeracy

Male 58.449857

40.303502

47.841996

47.651163 46.2265625

39.68243243

64.84127

40.176471

Female 57.719403

41.52 45.99569

48.637462 49.59166667

40.09433962

68.669291

37.923077

Life skill Male 79.722543

72.016461

55.357588

69.502618 70.64341085

68.51633987

70.349206

71.441176

Female 80.952239

73.961864

53.913793

90.349544 72.67213115

71.94578313

70.850394

73.384615

Eleme Emohua Etche Gokana Ikwere Khana Obio/Akpor

Onelga Ogu/Bolo

Okrika

56.516556

52.948849

24.93664 55.419075

65.911475

56.84051 61.782738 61.90113 67.236364

64.732

56.534091

53.937695

25.11587 53.660517

61.580925

59.46748 64.894595 59.912121

69.271186

57.25

57.119205

46.227621

16.505198

46.67052 60.570492

48.433812

44.791667 73.256338

62.654545

55.064

57.090909

46.23676 17.278591

40.594096

54.170029

48.670732

43.433604 74.292169

60.050847

53.35

71.51049 68.664962

27.452465

61.656069

74.820261

69.942584

83.770833 48.58427 72.363636

79.856

71.544872

69.691589

28.233097

59.02214 78.540698

69.73374 82.344173 49.816265

70.949153

74.934615

Omuma Opobo/Nkoro Oyigbo Port Harcourt

Tai

71.706667 62.22549 68.715976 60.481268 63.955556

71.804511 63.037736 69.97093 61.639423 65.479821

49.546667 59.029412 50.911243 48.971182 41.955157

52.842105 48.637462 50.755814 50.329327 42.541667

64.52 52.443396 69.35503 72.56196 70.282511

65.390977 90.349544 69.05814 73.038462 46.944444


Table 12A: Academic Staff Strength of Public Schools by LGAs and Gender

Primary School teachers

Junior secondary school teacher

Senior Secondary School teachers

LGEA Male Female Total Male Female Total Male Female Total

ABUA/ODUAL 194 175 369 93 26 119 62 16 78

AHOADA EAST 100 246 346 126 105 231 64 15 79

AHOADA WEST 140 126 266 113 60 173 100 22 122

AKUKU-TORU 38 82 120 86 64 150 24 11 35

ANDONI 135 95 230 101 24 125 38 8 46

ASALGA 51 124 175 33 25 58 31 30 61

BONNY 33 106 139 14 13 27 39 32 71

DEGEMA 85 150 235 76 67 143 27 17 44

ELEME 57 149 206 58 135 193 67 44 111

EMOHUA 196 166 362 191 164 355 122 32 154

ETCHE 298 205 503 181 76 257 149 42 191

GOKANA 201 131 332 132 52 184 143 27 170

IKWERRE 102 358 460 159 177 336 105 25 130

KHANA 413 177 590 190 63 253 178 38 216

OBIO/AKPOR 50 644 694 139 682 821 239 301 540

OGU/BOLO 49 53 102 14 21 35 9 3 12

OKRIKA 52 191 243 65 115 180 42 17 59

OMUMA 75 119 194 45 14 59 24 5 29

ONELGA 180 255 435 228 209 437 170 78 248

OPOBO/NKORO 59 68 127 39 17 56 2 1 3

OYIGBO 38 247 285 39 65 104 38 32 70

PHALGA 80 856 936 121 475 596 155 253 408

TAI 128 80 208 62 21 83 76 15 91

Grand Total 2756 4805 7573 2305 2670 4975 1904 1064 2968


Table 12B: Summary of Academic Staff Strength of Public Schools by LGAs and Gender

LGA Male Female

ABUA/ODUAL 349 217

AHOADA EAST 290 366

AHOADA WEST 353 208

AKUKU-TORU 148 157

ANDONI 274 127

ASALGA 115 179

BONNY 86 151

DEGEMA 188 234

ELEME 182 328

EMOHUA 509 362

ETCHE 628 323

GOKANA 476 210

IKWERRE 366 560

KHANA 781 278

OBIO/AKPOR 428 1627

OGU/BOLO 72 77

OKRIKA 159 323

OMUMA 144 138

ONELGA 578 542

OPOBO/NKORO 100 86

OYIGBO 115 344

PHALGA 356 1584

TAI 266 116

Grand Total 6963 8537


Table 13: Gender parity ratio across LGA

LGA Gender ratio

Parity

ABUA/ODUAL 1.032849 1

AHOADA EAST 0.997962 1

AHOADA WEST 0.944272 1

AKUKU-TORU 1.102789 1

ANDONI 0.940717 1

ASALGA 0.930582 1

BONNY 1.065939 1

DEGEMA 0.971656 1

ELEME 1.157858 1

EMOHUA 0.94579 1

ETCHE 1.029822 1

GOKANA 1.040854 1

IKWERRE 1.010268 1

KHANA 1.03288 1

OBIO/AKPOR 1.236886 1

OGU/BOLO 1.027586 1

OKRIKA 1.005176 1

OMUMA 1.018772 1

ONELGA 0.992986 1

OPOBO/NKORO 0.986842 1

OYIGBO 1.05981 1

PHALGA 1.252895 1

TAI 1.010367 1 GPI 1.06598 1

Table 14: LGAs Mean rating, MML, DML, and State Mean Score in Literacy

learning domain

LITERACY

Male Female STATE MEAN SCORE MML DML

Abua/ODUA 67.4 67.5 57.7 53.9 61.5

Ahoada East 56.8 58.4 57.7 53.9 61.5

Ahoada West 45.7 50.6 57.7 53.9 61.5

Andoni 54.6 56.0 57.7 53.9 61.5

Akuku Toru 66.9 70.1 57.7 53.9 61.5

Asari Toru 62.5 68.5 57.7 53.9 61.5

Bonny 61.2 63.0 57.7 53.9 61.5

Degema 64.8 64.6 57.7 53.9 61.5

Eleme 56.5 56.5 57.7 53.9 61.5


Emohua 52.9 53.9 57.7 53.9 61.5

Etche 66.3 66.9 57.7 53.9 61.5

Gokana 55.4 53.7 57.7 53.9 61.5

Ikwere 65.9 61.6 57.7 53.9 61.5

Khana 56.8 59.5 57.7 53.9 61.5

Obio/Akpor 61.8 64.9 57.7 53.9 61.5

Onelga 61.9 59.9 57.7 53.9 61.5

Ogu/Bolo 67.2 69.3 57.7 53.9 61.5

Okrika 64.7 57.3 57.7 53.9 61.5

Omuma 71.7 71.8 57.7 53.9 61.5

Opobo/Nkoro 62.2 63.0 57.7 53.9 61.5

Oyigbo 68.7 70.0 57.7 53.9 61.5

Port Harcourt 60.5 61.6 57.7 53.9 61.5

Tai 64.0 65.5 57.7 53.9 61.5

Table 15: LGAs Mean rating, MML, DML, and State Mean Score in Numeracy

learning domain

NUMERACY

LGA Male Female STATE MEAN SCORE MML DML

Abua/ODUA 58.4 57.7 49.6 44.9 54.3

Ahoada East 40.3 41.5 49.6 44.9 54.3

Ahoada West 47.8 46.0 49.6 44.9 54.3

Andoni 47.7 48.6 49.6 44.9 54.3

Akuku Toru 46.2 49.6 49.6 44.9 54.3

Asari Toru 39.7 40.1 49.6 44.9 54.3

Bonny 64.8 68.7 49.6 44.9 54.3

Degema 40.2 37.9 49.6 44.9 54.3

Eleme 57.1 57.1 49.6 44.9 54.3

Emohua 46.2 46.2 49.6 44.9 54.3

Etche 44.5 46.8 49.6 44.9 54.3

Gokana 46.7 40.6 49.6 44.9 54.3

Ikwere 60.6 54.2 49.6 44.9 54.3

Khana 48.4 48.7 49.6 44.9 54.3

Obio/Akpor 44.8 43.4 49.6 44.9 54.3

Onelga 73.3 74.3 49.6 44.9 54.3

Ogu/Bolo 62.7 60.1 49.6 44.9 54.3

Okrika 55.1 53.4 49.6 44.9 54.3

Omuma 49.5 52.8 49.6 44.9 54.3

Opobo/Nkoro 59.0 48.6 49.6 44.9 54.3

Oyigbo 50.9 50.8 49.6 44.9 54.3


Port Harcourt 49.0 50.3 49.6 44.9 54.3

Tai 42.0 42.5 49.6 44.9 54.3

Table 16: LGAs Mean rating, MML, DML, and State Mean Score in Life Skill

learning domain

LIFE SKILL


Abua/ODUA 79.7 81.0 70.9 67.0 74.8

Ahoada East 72.0 74.0 70.9 67.0 74.8

Ahoada West 55.4 53.9 70.9 67.0 74.8

Andoni 69.5 90.3 70.9 67.0 74.8

Akuku Toru 70.6 72.7 70.9 67.0 74.8

Asari Toru 68.5 71.9 70.9 67.0 74.8

Bonny 70.3 70.9 70.9 67.0 74.8

Degema 71.4 73.4 70.9 67.0 74.8

Eleme 71.5 71.5 70.9 67.0 74.8

Emohua 68.7 69.7 70.9 67.0 74.8

Etche 72.4 74.7 70.9 67.0 74.8

Gokana 61.7 59.0 70.9 67.0 74.8

Ikwere 74.8 78.5 70.9 67.0 74.8

Khana 69.9 69.7 70.9 67.0 74.8

Obio/Akpor 83.8 82.3 70.9 67.0 74.8

Onelga 48.6 49.8 70.9 67.0 74.8

Ogu/Bolo 72.4 70.9 70.9 67.0 74.8

Okrika 79.9 74.9 70.9 67.0 74.8

Omuma 64.5 65.4 70.9 67.0 74.8

Opobo/Nkoro 52.4 90.3 70.9 67.0 74.8

Oyigbo 69.4 69.1 70.9 67.0 74.8

Port Harcourt 72.6 73.0 70.9 67.0 74.8

Tai 70.3 46.9 70.9 67.0 74.8


Table 17: LGAs Mean rating, MML, DML, and State Mean Score in English

Language learning domain

ENGLISH LANGUAGE


Abua/ODUA 55.3 59.4 49.7 43.7 55.7

Ahoada East 37.2 41.4 49.7 43.7 55.7

Ahoada West 55.2 57.3 49.7 43.7 55.7

Andoni 31.8 33.1 49.7 43.7 55.7

Akuku Toru 41.8 41.7 49.7 43.7 55.7

Asari Toru 57.6 58.1 49.7 43.7 55.7

Bonny 52.5 54.7 49.7 43.7 55.7

Degema 37.3 38.9 49.7 43.7 55.7

Eleme 51.1 51.9 49.7 43.7 55.7

Emohua 50.5 54.6 49.7 43.7 55.7

Etche 51.0 45.1 49.7 43.7 55.7

Gokana 43.8 53.8 49.7 43.7 55.7

Ikwere 49.5 43.2 49.7 43.7 55.7

Khana 36.7 36.8 49.7 43.7 55.7

Obio/Akpor 54.0 54.5 49.7 43.7 55.7

Onelga 52.6 52.0 49.7 43.7 55.7

Ogu/Bolo 54.0 63.4 49.7 43.7 55.7

Okrika 53.8 55.3 49.7 43.7 55.7

Omuma 46.4 48.1 49.7 43.7 55.7

Opobo/Nkoro 39.2 40.3 49.7 43.7 55.7

Oyigbo 60.5 58.1 49.7 43.7 55.7

Port Harcourt 72.4 71.5 49.7 43.7 55.7

Tai 47.8 48.5 49.7 43.7 55.7

Table 18: LGAs Mean rating, MML, DML, and State Mean Score in Mathematics

learning domain

MATHEMATICS


Abua/ODUA 37.9 46.3 45.2 40.0 50.4

Ahoada East 57.8 46.1 45.2 40.0 50.4

Ahoada West 61.9 58.8 45.2 40.0 50.4

Andoni 48.6 49.6 45.2 40.0 50.4

Akuku Toru 54.6 52.9 45.2 40.0 50.4

Asari Toru 42.2 43.7 45.2 40.0 50.4


Bonny 64.5 63.6 45.2 40.0 50.4

Degema 37.8 24.4 45.2 40.0 50.4

Eleme 48.4 48.6 45.2 40.0 50.4

Emohua 48.0 47.0 45.2 40.0 50.4

Etche 44.9 41.8 45.2 40.0 50.4

Gokana 33.5 50.2 45.2 40.0 50.4

Ikwere 53.4 45.4 45.2 40.0 50.4

Khana 43.7 42.0 45.2 40.0 50.4

Obio/Akpor 33.8 40.0 45.2 40.0 50.4

Onelga 50.0 45.7 45.2 40.0 50.4

Ogu/Bolo 53.7 59.1 45.2 40.0 50.4

Okrika 57.2 53.4 45.2 40.0 50.4

Omuma 40.9 31.4 45.2 40.0 50.4

Opobo/Nkoro 38.4 37.4 45.2 40.0 50.4

Oyigbo 33.6 36.0 45.2 40.0 50.4

Port Harcourt 38.8 38.1 45.2 40.0 50.4

Tai 41.8 46.1 45.2 40.0 50.4

Table 19: LGAs Mean rating, MML, DML, and State Mean Score in General

Science learning domain

GENERAL SCIENCE

Male Female STATE MEAN SCORE MML DML

Abua/ODUA 70.4 78.3 58.4 50.5 66.3

Ahoada East 68.1 66.6 58.4 50.5 66.3

Ahoada West 44.5 45.9 58.4 50.5 66.3

Andoni 47.1 46.4 58.4 50.5 66.3

Akuku Toru 48.4 45.8 58.4 50.5 66.3

Asari Toru 65.6 65.8 58.4 50.5 66.3

Bonny 32.9 32.9 58.4 50.5 66.3

Degema 67.2 60.9 58.4 50.5 66.3

Eleme 72.0 69.9 58.4 50.5 66.3

Emohua 68.0 59.9 58.4 50.5 66.3

Etche 63.0 67.2 58.4 50.5 66.3

Gokana 45.9 49.0 58.4 50.5 66.3

Ikwere 37.3 35.0 58.4 50.5 66.3

Khana 51.7 53.7 58.4 50.5 66.3

Obio/Akpor 75.6 69.9 58.4 50.5 66.3

Onelga 65.3 69.3 58.4 50.5 66.3

Ogu/Bolo 68.1 73.5 58.4 50.5 66.3

Okrika 77.3 70.7 58.4 50.5 66.3


Omuma 41.7 35.5 58.4 50.5 66.3

Opobo/Nkoro 45.0 46.2 58.4 50.5 66.3

Oyigbo 70.4 63.1 58.4 50.5 66.3

Port Harcourt 72.5 71.0 58.4 50.5 66.3

Tai 58.0 59.6 58.4 50.5 66.3

gender differences in learning outcome

Documents

s o n o

i n t o

b o b e r n

n c y e n e

t o r i n g

g e c o n s u

d e y e

j o y o b