MLA in Rivers State, An Overview

Monitoring Learning Achievement

inRivers State Public

SchoolsVolume I

Prepared for the Rivers State Government by Arbitrage Consult Ltd.

Table of ContentsExecutive Summary...............................................................................................................................4

Chapter One..........................................................................................................................................7

The Monitoring Learning Achievement Study: Meaning, History and Importance........................7

Introduction to MLA......................................................................................................................8

MLA: From 1992 till Date...............................................................................................................9

Aim of the Survey........................................................................................................................10

Uses of MLA.................................................................................................................................10

Intelligence Testing......................................................................................................................10

Social and Economic Assessment................................................................................................11

An Assessment of the Impact of Government Spending and Policies on Education....................12

A tool for policy formation..........................................................................................................13

Scope and Methodology..............................................................................................................14

Sample Selection.........................................................................................................................14

Sample size..................................................................................................................................14

Data Sources................................................................................................................................16

Data Collection and Analysis........................................................................................................16

Challenges faced in carrying out the Study..................................................................................17

The Study Area: Rivers State........................................................................................................17

Chapter Two........................................................................................................................................20

Review of Monitoring Learning Achievement Surveys in Selected Countries.............................20

MLA Survey in Rivers State..........................................................................................................20

MLA Survey in Nigeria..................................................................................................................21

MLA Survey in Ghana...................................................................................................................23

Botswana.....................................................................................................................................24

Kenya...........................................................................................................................................25

Regional Monitoring Learning Achievement (MLA) Survey 1999................................................27

Lessons from Previous Studies.....................................................................................................29

Chapter Three......................................................................................................................................30

General Description and Characteristics of Survey Respondents................................................30

3.1 Background Information Supplied by the Pupils....................................................................30

3.2 Background Information Supplied by the Parents.................................................................39

1| P a g e A r b i t r a g e C o n s u l t L t d E m a i l : a r b i t r a g e c o n s u l t @ g m a i l . c o m+ 2 3 4 ( 0 ) 8 0 2 3 3 2 3 3 7 8 o r + 2 3 4 ( 0 ) 8 0 7 2 5 7 8 1 4 5

3.3 Background Information Supplied by Teachers.....................................................................43

3.4 Background Information Supplied by School Heads..............................................................48

Chapter Four........................................................................................................................................50

Test Performance.....................................................................................................................50

Pupils Performance in Literacy Test.............................................................................................52

Pupils Performance in Numeracy Test.........................................................................................53

Pupils Performance in Life Skills Test...........................................................................................54

Students Performance in English Test.........................................................................................57

Students Performance in Mathematics Test................................................................................58

Students Performance in General Science Test...........................................................................59

Chapter Five........................................................................................................................................60

How well did the Pupils/ Students Perform?.............................................................................60

Chapter Six..........................................................................................................................................69

Factors that Affect Learning Performance (A Test of Selected Variables)...................................69

Determinants of Learning Achievement..............................................................................................75

Gender differences...................................................................................................................75

Locational differences...............................................................................................................75

Other factors............................................................................................................................75

Conclusion and Recommendations.....................................................................................................77

Comparison of Survey findings with those from other studies............................................................80

References.............................................................................................................................................0



Executive Summary

Monitoring learning achievement is an important exercise in the evaluation of any educational system. It is a necessary or an imperative to do this if a society must be able to articulate the effectiveness of policy actions and financial outlay on education. Rivers State government under Governor Rotimi Amaechi has invested heavily in improving infrastructure and teaching materials, recruiting new teachers and undertaken policy reforms in order to achieve all the Education for All (EFA) goals.

This report contains the findings of the Monitoring Learning Achievement survey for primary and secondary schools funded by the Rivers state government. Learning achievement is defined as the gap between what is taught and what is learned and the Monitoring Learning Achievement survey was carried out with the objective of ascertaining the length and depth of that gap.To achieve this objective, the following variables were considered:

Internal variables (within the school environment) including the learning environment, teaching methods and curricular arrangement.

External variables (outside the school environment) such as parents’ educational backgrounds, distance to school and availability of transport.

To obtain the needed information, questionnaires and test questions were administered to relevant respondents- pupils, students, parents, teachers, principals and head teachers- across the twenty-three local governments of the state. The principals and head teachers acted as our primary contacts. The survey covered 1,209 state owned primary and secondary schools across the twenty-three local governments. 916 of those were primary schools and 293 were secondary schools. Each school received 15 students’ questionnaires, fifteen parents’ questionnaires and one questionnaire for the administrative head. Primary schools were administered 2 teachers’ questionnaires each and secondary schools were administered 4 teachers’ questionnaires each. In all, the questionnaires sent out totalled:

13,740 Primary Four Pupils’ Questionnaires 4, 395 Junior Secondary Students’ Questionnaires 18,135 Parents’ Questionnaires 3,004 Teachers’ Questionnaires 916 Head Teachers’ Questionnaires 293 Principals’ Questionnaires

Each school received 15 test questions. In all, 18,135 test questions were administered covering the following learning domains:

Primary schools: Literacy, numeracy and life skills. Secondary schools: Mathematics, English and general science.


Using quality control charts, minimum mastery levels (MML) and desired mastery levels (DML) were derived for all the domains. The mastery levels are cut-off scores used to rate students’ understanding of specific subjects. The MML is the lower limit of the mastery level while the DML is the upper limit of the mastery level. Scoring below the MML denotes a lack of understanding. Scoring up to or above the MML, but below the DML denotes a satisfactory level of understanding. Scoring up to or above the DML denotes excellent understanding.The information obtained from the returned questionnaires and test questions was sorted, analysed and translated as it relates to student performance. The survey unearthed several factors that affect students’ performance. A sentiment that echoed across the board is the shortage of basic school facilities. Our respondents bemoaned the lack of such key infrastructure as libraries, computer rooms and toilets and their availability was rated at 19%, 13% and 22% respectively. Availability apparently does not automatically translate into functionality as a high percentage of the available facilities were rated as under equipped or not at all equipped. Our research also turned up elements of inconsistency within the system. Specifically, there seems to be a principal-agent problem within the system. For example, despite the state government having lifted the payment of school fees, a significant number of the respondent parents report to the contrary. Their expenses include payments for school uniforms, school furniture, text books and the ‘school fees’ itself. This may or may not be going on with the knowledge of state education authorities and the school teachers.The responses received from the teachers reveal that a significant number of them are not willing to remain in the profession for the long term either because of the nature of their professional training or because of certain socioeconomic factors. Specifically, only 42% of the teachers who responded have university degrees in education. The remaining 58% studied in other fields and they probably view teaching as a temporary source of livelihood available to them while they search for something more desirable. Also, 36% of the respondents indicated a willingness to change career given the right incentives, chief of which were the prospects of better pay, improved working conditions and career advancement.

Being the primary focus, it was essential that we got into the minds of the students. Their personal characteristics, the influence of the people around them and the influence of their physical environment on their ability to learn were important factors that we obtained through our questionnaires. Very disturbing is the revelation that less than 40% of our respondents regularly enjoy three meals a day. 35% are victims of bullying. Our survey also unearthed the fact that most students who miss school do so on health grounds.

The Primary Four pupils did best in the Life skills learning domain and recorded the poorest mean scores in numeracy. While the JSS Two students recorded the highest mean score in


General science and the lowest in Mathematics. The test performance was found to vary across the urban and rural areas in the State with the highest scores in most of the learning domains being recorded in urban areas though the urban-rural differences in learning outcome were not statistically significant. Gender differences in learning outcome were also not statistically significant with girls performing fractionally better than boys.

The majority of parents who responded lack tertiary education. The secondary school leaving certificate is the most commonly cited qualification for parents in the sample. Only 41% of the parents in the sample regularly participate in school-related activities. A further 46% participate sometimes and 13% never participate.

75% of the students in the sample confirmed that they receive after-school academic support. It is positive that the most common after-school activity among students is attending extra-mural classes. This, however, accounts for only 36% of the sample. A further 29% take part in commercial activities and the same percentage perform house chores. Responses regarding students’ feeding patterns revealed that only 39% of them regularly have breakfast and lunch while 5% of them usually have neither.

It was established, through statistical analysis, that adequately fed students score higher marks than their inadequately fed counterparts. Also, students who attend extramural classes score higher marks than their colleagues who do not attend. These findings are true to our a priori assumptions. Contrary to those assumptions are the findings that students with no home assistance with their assignments performed better than their colleagues who have assistance.

Broadly speaking, the suggestions to solving the above highlighted problems lie in taking the following measures;1. More funds need to be allocated to the installation and development of needed educational infrastructure such as libraries, toilets and computer rooms. These funds must come from the state government and from the private sector who have an undoubted social responsibility to the inhabitants of the communities in which they do their business.2. It is necessary for the government to monitor more closely, the activities of its agents within the ministry and in the schools. This is to ensure these agents do not perform acts that deviate from or run completely contrary to the directives of government.3. Government’s recruitment criteria for teachers should work to separate the true educationists from those who are just looking to earn a salary. The government must become partial to applicants of a certain professional and attitudinal persuasion. 4. The school children of Rivers state face major socioeconomic challenges (financial problems, inaccessibility of proper healthcare) that hamper their ability to learn. These challenges can be tackled within and outside school with relevant legislation and social orientation. These efforts should aim to offer the children better protection, provide them


with better health care and arm their care givers with knowledge that will help them to help their wards become better students.

Chapter One

The Monitoring Learning Achievement Study: Meaning, History and Importance

The Monitoring Learning Achievement Study of Rivers State Public Schools is presented in four detailed volumes which are:

1. Monitoring Learning Achievement Study of Rivers State Public Schools: An Overview- This volume gives a general description of the study (its purpose, its nature, the methodology of it and the general results). It is an introductory chapter and serves as the foundation for the structures and the formats of the succeeding volumes.

2. Monitoring Learning Achievement Study of Rivers State Public Schools: Gender and Learning Performance- This volume presents and analyses students’ learning performance along gender lines.

3. Monitoring Learning Achievement Study of Rivers State Public Schools: Rural and Urban Differences in Learning Performance- in this volume, it is examined to what extent students’ learning performances differ along locational lines.

4. Monitoring Learning Achievement Study of Rivers State Public Schools: Determinants of Learning Performance- In this volume, the factors that affect learning performance are presented in qualitative and quantitative detail.

This document is the first volume, the overview. It comprises six chapters, the first of which is titled, The Monitoring Learning Achievement Study: Meaning History and Importance. This chapter looks at the meaning, the evolution and the uses of MLA and explains its relevance in the Rivers state context.

Chapter 2 is titled, Review of Monitoring Learning Achievement Surveys in Selected Countries. Here, MLA is discussed as a global concept. Using various countries as case studies, it is shown how MLA has been successfully implemented all over the world.

General Description and Characteristics of Survey Respondents is the title of chapter 3. It contains the findings of the study, presented with the use of graphical aids.

Chapter 4 is titled Test Performance. It is a presentation and analysis of the scores from the tests administered to Primary Four and JSS Two students. The scores are compared and contrasted based on gender and location.


Chapter five is titled, How Well Did The Students/Pupils Perform? In this chapter, the children’s individual and mean scores are measured against the MML and the DML.

The sixth chapter is titled, Factors That Affect Learning Performance (A Test of Selected Variables). Here, a few randomly selected variables are analysed to establish the nature of their relationships (positive or negative) with students’ learning achievement.

The volume is rounded off with a list of conclusions and recommendations deduced from the results of the study.

Introduction to MLAEvery investment whether financial, mental, physical or emotional requires a return. We as human beings require returns on our investments. Ideally, returns should surpass investment and at worst, returns should be equal to investment. That is to say every investor hopes to make a profit or at least break even.

That brings us to the question; what constitutes a profit and how is profit measured. The answer varies depending on who you ask. In the profit industry, a profit is achieved when earnings exceed expenditure and it is measured as the difference between income and outcome.

The computation of profit is, however, not so straight forward in the public sector. Here, profit is not measured in terms of how much money is made, but in terms of how many lives are impacted and how deeply they are impacted. Public spending is intended to effect specific changes in the consumption patterns, the income distribution and the standard of living of the populace.

The Rivers state government through its ministry of education has invested heavily in the state's education sector. At great financial cost, old schools have been renovated, new model schools have been built, learning facilities have been upgraded, additional teachers have been employed and the cost of education has been heavily subsidized.

All these actions are being taken for the benefit of the school children of Rivers state. But are the children really benefiting? What has been the impact of the government's huge expenditure on the quality of education that the children receive? What has been the impact thus far of government’s spending on the actual learning outcome? Can the government do more and if yes, in what aspects can they do more? Is the government's investment yielding the desired outcome?

The Monitoring Learning Achievement (MLA) survey will provide answers to some of the above questions. Started in 1992, MLA is the brainchild of a joint UNESCO/UNICEF team on education. MLA is an educational assessment initiative that aims to ascertain the actual impact of educational investment and socioeconomic factors on actual learning. MLA is a tested and trusted method of educational assessment and it is exactly the tool required by 8| P a g e A r b i t r a g e C o n s u l t L t d E m a i l : a r b i t r a g e c o n s u l t @ g m a i l . c o m

+ 2 3 4 ( 0 ) 8 0 2 3 3 2 3 3 7 8 o r + 2 3 4 ( 0 ) 8 0 7 2 5 7 8 1 4 5

the Rivers State Ministry of Education to evaluate the worthwhileness of its investment in education.

MLA: From 1992 till DateMLA has been adopted the standard learning achievement measuring tool in the world. MLA was introduced in 1992 but its seeds were being sown long before that time. The United Nations, through its agencies UNICEF and UNESCO, has for decades, been at the forefront of the fight against illiteracy. In the beginning, their strategy focused solely on enablement i.e. they assisted member countries to develop their educational systems by providing financial and professional support. The object of all these efforts was to boost learning.

As time went by, it became necessary to evaluate the progress thus far. It was agreed that the best way to determine the extent of learning is to assess the learners themselves. A list of criteria for assessing the students were then developed. The list includes the following:

1. Students’ learning achievement: Students are to be put through standardized tests to test their mastery of literacy, numeracy and life skills. Students’ scores will determine if they have achieved the requisite knowledge for the level of education that they have attained.

2. Students’ socioeconomic environment: It has been proven that students’ performance in school is influenced by factors other than those which exist within the educational environment. Factors such as family backgrounds, peer influences, media exposure, government policies and even geographical environments can influence students’ ability to learn. To properly assess the students, it is necessary to determine in what direction and to what extent these influences play a part in their ability to learn.

3. The learning environment: Nowhere do there exist more factors that affect learning achievement than within the learning environment itself. Teachers have a profound and direct influence on students’ ability to learn. The teachers’ educational and professional backgrounds, their attitudes and the socioeconomic challenges they face all affect their effectiveness in the learning environment.Infrastructure or the inadequacy thereof could enhance or diminish a student’s educational experience. Facilities such as toilets and dispensaries make the school environment conducive for the students. Libraries and computers are standard facilities in the modern day learning environment, the absence of which reduces a students’ learning options.Administrative factors could conspire to either encourage or discourage teachers’ and students’ interests in their work.


It was with these criteria in mind that the Monitoring Learning Achievement Project was developed in 1992. MLA is the product of joint consultations by educational experts representing UNICEF and UNESCO. It was initially designed to measure the learning achievement of students in standard four but has since been upgraded to accommodate students of any standard.Since the introduction of the Monitoring Learning Achievement study, it has been implemented in several countries to great success. Countries in which MLA has been implemented include Ghana, Thailand, Mauritius, Gabon, Botswana, Madagascar, Senegal and the Republic of Niger.

Aim of the SurveyData is the basic element on which MLA thrives. So naturally, the process of Monitoring Learning Achievement begins with the determination of what data is needed. The nature of the data needed is encapsulated in the characteristics of high performing schools as determined by the United States Department of Education which are;

1. A clear and shared focus.2. High standards and expectation for all students. 3. Effective school leadership.4. High levels of collaboration and communication.5. Curriculum, instruction and assessment aligned with state standards. 6. Frequent monitoring of teaching and learning. 7. Focused professional development.8. A supportive learning environment.9. High levels of parent and community development.

Questionnaires are prepared in such a way as to extract as accurately as possible, data on the above characteristics. These questionnaires are then distributed to the appropriate respondents. For this study, the appropriate respondents were determined to be the students/pupils, parents, teacher and school administrative heads.

On receiving back the questionnaires, the data is extracted, sorted, then descriptively and statistically analysed as it relates to learning achievement. The knowledge obtained from the survey serves as a measure of the effectiveness of government policies and spending on education as well as an effective tool in the determination of future policies and spending on education.

Uses of MLAThe Monitoring Learning Achievement survey is a multifaceted educational assessment tool, the uses of which are multifold.


Intelligence TestingMLA is an IQ test for students. Specifically tested are the students’ learning achievement in literacy and numeracy and their mastery of life skills. The tests are composed of topics that the students are likely to have been exposed to at their level of education. In the preparation of test questions, standardized educational assessment models are consulted. These models include.

Trends in International Mathematics and Sciences Study (TIMSS):TIMSS is an international assessment of the mathematics and science knowledge of 4th and 8th grader (loosely ages 9/10 and 13/14 respectively) students around the world. TIMMS was developed by the International Association for the Evaluation of Educational Achievement (IEA) in 1995 to allow participating nations to compare students’ educational achievement across borders.

Programme for International Student Assessment (PISA): PISA is a mathematics, science and reading study for 15 year old students. It was developed by the Organization for Economic Cooperation and Development in the year 1997 and it covers both member and non-member countries. It was created with a view to improving educational policies and outcomes. The data has been used to assess the impact of education quality on the economy and for understanding what causes differences in educational quality across nations.

Progress in International Reading Literacy Study (PIRLS): An initiative of the IEA, PIRLS is a study of the reading achievement of 4th grade students. According to the IEA “It is designed to measure children’s literacy achievement to provide a baseline for future studies of trends in achievement and to gather information about children’s home and school experiences in learning to read.”

Social and Economic AssessmentThe MLA study is an assessment of the impact of the economy on educational quality and vice versa. Similarly, it tests for the impact of the social environment on educational quality and vice versa. MLA is able to achieve this through its extensive and all-encompassing scope of study.

Respondents to MLA questionnaires cover the spectrum of participants in the educational system. These are the students and pupils who are the receivers of the education and the primary focus of the study. There are also the parents and guardians who pay for their wards’ education. Finally there are the school teaching and administrative staff that teach and guide the students in the learning environment. The range of questions of these respondents is extremely wide and extends well beyond issues that relate directly to education. The scope of questioning is described below.

Students and Pupils are asked questions relating to:


Their personal characteristics e.g. age, sex. Their family backgrounds: Students provide information about afterschool academic

support. Their mind-set: Students’ attitudes to their subjects and their satisfaction or lack

thereof with several aspects of schooling are ascertained. The nature of their extracurricular activities. Socioeconomic situations such as distance to school, access to transportation and

exposure to media and regularity of attendance and health challenges.

Parents and Guardians are asked questions relating to:

Their personal characteristics. Their family backgrounds: They provide information about their marital status and of

their household sizes. Their educational background: This information gives insight into the nature of

employment these parents and guardians will be able to secure which consequently determines their level of income. Also, when parents’ educational backgrounds are matched against their wards’ academic performance, we see the correlation and/or

association between the two. Their state of mind as regards to their children’s schools and the need for the

children to attend school.

School Staff are asked questions relating to:

Their personal characteristics. Their educational qualification and professional training. Work experience and work satisfaction. Socioeconomic situations such as distance to school, access to transportation and

exposure to media and regularity of attendance and health challenges.

The questions asked of the respondents cover practically the full spectrum of their professional and personal lives. In this way, MLA serves a socioeconomic assessment tool as well as a learning achievement assessment tool.

An Assessment of the Impact of Government Spending and Policies on EducationGovernment expenditure and policy formulation on education is made with specific goals in mind. The structure of the MLA study is such that it can be determined if and to what extent these goals are being achieved. Through MLA, it is ascertained if and to what extent educational spending and educational policies have led to an improvement in the following:


Enrolment rates: By increasing the infrastructural and academic standard as well as subsidizing tuition costs, government expects the rate of enrolment in its schools to increase.

Learning outcomes: The government is providing new learning facilities in its schools as well as upgrading existing ones in the hope that this will boost the students’ performances across the learning domains. These facilities include libraries and computers. Simultaneously, teachers are being put through government sponsored up skilling programs so as to be able to provide a more qualitative education to the students.

The conduciveness of the school environment: The extent to which students feel comfortable and secure in the school environment has a profound effect on their attendance rates, their commitment and consequently, their academic performance. In recognition of this fact, facilities such as toilets and dispensaries are being built in government schools. More classes are being built while more teachers are being recruited so as to achieve the state recommended student/teacher ratio of 25:1.

A tool for policy formationThe in-depth analysis provided by the MLA study assists policy makers to formulate accurate educational policies and determine where and how educational funds need to be spent. MLA is designed to identify the factors that affect learning achievement, the extent, frequency and distribution of these factors across various locations as well as the reasons for the disparities in learning achievement across groups and locations. The causes for disparities in learning achievement include:

Locational causes: Learning achievement differs across urban and rural locations. This can be attributed to the differences in population, commercial development and infrastructural development between the two.

Gender related causes: It has been discovered that there exist gaps in the achievement of boys and girls. Factors responsible for this include attitudinal differences between the two sexes as well as differences in the societal attitudes to boy child education and girl child education.

Foundational causes: It has been established that children with access to quality early childhood education tend to perform better in school than kids who do not have access. Also, the quality of academic support received outside of the academic environment has heavy implications on students’ performance.

Institutional causes: These are the political factors that affect the quality of education delivery and the accessibility to education across locations.


Scope and MethodologyRivers state government education reforms started during the first term of Governor Chibuike Amaechi’s regime in May 2009. This reform is comprehensive; encompassing infrastructural development, human-up skilling and school material supplies. The scope of this study covers the period when the state started the implementation of the reforms to July, 2013 when this MLA survey was conducted. Restricted to public Schools alone, it covered all the 23 LGAs in the three senatorial districts of the state, with emphasis on public primary and secondary schools in both rural and urban areas in order to ensure a balanced spread.

Sample SelectionFor the purpose of this MLA study, we randomly selected 15 pupils from Primary four and 15 students from junior secondary school two (JSS2) in all the public primary and secondary schools across the twenty-three local governments in the state, who are believed to have spent at least a period of 18 months and above in their respective present primary and secondary schools.

Sample sizeA total of 1,209 number of Public Schools were surveyed which consists of 916 Public Primary Schools and 293 Junior Secondary Schools. 10,371 Primary four pupils responded out of 13,740 questionnaires sent out and 3,340 JSS2 students responded out of 4,395 questionnaires distributed. The overall response rate for pupils was 75.5%, while that of student was 76%. Similarly, out of 18,135 parents’ questionnaires distributed 75.3% response rate was achieved. Likewise, out of 3,004 teachers and 916 school head questionnaires distributed a response rate of 42.5% and 71.3% was recorded respectively. The tables below illustrate the number of questionnaires distributed and responses received

Table 1.1: Number of Questionnaires Distributed in Schools across the LGAs

S/N

LGAs NO. OF PRY

SCHOOLS

NO. OF SEC

SCHOOLS

PUPILS

STUDENTS

PARENTS

PRY SCHO

OL TEACH

ERS

SEC SCHO

OL TEACH

ERS

HEAD TEACH

ERS

PRINCIPALS

1 ABUA/ODUA

49 31 735 465 1200 98 124 49 31

2 AHOADA-EAST

38 19 570 285 855 76 76 38 19

3 AHOAD-WEST

60 11 900 165 1065 120 44 60 11


4 ANDONI 58 10 870 150 1020 116 40 58 105 AKUKU-

TORU22 6 330 90 420 44 24 22 6

6 ASARI-TORU

27 10 405 150 555 54 40 27 10

7 BONNY 21 3 315 45 360 42 12 21 38 DEGEMA 24 6 360 90 450 48 24 24 69 ELEME 22 5 330 75 405 44 20 22 5

10 EMOHUA

51 21 765 315 1080 102 84 51 21

11 ETCHE 80 44 1200

660 780 160 176 80 44

12 GOKANA 39 9 585 135 720 78 36 39 913 IKWERRE 39 14 585 210 795 78 56 39 1414 KHANA 79 22 118

5330 1515 158 88 79 22

15 OBIO/AKPOR

43 19 645 285 930 86 76 43 19

16 ONELGA 71 19 1065

285 1350 142 76 71 19

17 OGU/BOLO

15 3 225 45 270 30 12 15 3

18 OKRIKA 34 6 510 90 600 68 24 34 619 OMUMA 21 4 315 60 375 42 16 21 420 OPOBO/

NKORO17 5 255 75 330 34 20 17 5

21 OYIGBO 21 2 315 30 345 42 8 21 222 PORT

HARCOURT

50 11 750 165 915 100 44 50 11

23 TAI 35 13 525 195 795 70 52 35 13TOTAL 916 293 13,7

404,395 18,13

51,832 1172 916 293

Total no of schools surveyed (Primary and secondary schools) – 1,209

Table 1.2: Response Rate

RESPONDENTS NO OF QUESTIONNAIRES SENT

NO OF QUESTIONNAIRES

RETURNED

RESPONSE RATE

Primary four pupils 13,740 10,371 75.5%

JSS2 students 4,395 3,340 76%

Parents 18,135 13,650 75.3%

Teachers (Primary/Sec School

3,004 1,278 42.5%


Teachers)Head teachers 916 653 71.3%Principals 293 77 28.2%

Data SourcesThe data used for this study was sourced with the aid of questionnaires administered to Pupils in Primary four, Students in JSS2, parents, teachers, head teachers and principals in sampled schools across the twenty-three local governments. Test questions in different learning domains including: literacy, numeracy and life skills were administered to Primary Four pupils, while test questions in Mathematics, English Language and General Science were administered to JSS2 students.

Data Collection and AnalysisA one-day Inception workshop in which all the teachers and head teachers from all the public primary and secondary schools were present was held at the Ministry of Justice Hall, State Secretariat, Port Harcourt, Rivers State. The aim of the workshop was to explain the purpose, objective and the methodology of the tests, as well as the modalities for the selection of students/pupils, teachers, parents and arrangement for returning the survey instruments after the survey.

The Data gathering technique for the pupils and students involved Simple random sampling, while Purposive Sampling technique was used to select the Parents of Pupils/students who automatically became respondents due to their children or wards being chosen. Likewise, purposive sampling was used to select specific class teachers of Primary 4 pupils, subject teachers of Junior Secondary Schools, Head teachers and Principals from the sampled schools.

The collection exercise required the use of two selected class teachers in each of the Primary Schools and four carefully chosen Secondary School teachers in each of the Junior Secondary Schools to assist in the Administration of respective test questions, pupil/student questionnaires and parent questionnaires to each of Pupils/ students. Head teachers and Principals supervised the process to ensure it went on smoothly.

The sampled pupils/students took the parent questionnaires home for their respective parents/guardians to fill and returned them the following day. While the selected teachers and head teachers completed their questionnaires instantly, collated the test questions and all the respondent questionnaires together and delivered them to the collection point.

The instruments were administered in July 2013, three weeks to the end of the third term of the school calendar (2012/2013 Academic Session). The tests and the questionnaires were completed at the schools, except for the parent questionnaires which the pupils/ students took home to their parents/guardians.


The tests assessing pupils learning achievement in primary schools covered three areas namely: (i) Literacy (Vocabulary, Comprehension, Grammar and Writing) (ii) Numeracy (Numbers, Measurement and Quantitative Techniques) and (iii) Life Skills (Health, Civic and Environment). Tests assessing students learning achievement in secondary schools covered Mathematics, English Language and General science. Question papers in each learning domains were prepared and administered within a stipulated time and were marked by independent examiners.

The marked sheets, alongside the completed questionnaires from each Local Government were sent through the Secretaries of the LEA’s (Local Government Education Authorities) to the central collection point at the State Secretariat where our officials were stationed. Our officials, after sorting and arranging the responses according to local government areas forwarded the survey Instruments to the central office in Abuja to be analysed by our data Analysts. The data Analysts subjected the data collected through various rigorous processes such as data (inputting, cleaning) to ensure credibility of the data collected to remove extreme values (outliers) as a means of quality control.

Basic descriptive statistics such as frequency distribution, mean, standard deviation were carried out as well as further tests such as t-tests, correlation, normality tests and ANOVA were also used to analyse the data. However, narratives of the descriptive statistics were done to enable easier comprehension by non-technical readers and policy makers without statistical Knowledge to facilitate Policy Implementation.

Challenges faced in carrying out the StudyIn the course of carrying out the study certain challenges were encountered; such as omission of vital Information by some respondents. Some respondents were not truthful with some personal details, therefore such information was disregarded. Some respondent Information was also rendered null and void as a result of discrepancies observed in certain responses and was eliminated during data cleaning. Similarly, influence of some teachers in some schools in the answering of the test questions were observed and accordingly led to the exclusion of test papers.

The Study Area: Rivers State

Location, Geography and Ethnic Characteristics of Rivers stateRivers state is Nigeria’s southernmost state. Its capital Port Harcourt is one of its 23 local governments. Port Harcourt is considered the commercial capital of Nigeria’s Southern region. Rivers state is Nigeria’s premier crude oil producing state as well as a hub of commercial marine activity due to its abundance of natural water resources. There are two major refineries and two major seaports in the state.


Rivers state is a multi-ethnic society. Ethnic groups in the state include the Ogoni who are of Ghanaian origin, the Epeye who emigrated from the old Benin Empire and the Etche who are of Igbo descent, Ijaw, Ikewrre, Kalabari and Andoni.

The state’s immense oil wealth means that the government has a significant amount of money available to it to dedicate to education. On the flipside, the plethora of unskilled jobs available in the oil and gas industry has led many youths to ignore school and go to work instead. Some people pervert the system and access the oil money through extortion, lobbying and bunkering.

Socioeconomic Environment of Rivers stateRivers state constantly witnesses the emigration on non-indigenes from within and outside the country. This is due to the vast employment opportunities available in the state. The influx of the migrant schoolers is not factored into the state’s educational planning and this leads to population constraints in the schools.

Following an era of militancy that plagued the state for the best part of the first decade of this century, peace has returned to the state under Governor RotimiAmaechi. Children who were kept out of school during the years of insecurity have since returned to school. However, many of them have resumed in classes suited to their current ages but above their academic ability. This partly accounts for some of the below par performances currently being witnessed in primary and secondary schools.

Mainland/Island divide in Rivers stateRivers state is made up of a large mainland and several smaller islands. Government investment on the mainland exceeds that of the islands. This is evidenced by the disparity in infrastructural adequacy between the two with the airports located in Port Harcourt and the sea ports located in Port Harcourt and Eleme which are both located on the mainland.

Perhaps due to their distance from the headquarters of government, no significant government infrastructure is located outside of the mainland with islands like Kala Ibiama not even connected to the national power grid. The disparity in government investment also extends to education with government’s spending thus far being mostly on mainland schools. Island schools also tend to be less supervised which may lead to high levels of absenteeism on the parts of both students and teachers. For this reason, island schools may have a lower all-round standard than that of their mainland counterparts and consequently, their students may perform less well than their peers across the water.

Environmental issues in Rivers stateNwachukwu and Uguanyi noted that “the ambient air quality in Rivers state is far worse than the World Health Organization Air Quality Standard”. This is especially true in the host communities of the major manufacturing and exploration companies. Cement dust from construction sites, lead from paint and carbon monoxide from gas flaring cause respiratory


and blood diseases. The sicknesses associated with poor air quality pose a danger to the health of teachers and students and may be blamed for some cases of absenteeism.

Crude oil spills have deteriorated the quality of marine resources in the state. The implications of this are both social and economic. Consumers of wildlife who have been infected by the pollution are prone to infection themselves. Also, due to the depletion of the aquatic life, fishing which is Rivers state’s staple profession has become a far less profitable venture in recent years. With fishermen’s income dropping, they may become hard-pressed to finance their kids’ education.


Chapter Two

Review of Monitoring Learning Achievement Surveys in Selected CountriesThe importance of education as a fundamental factor in national development has been globally acknowledged. Not inconsequential to this acknowledgment have been the various Education for All (EFA) conferences held at different times since 1999 and the annual EFA global progress reports published to monitor the extent of achievement of the set EFA goals. All these have stimulated investment in education around the world.

However, investment in education in terms of provision of adequate infrastructure, learning materials and teachers does not automatically imply that the school goers achieve mastery of knowledge and skills expected of them at various levels of education. Education is not an end in itself but a means to an end, which could be national development, skilled labour force, etc. To achieve these ends, the process of education has to cumulate in knowledge and skill acquisition. The extent to which investments in education result to better learning performance of school children has been the reason for the conduct of learning achievement assessments in many countries. This chapter contains a review of some of such assessments.

MLA Survey in Rivers StateAn assessment of the learning achievements of pupils/ students in Rivers State was conducted in the first quarter of 2013 by an independent consultant funded by the Rivers State Ministry of Education. It was a preliminary survey geared towards gathering information for education decision makers as regards the impact of the State government’s reforms in terms of infrastructural development on the education sector. It emanated out of a need to match government reforms against performance of students in Rivers State public schools.

The survey covered two public schools – one primary school and one secondary school- in each of the twenty-three local government areas in the state. The schools were randomly selected. 30 pupils/ students were selected from each local government – 15 Primary Five pupils and 15 JSS Two students. There was also a random sample of school teachers, head teachers and parents.

The Primary Five pupils were tested in three learning domains namely: Literacy, Numeracy and Life skills. While, the JSS two students were tested in Mathematic and English Language. The test questions in each of the learning domains were prepared and administered by independent examiners.


Questionnaires were administered to the randomly selected school teachers, head teachers and parents in order to gather background information on some endogenous factors (within the school environment) and exogenous factors (outside the school environment) that affect the learning achievement of pupils/ students.

Generally, the surveyed primary school pupils performed poorly with a total mean score of 43%. The JSS two students performed better with a total mean score of 60%. However, both primary and secondary schools recorded low scores in the Numeracy and Mathematics learning domains respectively. The scores were impressive in the Literacy and English Language learning domains.

The study reports that in terms of overall performance, secondary schools out-performed primary schools. Locational discrepancies in pupil/ student performance were found to be narrow and perhaps non-existent.

The information gathered from the questionnaires administered revealed little about the factors that affect learning achievement of pupils/ students. This was attributed to the preliminary nature of the study and time constraints within which it was conducted. However, consideration of the after-school activities of the pupils/ students as revealed by parents led to the recommendation that remedial classes should be introduced.

As earlier stated, this was a preliminary study and it largely succeeded at its task of laying a foundation for a larger and more comprehensive MLA survey.

MLA Survey in NigeriaThe history of assessing education standard in Nigeria can be traced back to 1996; however, in 2003, MLA survey was conducted by the Federal Ministry of Education as a form of follow up exercise to the 1996 assessment. The scope of the 2003 study was limited to students in primary schools specifically primary 4 and 6 in 774 LGAs areas across the country.

A multi-stage sampling design was adopted with probability proportional to the number of schools within the LGAs in each state. 28 schools were sampled in each state and 14 from Abuja FCT totalling 1,036 schools and at least 20% of the selected or sampled schools in each state were private schools. From sampled schools, 30 pupils were randomly selected from primary 4 and 6 respectively.

Two categories of instruments were developed- (1) Learning Achievement Test instruments in Literacy, Numeracy and Life Skills test; (2) Questionnaire for pupils, teachers and parents. Nationwide administration was carried out in June/July 2003.

In all the areas tested the pupils in private schools performed better than their public schools’ counterpart. The urban schools performed better than the rural schools, boys performed slightly better than girls, pupils who had pre-primary education did better than pupils who did not and Life Skills recorded the lowest result of mean score of 25.42%.


Table 2. 1State Means Scores from 2003 Education Assessment for Primary IV Pupils

S/N States Literacy Numeracy Life Skills Total Average1 Ogun 50.8 49.27 60.3 160.38 53.462 Kaduna 51.63 47.75 56.78 156.17 52.063 Enugu 46.64 48.8 59.69 155.12 51.714 Bauchi 46.57 45.5 55.14 147.21 49.075 Kebbi 47.42 41.43 57.53 146.39 48.86 Jigawa 41.32 46.35 53.58 141.25 47.087 Yobe 44.58 39.28 52.54 136.4 45.478 Benue 27.21 40.78 60.7 128.69 42.99 Ondo 42.98 35.03 47.36 125.37 41.79

10 Gombe 44.67 36.71 43.38 124.77 41.5911 Oyo 42.28 36.41 44.73 123.42 41.1412 Kogi 43.05 32.2 47.26 122.5 40.8313 Taraba 19.13 45.15 55.78 120.07 40.0214 Lagos 41.89 32.54 45.61 120.04 40.0115 Kwara 41.59 32.59 44.18 118.37 39.4616 Delta 40.35 30.46 43.77 114.58 38.1917 Cross River 38.25 34.4 40.77 113.41 37.818 Kano 35.46 36.51 40.56 112.52 37.5119 Niger 36.46 32.65 41.37 110.48 36.8320 Anambra 37.04 31.04 42.16 110.24 36.7521 Osun 34.03 32.4 39.45 105.88 35.2922 Zamfara 22.31 33.17 43.06 98.54 32.8523 Akwa-Ibom 33.44 28.29 36.39 98.12 32.7124 Plateau 31.37 29.11 35.89 96.38 32.1325 Imo 30.3 26.32 37.75 94.38 31.4626 Abia 30.78 27.63 34.97 93.98 31.1327 Edo 16.44 36.64 40.05 90.13 30.0428 Nasarawa 26.87 25.4 33.31 85.58 28.5329 Adamawa 25.84 22.93 33.85 82.62 27.5430 Katsina 13.35 29.85 35.14 78.34 26.1131 Ebonyi 16.19 20.21 30.38 66.77 22.2632 Borno 19.01 19.32 18.54 56.87 18.96

States in which only two tests were administered33 Sokoto 27.77 43.94 71.72 35.8634 Ekiti 35.63 42.65 68.68 39.1435 Bayelsa 22.61 42.3 64.91 32.4636 Rivers 25.58 - 32.73 58.31 29.1637 Abuja 28.33 46.42 74.75 37.38

National Average 35.05 33.74 43.81 110.6 36.87Source: Nigeria Education Sector Analysis (Draft Report); 2003. Federal Ministry of Education

Table 2.1 above shows the test result from the 2003 assessment of learning achievement of primary 4 pupils all across Nigeria. The mean score in Literacy test was 35.05 with Kaduna state scoring the highest (51.63%) followed by Ogun state (50.8%) while Kastina and Borno


scored the lowest grades - 13.5% and 19.01% respectively. The National mean score in Numeracy test was 33.74% and Ogun state had the highest grade at 49.27% followed by Enugu state 48.8% while Ebonyi 20.21% and Borno state 19.32% had the least grades. In Life Skills test the National mean score was 43.81% while Benue 60.7% and Ogun state 60.3% had the highest grades while Ebonyi (30.38%) and Borno 18.54% had the lowest grades. Overall, Ogun state came first with mean grade of 53.46% followed by Kaduna state with 52. 06% mean score while Bayelsa state 29.16% and Rivers state 29.16% came last.

Focusing on Rivers state, and for primary 4 pupils, tests were only conducted in two learning domains- Literacy test with a mean score of 25.58% (29 th position among other states) and Life Skills test with a mean score of 32.73% (34th position in the federation) and an overall standing of 36th position among 36 states was dismal while primary six pupils were tested in Numeracy- 27.78% mean score (32nd position) and Life Skills-23.7% mean score (33rd). The total mean score for primary six pupils was 51.48% and mean grade of 25.74% which earned the state 32nd position.

MLA Survey in GhanaIn 2009, an MLA assessment project was undertaken in Ghana. Though enrolment rates in primary and junior secondary schools in Ghana were rising, as government policies in education were being implemented but assessments showed that the learning achievement of students was low.

The study was primarily carried out to examine the relationship between learning achievements and the level of human and physical resources allocated to schools (primary schools). There were also concerns about the varying levels of learning achievements among schools in different areas (districts). Though this was still in relation to how much the difference in allocation of resources explained the disparity in the level of learning outcomes between urban and rural areas.

The study was a district-by-district snapshot of the state of education in each of the 139 districts with information on learning achievements, infrastructure improvements and management characteristics by comparison to national and regional averages, Background documents on the Education Sector in Ghana were gathered and analysed and in order to find out the characteristics associated with high or low achievements, data from the NEA (The National Education Assessment) and the EMIS (The Education Management Information System) were merged.

The NEA tested learners in grade three and six in a national sample of schools in 2005 and 2007. The test was in English and Mathematics. The EMIS on the other hand refers to a collection of reliable information on available equipment, infrastructure and management characteristics of every primary school in Ghana. In essence, the study was to find out to


what extent the differences in the distribution of human and physical resources across schools explain the differences in learning outcomes.

Teachers, administrators, stakeholders (senior members of the Ministry of Education, officials in District Education Offices and head teachers of primary schools and teacher training colleges) were all interviewed to elicit information on their perception of the problems and successes of the education sector.

The following indicators across all districts were established to monitor the improvements of education quality- Achievements overtime on NEA and BECE tests, participation rates in terms of net school enrolment over time, as well as completion, dropout and repetition rates, the quality of school infrastructure in terms of drinking water, electricity, toilets and needed repairs, school management in terms of the frequency of school management committee meetings and visits from the circuit, supervisor, free meals provided and the portion of schools with a book to record teacher attendance and teaching and learning materials in terms of available writing places, library books and textbooks. Descriptive statistics of the achievement and resource variables were used to identify basic tendencies and further analyses were conducted using ordinary least squares regressions.

Two case study districts were chosen and the following findings were made:

For the first district, the low level of performance was attributed to: low level of teacher motivation, reluctance of some individual parents to provide basic needs for their children and low enthusiasm and commitment to learning on the part of pupils. For the second district, the low level of performance was attributed to: quality of teachers, low teacher morale and poverty of the parents in the district.Furthermore, the findings from the assessment revealed that demographic differences in resource allocation have been moderated to a commendable extent, but the demographic disparities in Learning Outcomes have not improved.

BotswanaA learning achievement survey sponsored by UNICEF and the government of Botswana was carried out in February 1999. It was carried out in accordance with the country’s Revised National Policy on Education which stipulated assessment and monitoring of progress in education. It was also to serve as a data collection process for the Education for All (EFA) 2000 assessment report. The study was to assess the achievement of Standard four pupils in four learning domains which included: Literacy in Setswana, Literacy in English, Numeracy and Life Skills.

The assessment was carried out by a selected group of officers from different departments of the Ministry of Education. Class teachers from primary schools also worked on the


project. Standardized survey instruments were constructed by the working group to ensure that they would adequately measure the competencies defined for Standard Four pupils in Botswana. A total of four tests and four questionnaires were developed. The tests were in Literacy in Setswana, Literacy in English, Numeracy, and Life Skills. The questionnaires were administered to Standard Four pupils, head teachers, teachers of Standard Four, and parents of the pupils. While tests were to measure the performance of pupils in terms of their mastery of defined learning competencies, the questionnaires were designed to collect information on factors that affect the learning achievement of pupils.

A sample was specified for data collection to represent the total school population in Botswana. It consisted for seventy primary schools across six regions. A total of 5, 460 (Female: 2, 726, Male: 2, 734) Standard Four pupils were surveyed. A total of 5, 540 parents responded as did 68 and 159 head teachers and Standard Four teachers, respectively.

The study found the performance of the pupils in the test domains to be generally weak. The percentage of competent pupils in each of the domains was as follows: Literacy in Setswana 39.6%, Literacy in English 21.9%, Numeracy 21.2%, and Life Skills 77.7%. Clearly, the pupils performed best in the Life Skills test.

The performance of pupils was also found to vary significantly across gender with female pupils outperforming their male counterparts. Variances in performance were also observed on regional basis.

The study identified a number of factors that affect the learning achievement of pupils. The factors cut across various areas including the school environment, school location, parental background, pre-primary education, etc. For example, pupils from homes with telephones, electricity and tap water were found to perform better than their counterparts without such amenities. The educational level of mothers was another significant factor identified. Pupils whose mothers have educational qualifications beyond primary education performed better relative to others whose mothers have lower levels of education. As regards the school environment, such factors as teacher absenteeism and the availability of electricity in the school were reported to affect pupil’s learning achievement; schools where teacher absenteeism was classified as ‘always’ performed poorly compared to schools where it was classified as ‘not at all.’ Schools in urban areas generally out-performed schools in semi-urban and rural areas in all the learning domains with the exception of life skills where semi-urban schools performed best.

The main conclusion of the study was that the pupils generally did not reach the established minimum competency levels .Only 39.6% of pupils achieved the competence level in Literacy in Setswana, 21.9% in Literacy in English and 21.2% in Numeracy. The highest was in the life skills learning domain where 77.7% of pupils achieved the competency level. The minimum competency levels were established in a one-day workshop that had 24 classroom


teachers in attendance as judges. It also concluded that multiple factors affect the learning achievements of pupils, including factors within and outside the school environment.

KenyaKenya participated in the Southern and Eastern Africa Consortium for Monitoring Education Quality (SACMEQ) III research project. The project was carried out between 2005 -2011 in some of the 15 member countries of the consortium. The project was focused on gathering information on the following: general schooling conditions, the achievements of Grade Six pupils and their teachers in reading and mathematics, and the knowledge that pupils and their teachers have about HIV/ AIDS.

The sample taken for the study included 193 primary schools from which 4, 436 pupils, 733 teachers and 193 head teachers were sampled. The SACMEQ Coordinating Centre prepared the survey instruments which consisted of tests and questionnaires. Specifically, the data collection instruments were: School Heads Booklets, School Information Forms, Teacher Booklets, Learner Booklets, and Learner Name Forms. Reading and mathematics tests were administered to pupils and teachers. Questionnaires were administered to head teachers, teachers and pupils.

The study found that majority of the teachers and pupils attained minimum competency levels in reading and mathematics. In the reading test, the national mean score of pupils was 543.1, while for teachers it was 792.1. In mathematics, the national mean score for pupils was 557.0 while for teachers it was 906.1. It is clear that teachers performed much better than the pupils. Amongst the pupils, performance was found to vary across various subgroups including gender and location. Urban areas out performed rural areas in both the reading and mathematics test with mean scores of 575.6 and 580.0 respectively. Scores in the rural areas were 525.6 for the reading test and 544.5 for the mathematics test. Boys did better than girls in both the reading and mathematics tests with means scores of 544.1 and 567.6respectively, compared to the 542.1 and 546.0 scored by the girls.

For the HIV/ AIDS knowledge test, only 39.2 % of pupils reached the minimum level and only 6.8% reached the desired level. This also varied across locations with pupils from the urban area scoring higher than those from the rural areas.

The background information gathered from pupils, teachers, and school heads via the administration of questionnaires was extensive and revealing. From the pupils, data was gathered in such areas as feeding patterns, language spoken at home, parental education, living conditions of pupils, the number of books at home, preschool attendance, travel distance to school, homework assistance, amongst others. From the teachers, data gathered included: level of education, availability and frequency of in-service training, teacher time allocation, and time spent on lesson preparation, frequency and contents of communication with parents, availability of teaching aids, etc. Information supplied by the school heads


included: their professional characteristics, school resources, pupil behavioural problems, teacher behavioural problems, frequency of school inspections, etc.

Multilevel analysis was carried out using STATA version 11 (Stata Corp, 2009) to investigate the pupil-level and school-level factors that affect the learning achievement of the pupils in the reading and mathematics tests. About 70 predictor variables for both Reading and Mathematics which were significant at p=.05 were selected using multiple linear regression. The following conclusions were derived from the analysis:

Pupils who are absent from school perform poorly in Reading Pupils who speak English at home do well in Reading. Pupils staying with another family perform poorly in Reading. Pupils from families with many siblings perform poorly Schools with pupils who borrow books from their school libraries achieved better in

Reading Pupils who use computers at home achieved higher scores in Mathematics. Pupils who were absent from school to care for their siblings had low achievement in

Mathematics. Pupils who stay alone at home perform poorly in Mathematics Younger pupils perform better in Mathematics compared to their older counterparts. Pupils in schools with dilapidated buildings performed less well in Mathematics.

Some of the policy suggestions offered by the study were that education stakeholders should continue their efforts to eliminate absenteeism; caregivers should encourage children to speak English both at home and at school because it is the medium of instruction at grade 6. The home background of the pupil was also emphasized as critical to success in school. Suggestions were directed at parents, caregivers and other significant family-related institutions to take up the responsibility for quality education. It was also recommended that more effort should be put into improving the learning environment through the provision of learning materials, facilities, and improving the quality of teaching.

Regional Monitoring Learning Achievement (MLA) Survey 1999In developing countries in general, there was not a single regional survey, which measured improvement in learning outcomes prior to WCEA Jomtien, in 1990. The 1999 Regional Monitoring Learning Achievement (MLA) survey, of 9 African countries which was especially commissioned for Indicator 15 of the Education for All (EFA) 2000 Assessment Survey, was the first one of its kind in Africa. The 1999 African MLA survey assessed learner performance from the viewpoint of what is taught and learnt in and out-of schools. The detailed results of learning achievement are presented in the various learning domains of literacy, numeracy, and life skills, respectively below.


Learning Achievement profiles of Selected MLA African countries by learning domains for Grade 4 pupilTable 2.2

CountriesLiteracy Numeracy Life Skills

Voca

bula

ry

Com

preh

ensi

on

Gra

mm

ar

Writi

ng

Num

ber

Mea

sure

men

t

Geo

met

ry

Hea

lth

Civi

l &

Envi

ronm

ent

Scie

nce

&

Tech

nolo

gy

Botswana 70.0 53.0 49.0 27.0 53.0 39.0 54.0 54.0 69.0 49.0

Madagascar 53.0 72.0 48.0 56.0 49.0 32.0 43.0 80.0 72.0 76.0

Malawi 54.0 37.0 35.0 23.0 42.0 43.0 47.0 78.0 80.0 70.0

Mali 85.0 57.0 43.5 45.3 34.1 49.9 48.3 56.2 58.1 55.6

Mauritius 89.0 68.0 60.0 47.8 61.5 52.1 61.7 67.2 67.2 56.7

Niger 80.6 50.5 43.2 32.7 35.9 42.6 45.8 46.2 48.7 48.5

Senegal 75.2 48.4 48.7 36.1 28.9 39.4 38.4 47.6 48.4 40.6

Uganda 80.0 62.0 59.0 47.0 48.7 47.6 52.6 68.4 66.3 64.0

Zambia 72.0 45.0 49.0 28.0 36.0 35.0 37.0 52.0 52.0 48.0

Source: Chinapah et al. 2,000a, p.21 (adjusted).

From table 2.2 above, Literacy test was broken into four major domains which include Vocabulary, Comprehension, Grammar and Writing while Numeracy test was divided into Number, Measurement and Geometry, and Life skills was divided into three domains including Health, Civic and Environment and Science and Technology.Across board, Literacy test has the highest grade and Vocabulary component of Literacy test recorded the highest grade. Overall, performance in Numeracy was poor with the lowest score in Measurement.Mauritius has the highest grade (89%) in Vocabulary and Grammar (60%) while Madagascar has the lowest grade in Vocabulary with 53% but has the highest grade in Comprehension (72%). Malawi has the lowest grade in comprehension (37%). Mauritius again scored highest grades in all Numeracy components while Madagascar and Malawi in Life Skills test were the two top performers.


Percentage of Grade 4 pupils who attained the Minimum (MML) and Desirable (DML) levels of mastery Table 2.3

CountryCombined Literacy Numeracy Life Skills

MML DML MML DML MML DML MML DMLBotswana 57.8 8.7 46.2 6.0 55.4 5.4 71.8 14.9

Madagascar

66.1 11.7 56.9 20.6 34.4 5.6 97.3 60.3

Malawi 54.9 3.0 15.3 1.4 30.7 1.4 95.4 69.4Mali 54.9 7.3 50.4 13.1 37.9 6.2 69.8 23.7

Mauritius 70.3 24.1 77.6 35.4 70.3 26.4 71.6 32.4Niger 25.6 2.0 39.3 3.6 15.3 5.7 44.9 7.0

Senegal 31.2 2.0 45.6 6.7 22.9 3.0 36.3 7.0Uganda 54.4 14.4 64.3 23.3 41.9 10.2 78.8 51.1Zambia 31.9 5.6 37.8 7.3 19.9 4.4 49.0 26.1

Source: Chinapah et al. 2,000a, p.21 (adjusted).

From table 2.3, overall Mauritius has the highest percentage of pupils who have attained MML and Niger has the lowest, when the test scores are broken into different domains, Mauritius has the highest percentage of pupils who have attained MML in Literacy and Numeracy while Madagascar has the highest percentage of pupils who have attained MML in Life Skills. Niger has the lowest percentage of pupils who have attained MML in the entire learning domain except Life Skills where Senegal has the lowest percentage of pupils who have attained MML.

Though the findings on factors that affect or determine learning outcomes varied among and within the nine surveyed countries, however, some factors are common to all. These factors include- content of curriculum, teaching and working environment, school and home learning environment.

Lessons from Previous StudiesThere are key concepts that resonate from previous learning achievement surveys, some of such concepts are highlighted below:

It is important to not judge the success of the education system on the basis of increased enrolment or infrastructural development because education is not simply about more students or well-built classrooms. The success or failure of an education system can be measured basically by the quality of learning that actually goes on and the mastery of knowledge and skills that school goers achieve.

Most of the reviewed studies tested pupils in the following learning domains: literacy, numeracy and life skills, according to what has been established as the goal of primary education.

Learning goes beyond the school environment. The home environment largely affects the learning achievements of pupils and must not be neglected. Parental


education and learning support at home are vital to learners. This necessitates that more attention be paid to adult education as the learning achievement of the adult populace affects that of young learners.

Teacher training as well as teachers’ working conditions require special attention because the teacher is perhaps the most important school resource.

Greater attention should be given to the even distribution of education resources in both urban and rural areas so as to reduce as much as possible the locational discrepancies in learning achievement.

The findings of previous MLA surveys as highlighted above echo the globally acknowledged fact that ‘Education for all is the responsibility of all.’ It follows therefore that achieving the respective ends for which we have education systems has to be approached holistically and inclusively. Everyone, ranging from education policy makers, to parents, school staff and the learners, has a responsibility.

Chapter Three

General Description and Characteristics of Survey RespondentsThis chapter details background information on factors that can affect the learning achievement of pupils/ students in Rivers State. The information generally concerns the socioeconomic background of pupils/ students, their school environments, school facilities, the competencies of teachers, amongst others. The information was harnessed via questionnaires administered on pupils/ students, their parents, teachers and head teachers.

3.1 Background Information Supplied by the PupilsThe information supplied by pupils indicating their general characteristics as well as factors that can affect their performance is presented as follows:

Distribution of Sampled Pupils/ Students by Sex

Pupils (Primary Four Pupils)The gender representation of sampled pupils was fairly equal across all the LGAs. Where there are differences such as in Eleme, Ahoada West, Emohua, Opobo/Nkoro, Ahoada East, Andoni, Ogu/Bolo, ASALGA, it is negligible. This is shown below:

Fig 1


ELEME

AHOADA WES

T

EMOHUA

OPOBO/NKORO

AHOADA EAST

ANDONI

PORT HARCOURT

GOKANA

AKUKU-TORU

ETCHE

KHANA

IKWER

RE

OKRIKA TAI

ABUA/ODUAL

OYIGBO

OMUMA

ONELGA

BONNY

OGU/BOLO

ASALG

A0

20

40

60

80

100

Distribution of Sampled Pupils by Sex Across the LGAs

Male Female

LGAs

Perc

enta

ge

Students (JSS Two Students)However, some level of inequality was observed among the JSS two respondents. In Obio/ Akpor LGA there were far more female respondents than males. The reverse occurred in Ogu/ Bolo.

Fig 2

ABUA/ODUA

AHOADA EAST

AHOADA WES

T

AKUKU-TORU

ANDONI

ASARI-T

ORU

BONNY

DEGEM

A

ELEM

E

EMOHUA

ETCHE

GOKANA

KHANA

OBIO/A

KPOR

OGU/BOLO

OKRIKA

OMUM

A

ONNE

OPOBO/NKORO

OYIGBO

PORT-HARCOURT

TAI

01020304050607080

Distribution of Sampled Students by Sex Across the LGAs

MaleFemale

LGAs

Pe

rce

nta

ge


Age Distribution of Sampled Pupils/ StudentsMajority of the respondents in primary four fall within the age range of 9 to 12, while the respondents in JSS2 fall within the range of ages 13 to 16. Generally, 9 year-olds and 13 year-olds constitute the largest age groups amongst the sampled pupils and students making up to 30 and 33 percent respectively. Ages 10 and 14 also constitute more than 20 percent each of pupils and students in the sampled population. This is illustrated in the chart below:

Fig 3

7 8 9 10 11 12 13 14 15 16 17 18 19 200

5

10

15

20

25

30

35

Distribution of Sampled Pupils/ Students by Age

Pupils Students

Age

Pe

rce

nta

ge

Pre-Primary Education Early childhood development and Pre-primary education is widely recognized as having a significant impact on the performance of children in basic educational programmes by developing the cognitive ability of the pupils before proceeding into Primary education. 36% of our primary four respondents had no pre-primary education while 64% had some form of pre-primary education. This shows that a majority of the surveyed pupils had pre-primary education. See the diagram below:

Fig 4

64%

36%

Distribution of Sampled Pupils by Pre-Primary Educa-tion

Had

Had None


Feeding PatternHealthy and balanced nutrition affects a child’ general wellbeing. It plays a major role in the child’s ability to comprehend what is being taught. Hungry children are less likely to concentrate in class and as a result might perform poorly. From the pupils surveyed, 37% usually have no lunch, 19% have no breakfast and 5% have neither lunch nor breakfast. Only 39% of respondents were well fed. See the chart below:

Fig 5

Well Fed No Breakfast No Lunch None0

5

10

15

20

25

30

35

40

45

39%

19%

37%

5%

Feeding Pattern of Sampled Pupils

Distance to SchoolThe charts below show the time it takes sampled pupils/ students to get to school from their homes in each LGA. In both primary and secondary schools across most of the LGAs, a majority of the students report a travel time of between 1-10 minutes. However, majority of Pupils in Ogu/Bolo LGA report a travel time of between 11-20 minutes as do most of the sampled students in Bonny. See the charts below:

PupilsFig 6


ABUA/ODUAL

AHOADA EAST

AHOADA WES

T

AKUKU-TORU

ANDONI

ASALG

A

BONNY

ELEM

E

EMOHUA

ETCHE

GOKANA

IKWER

RE

KHANA

OBIO/A

KPOR

OGU/BOLO

OKRIKA

OMUM

A

ONELGA

OPOBO/NKORO

OYIGBO

PORT HARCOURT

TAI

01020304050607080

Travel Time to School (Pupils) 1-10mins 11-20mins 21-30minms 31-40mins 41mins & Above

LGAs

Perc

enta

ge

Students

Fig 7

ABUA/ODUAL

AHOADA EAST

AHOADA WES

T

AKUKU-TORU

ANDONI

ASALG

A

BONNY

DEGEM

AELE

ME

EMOHUA

ETCHE

GOKANA

KHANA

OBIO/A

KPOR

OGU/BOLO

OKRIKA

OMUMA

ONELGA

OPOBO/NKORO

PORT HARCOURT TA

I0

1020304050607080

Travel Time to School (Students)1-10mins 11-20mins 21-30mins 30-40mins 41mins & Above

LGAs

Perc

enta

ge

Means of Transportation to SchoolThe mode of transportation to school reflects the overall convenience of pupils/ students. Pupils/ students who walk long distances to school would most likely be fatigued on getting to school. Such fatigue in turn affects their comprehension and performance. Walking long distances to school unsupervised could expose them to truancy and other dangers. Most (at least 7 out of 10) of the sampled pupils/ students travel to school by foot. This is understandable given the travel time of between 1 to 10 minutes

Fig 8


80%

6%

8%

4%

2%

Means of Transport to School (Pupils)

Foot

Public bus

Okada

Parent's car

Others

Fig 9

Foot; 75%

Public Transport;

8%

Okada; 13%

Parent's Car; 4%

Means of Transport to School (Students)

FootPublic TransportOkadaParent's Car

Pupils’/ Students' Attitude to SchoolingHere we consider the characteristics of students and pupils in relation to certain push factors (endogenous factors – within the school environment). As illustrated above, the major turn off to pupils and students is the fear of bullies (3 in 10). Lack of comprehension (another 3 in 10) of what is being taught also registers a high percentage. Pockets of respondents also claim not to like their teachers, and are afraid of punitive measures employed within the school. Collectively, all these factors could affect learning achievement. This is illustrated below:

Fig 10


I don't

Like m

y Tea

cher

s

Lack

of C

omprehen

sion

Fear

of Punish

ment

I hav

e no fr

iend in

school

Fear

of Bullie

s0%5%

10%15%20%25%30%35%

14%

29%

14% 13%

30%

Attitude of Pupils towards Schooling

Attitude

Perc

enta

ge

Fig 11

I don't L

ike m

y Tea

chers

Lack o

f Compreh

ensio

n

Fear

of Punish

ment

I hav

e no fr

iend in

School

Fear

of Bullie

s0%5%

10%15%20%25%30%35%40%45%

6%

29%

16% 11%

39%

Attitude of Students towards Schooling

Attitude

Perc

enta

ge

Pupil/ Student AbsenteeismThe respondents revealed that illness is the major causal factor for absenteeism. About a quarter of respondents stated commercial activities as the reason for their being absent. House chores, the availability of transportation fare and the condition of the weather, are other reasons highlighted by pupils for being absent from school. Special health care provisions or fee-waiver for health services for pupils as well as the provision of school buses are measures that can be taken to drastically reduce pupil’s absenteeism. Child labour laws need to be enforced to prevent pupils from being forced to engage in commercial activities. See chart below:

Fig 1236| P a g e A r b i t r a g e C o n s u l t L t d E m a i l : a r b i t r a g e c o n s u l t @ g m a i l . c o m

+ 2 3 4 ( 0 ) 8 0 2 3 3 2 3 3 7 8 o r + 2 3 4 ( 0 ) 8 0 7 2 5 7 8 1 4 5

Illness Transport Fare House Chores Commercial activities Weather0%

5%

10%

15%

20%

25%

30%

35%

40% 38%

15%

19%

25%

3%

Reasons for Pupil Absenteeism

Reasons

Pe

rce

nta

ge

From the JSS 2 respondents, illness ranked highest as the major reason for absenteeism. Close to 60% of respondents identified ill health as their reason for being absent from school. Transport fare and house chores were also highlighted as reasons for absenteeism. As stated earlier, adequate health care services and provision of school buses to convey students to and from school are measures that may reduce absenteeism. See Chart below:

Fig 13

Illness Transport Fare House Chores Weather Others0%

10%

20%

30%

40%

50%

60%

70%

59%

19%

8% 7% 7%

Reasons for Student Absenteeism

Reasons

Pe

rce

nta

ge

Homework AssistanceThe chart below shows that a majority of sampled pupils have assistance at home as they work on their home assignments. Such assistance could help pupils get clarity in areas they find difficult at school. Pupils with strong academic assistance at home are likely to do better than those without such assistance.

Fig 14


Have Have None0%

10%

20%

30%

40%

50%

60%

70%

80% 75%

25%

Distribution of Pupils by Availability of Assistance in doing Homework

After School ActivitiesLearning does not end in the four walls of a classroom. A child’s activities after school hours could help to either enforce or jeopardise the child’s understanding of what was taught during school hours. The charts below show that majority of pupils/ students who responded attend extramural classes after school. Less than 30% are engaged in commercial activities. House chores also account for a major proportion of after school activities for both pupils and students alike. Less than 9% watch television after school. It is important to note that pupils/ students involved in commercial activities tend to be distracted from their educational programmes. Enforcement of child labour laws can help reduce the number of children involved in commercial activities.

Fig 15

House Chores Commercial Activities Watching Television Extra Mural Class0

5

10

15

20

25

30

35

40

29% 29%

7%

36%

After School Activities (Pupils)

Activities

Perc

enta

ge

Fig 16


House Chores Commercial activities Watching Television Extramural Class0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

26%28%

5%

41%

After School Activities (Students)

Activities


3.2 Background Information Supplied by the ParentsThe information harnessed from parents as regards factors that affect the learning achievements of their children is stated as follows:

Gender DistributionOut of the 13,650 parents who responded, about 57% were females while about 43% were males. On the average, more females responded in most local government areas than males. Eleme recorded the highest level of female respondents while Abua/Odua recorded the highest level of male respondents.

Fig 17

ABUA/ODUAL

AHOADA/EAST

AHOADA/WES

T

AKUKU-TORU

ANDONI

ASALG

A

BONNY

DEGEM

A

ELEM

E

EMOHUA

ETCHE

GOKANA

IKWER

RE

KHANA

OBIO/A

KPOR

OKRIKA

OMUM

A

ONELGA

OPOBO/NKORO

PH TAI

0

10

20

30

40

50

60

70

80

90

Gender Distribution of Sampled Parents across the LGAs

MaleFemale

LGAs

Perc

enta

ge

Relationship of Pupils/ Students with Respondents to Parent QuestionnaireThe chart below shows the relationship between sampled parents/ guardians with the surveyed pupils/ students; majority of the parents who responded are the actual biological or foster parents of the pupils/ students.

Fig 18

Father Mother Guardian Relative0%

10%

20%

30%

40%

50%

60% 55%

25%

14%

7%

Distribution of Sampled Parents by Relationship to the surveyed Pupils/ Students


Age Distribution of the RespondentsThe chart below shows the age distribution of sampled parents. About 74% of sampled parents were aged between 31 and 50 years old. Only 14% were above 50 years old.

Fig 19

20-30 31-40 41-50 Above 500%

5%

10%

15%

20%

25%

30%

35%

40%

45%

12%

34%

40%

14%

Age Distribution of Sampled Parents

Years

Parents Expenditure on School related ItemsThe Rivers State government has provided free education for pupils/ students at primary and secondary levels. However, respondents reported some costs incurred from schooling. The highest expenditure was attributed to school uniforms, followed by transport fare, textbooks, ‘school fees’ or levies and classroom desks. School fees and classroom desks are particularly disturbing considering huge government investment in school infrastructure.

Fig 20

School Fees Transport Fare Textbooks Uniform Classroom Desks0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

13%

23%

18%

39%

7%

School Related Items on Which Parents Expend

Items


Parents’ Highest Educational LevelsA majority of the parents who responded have secondary school certificates as their highest educational qualification. This was the case in 10 LGAs (Abua/ Odua, Ahoada East, Ahoada West, Akuku – Toru, Asari Toru, Degema, Emohua, Gokana, Ikwerre, Opbobo/ Nkoro).

Fig 21

ABUA/ODUAL

AHOADA EAST

AHOADA WES

T

AKUKU-TORU

ANDONI

ASALG

A

BONNY

DEGEM

A

ELEM

E

EMOHUA

ETCHE

GOKANA

IKW

ERRE

KHANA

OBIO/A

KPOR

OKRIKA

OMUM

A

ONELGA

OPOBO/NKORO

PORT HARCOURT

TAI

0

10

20

30

40

50

60

Highest Educational Levels of Sampled Parents

0-6 years 7-12 years13 years-Above

Participation in School ActivitiesParticipation in school activities is an indicator of parents’ interests in the educational achievements of their children. Parents who are more committed to their children’s education tend to spur them to achieve more academically and this could have positive impacts on the children’s learning achievements. The chart below shows the rate of participation in school activities by sampled parents, indicating that majority of the parents participate, although, only 41% of the respondents ‘always’ participate in school activities.

Fig 22

Always Sometimes Never0

5

10

15

20

25

30

35

40

45

50

41%

46%

13%

Distribution of Sampled Parents by Participa-tion in School Activities

Pe

rce

nta

ge


Attitude towards EducationAmong the sampled parents, only 41% feel that education is the best investment; this is a worrying statistic as the attitude of parents towards education affects a child’s learning achievement. Where parents have poor attitudes towards education, children tend not to get necessary home support and guidance for their school work. The sampled parents mostly argue against the notion that education of male children is more important than that of female children. See the chart below:

Fig 23

Education is the best Investment Female Children should be educated

Male children should be educated more than female

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Parents' Attitude to Education


3.3 Background Information Supplied by TeachersTeachers and students are the two basic elements of any educational institution. It is the teachers who have the most influence on the students’ academic performance and the nature of this influence depends on their quality and other factors.

The information contained in this section is based on the feedback received from our respondents. We present in figures and in words, information such as the teachers’ qualifications, professional attitudes and general mindset.

Highest Educational LevelsChildren with more experienced teachers who are also frequently assessed tend to perform better. Here, teacher quality is indicated by the teacher’s educational qualification. From the chart below, a majority of primary school teachers who responded have at least one form of tertiary education or another. Only 3% have SSCE qualification as their highest. The trend is similar for secondary schools.

Fig 24

SSCE OND/NCE HND B.Ed BSc MSc0%

10%

20%

30%

40%

50%

60%

3%

57%

1%

29%

9%

1%

Highest Educational Levels (Primary School Teachers)


Fig 25

SSCE OND/NCE HND B.Ed. B.Sc Post-graduate 0%

10%

20%

30%

40%

50%

60%

2%

12%

4%

55%

21%

6%

Highest Educational Levels (Secondary School Teachers)

Teaching ExperienceMore experienced teachers tend to deliver better teaching and this in turn makes for better pupil/ student academic performance. As shown in the chart below, majority of the teachers that responded had above 12 years of teaching experience. This was the case for both primary and secondary schools.

Fig 26

1-3yrs 4-7yrs 8-12yrs Above 12yrs0%

10%

20%

30%

40%

50%

60%

70%

80%

Distributon of Sampled Teachers by Years of Teaching Experience

Primary TeachersSecondary Teachers


Teacher Absenteeism The respondents say they sometimes miss school. Their reasons for such absence are presented in the charts below. The predominant reason for absence by primary school teachers is illness. 23% of respondents claim they missed school to attend training programmes. The trend is similar for secondary schools.

Fig 27

Illness Maternity Training Weather Transportation Problem

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50% 47%

11%

23%

13%

6%

Reasons for Teacher Absenteeism (Primary Schools)

Fig 28

Illness Maternity Training Weather Transportation Problem

0%

10%

20%

30%

40%

50%

60%

51%

7%

21%

10% 11%

Reasons for Teacher Absenteeism (Secondary Schools)

Distance to SchoolPrimary school teachers mostly (65%) reported that it takes them less than 30 minutes to get to school. But only 48% of secondary school teachers reported the same travel time. The travel time distributions are shown in the chart below:


Fig 29

1-10mins 11-20mins 21-30 31-40 Above 41mins0%

5%

10%

15%

20%

25%

30%

35%

40%

21%

30%

14%11%

24%

13%

20%

15% 14%

38%Teachers' Travel Time to School

Primary TeachersSecondary Teachers

Interest of Teachers in TeachingMost of the teachers who responded are not willing to change their careers (See the chart below). Of the less than 40% of teachers who indicated a desire to change careers, improved benefits was the most prevalent reason stated. Other reasons stated were improved working conditions and career development. The teaching profession should be made more rewarding so as to retain the current workforce and attract new teachers when needed.

Fig 30

Yes No0%

10%

20%

30%

40%

50%

60%

70%

80%

Teachers' Desire to Change Career

PrimarySecondary


Teacher TrainingTeacher training is important to pupil/ student learning achievement. Through frequent training, teachers become better skilled at impacting knowledge. Most of the teachers surveyed had attended up-skilling programmes. However, only 25% reported to have attended up-skilling programmes more than three times throughout their careers. It is important to institute frequent training programmes to improve the skill level of teachers.

Fig 31

Had Had None0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Attendance of Up-Skilling Trainings

Primary

Secondary


3.4 Background Information Supplied by School HeadsInformation obtained from the head teachers and principals sampled are presented below:

Highest Educational Levels Most of the sampled school heads have undergraduate degrees as their highest educational qualification. 6% of head teachers and 15% of principals have post-graduate degrees.

Fig 32

Head Teacher Principal0%

10%

20%

30%

40%

50%

60%

24%

2%0.01

33%31%

36%

52%

6%

15%

Highest Educational Levels of School Heads

NCEHNDB.Ed.B.ScAbove

Rate of Teacher AbsenteeismThe school heads gave the rate of teacher absenteeism as presented in the charts below. It is established that teachers are sometimes absent from school. However, less than 10% of teachers in both primary and secondary schools are always absent. It appears that absenteeism is mostly a rare occurrence or it may be head teachers are frugal with the truth.

Fig 33

Primary School Secondary School0%

10%

20%

30%

40%

50%

60%

70%

80%

9% 8%

67% 67%

10%17%14%

8%

Rate of Teacher Absenteeism

Always SeldomAt the beginning of a new Term At the end of theTerm


Factors Contributing to Poor Performance of Pupils/ StudentsThe sampled school heads identified socioeconomic status as being largely responsible for poor academic performance among pupils/ students. Generally, school related factors (automatic promotion, overloaded curriculum, lack of remedial teaching, lack of teaching, and language of instruction) account for a combined 41% of the responses, parent/ student related factors (parental indifference, student’s mental ability) account for a combined 27%, while socioeconomic status account for 32% as a single most important factor. See the chart below:

Fig 34

Automatic Promotion

Overloaded Curric

ulum

Parental

Indiffrence

Student's

Mental Ability

Socioeco

nomic Stat

us of th

e Pupils

Lack o

f Rem

edial Tea

ching

Lack o

f Teach

ing Skill

s

Language

of Instr

uction

0%5%

10%15%20%25%30%35%

11%8%

12%15%

32%

7% 8% 7%

Factors Contributing to Poor Performance of Pupils/ Students


Chapter Four

Test PerformanceThis chapter reports the performance of the pupils/students in all the learning domains across the local government areas in Rivers State.

Primary School Pupils (Primary 4)Table 4.1

S/N LGA No. of Primary Schools Literacy Numeracy Life Skills1 ABUA/ODUA 49 67.09 57.47 75.162 AHOADA EAST 38 55.72 39.16 66.373 AHOADA WEST 60 47.36 47.31 54.964 AKUKU-TORU 58 60.79 46.63 70.595 ANDONI 22 48.73 48.04 78.276 ASARI-TORU 27 63.92 38.40 70.307 BONNY 21 62.85 67.29 70.208 DEGEMA 24 58.89 35.40 72.029 ELEME 22 56.12 57.80 71.2910 EMOHUA 51 53.50 46.23 69.2711 ETCHE 80 67.00 46.00 73.0012 GOKANA 39 58.64 49.08 54.8013 IKWERRE 39 63.42 57.08 76.4314 KHANA 79 57.44 48.41 69.5515 OBIO/AKPOR 43 63.15 43.83 82.5616 OGU/BOLO 15 68.29 61.31 71.6317 OKRIKA 34 61.04 54.30 77.5018 OMUMA 21 71.77 51.65 65.0819 ONE 71 60.59 49.18 73.6520 OPOBO/NKORO 17 62.83 55.94 70.8921 OYIGBO 21 71.05 50.51 72.6622 PORT-

HARCOURT50 61.20 49.16 72.13

23 TAI 35 63.39 42.18 73.19TOTAL 916

Literacy Numeracy Life SkillsMean Score 61.08 49.67 70.94Minimum Score 47.36 35.40 54.80Maximum Score 71.77 67.29 82.56

Source: MLA Administered tests 2013


The chart below highlights the test performance of pupils in all the learning domains in the 23 LGAs. Generally, performance was best in the Life Skills test and lowest in the Numeracy test. 916 public primary schools were surveyed, out of which 545 primary schools (or 59.5%) across 15 LGAs performed above the state mean score in the literacy learning domain, while 517 primary schools (or 56.4%) across 11 LGAs underperformed in the Numeracy test. The highest performance level was recorded in life skills where 754 primary schools (or 82.3%) across 19 LGAs performed above the state mean score. Pupils showed a keen interest in Life skills compared to Numeracy and Literacy. This was reflected in the overall good performance in Life skills relative to the other two learning domains. The results show that less than 6 in 10 primary school pupils failed to perform above the average score in numeracy tests, while about 6 in 10 performed above the state average in literacy.

Fig 1

ABUA/ODUA

AHOADA EAST

AHOADA WEST

AKUKU-TORU

ANDONI

ASARI-T

ORUBONNY

DEGEM

AELE

ME

EMOHUA

ETCHE

GOKANA

IKWERRE

KHANA

OBIO/AKPOR

OGU/BOLO

OKRIKA

OMUMAONE

OPOBO/NKORO

OYIGBO

PORT-HARCOURT TA

I0

10

20

30

40

50

60

70

80

90

Test Performance in all the Learning Domains (Primary Four pupils)

LITERACYNUMERACYLIFE SKILLS


Pupils Performance in Literacy TestThe performance of pupils in the Literacy test is presented in the chart below. Based on the state mean score in the literacy domain, which is 61.08, 559 primary schools across 15 LGAs performed above the state mean score, while 335 primary schools in 8 LGAs performed below the state mean score. This is more than a third of primary schools in the state. Notably, the schools that scored the highest are located in the rural areas.

Fig 2

ABUA/ODUA

AHOADA EAST

AHOADA WEST

AKUKU-TORUANDONI

ASARI-TORUBONNY

DEGEMAELEM

E

EMOHUAETCHE

GOKANAIKWERRE

KHANA

OBIO/AKPOR

OGU/BOLOOKRIKAOMUMA ONE

OPOBO/NKOROOYIGBO

PORT-HARCOURT

TAI0

1020304050607080

Performance in Literacy Test (Pupils)

LITERACY STATE MEAN SCORE


Pupils Performance in Numeracy TestThe chart below displays performance of pupils in the numeracy test across the LGAs. A low level of performance was recorded in this learning domain where 517 public primary schools in 11 LGAs performed below the state mean score of 49.67 while 399 public primary schools (or 43.5%) performed above the state mean score. This means that more than half of public primary schools in the state performed poorly – below the state average score in numeracy. The scores indicate that pupils performed poorly in this learning domain and this was observed across all the LGAs.

Fig 3

ABUA/ODUA

AHOADA EAST

AHOADA WEST

AKUKU-TORUANDONI

ASARI-TORU

BONNY

DEGEMAELE

ME

EMOHUA

ETCHE

GOKANA

IKWERREKHANA

OBIO/AKPOR

OGU/BOLOOKRIKA

OMUMA ONE

OPOBO/NKOROOYIG

BO

PORT-HARCOURT

TAI0

10

20

3040

50

60

7080

Performance in Numeracy Test

NUMERACY STATE MEAN SCORES


Pupils Performance in Life Skills TestThe diagram below shows the performance of pupils in the life skills test. Pupil’s performance in life skills learning domain appears very exceptional relative to other learning domains. This was the case in all the LGAs. However 158 primary schools in 4 LGAs performed below the state mean score. This is less than 20% of public primary schools. Most of the LGAs achieved the State mean score (70.93).

Fig 4

ABUA/ODUA

AHOADA EAST

AHOADA WEST

AKUKU-TORUANDONI

ASARI-TORU

BONNY

DEGEMAELE

ME

EMOHUA

ETCHE

GOKANA

IKWERREKHANA

OBIO/AKPOR

OGU/BOLOOKRIKA

OMUMA ONE

OPOBO/NKOROOYIG

BO

PORT-HARCOURT TAI

0102030405060708090

Performance in Life Skills Test(Pupils)

LIFE SKILLS STATE MEAN SCORES


Secondary School Students (JSS2) Table 4.2

Average ScoresS/N LGA No. of Secondary

SchoolsEnglish Mathematics General

Science1 ABUA/ODUA 31 55.87 40.01 72.132 AHOADA EAST 19 38.80 41.55 65.463 AHOADA WEST 11 66.84 39.00 55.524 AKUKU-TORU 10 44.60 61.19 49.325 ANDONI 6 29.50 49.13 46.726 ASARI-TORU 10 56.98 43.00 65.707 BONNY 3 53.64 64.00 30.538 DEGEMA 6 38.28 32.86 65.349 ELEME 5 51.52 48.49 72.3610 EMOHUA 21 52.27 47.57 64.7411 ETCHE 44 47.82 43.19 65.3012 GOKANA 9 49.11 42.56 47.3313 IKWERRE 14 45.46 48.90 36.0014 KHANA 22 36.78 42.84 52.3315 OBIO/AKPOR 19 54.05 36.94 72.7416 OGU/BOLO 19 58.25 56.16 70.5617 OKRIKA 3 55.36 59.40 73.9818 OMUMA 6 47.08 37.22 39.2919 ONE 4 52.32 47.83 66.5920 OPOBO/NKORO 5 39.81 37.84 45.6621 OYIGBO 2 50.60 40.92 60.7222 PORT-

HARCOURT11 72.86 35.87 67.01

23 TAI 13 46.98 43.49 58.22TOTAL 293

English Mathematics General Science

Mean Score 49.77 45.22 58.43Maximum Score 72.86 64.00 73.98Minimum Score 29.50 32.86 30.53

Source: MLA Administered tests 2013


The general performance of JSS two students sampled is presented in the chart below (Fig 5). It shows their performance in the three learning domains (English, Mathematics, and General Science) in which they were tested. It was observed that students performed best in General science and lowest in mathematics. The test scores indicate that students did better in General science and English language compared to mathematics. This was observed across all 293 public secondary schools that were surveyed in all the LGAs. 143 secondary schools in 10 LGAs performed below the state mean score in the English learning domain, while 206 secondary schools in 14 LGAs underperformed in mathematics. The highest performance level was recorded in the general science learning domain, however 84 public secondary schools in 9 LGAs performed below the state mean score in this learning domain. The highest performances were recorded in urban areas. Performance analysis across LGAs in the learning domains tells us the direction of extra efforts by policy makers to improve students’ learning competence. Which LGA(s) need extra backstopping support from policy makers? The starting point will be those LGAs with consistently below average performance in each of the three learning domains. There are four critical cases – Gokana, Khana, Omuma and Opobo/ Nkoro – needing urgent policymakers’ attention. Further investigation may be necessary to understand the root of such poor performance. There are other 8 LGAs performing below state average in at least two of the learning domains which need to be helped to improve performance in their weak learning domains.

Fig 5

ABUA/ODUA

AHOADA WEST

ANDONI

BONNYELE

MEETC

HE

IKWERRE

OBIO/AKPOROKRIKA ONE

OYIGBO TA

I0

10

20

30

40

50

60

70

80

Test Performance in all the Learning Domains (JSS Two Students)

ENGLISH MATHEMATICS GENERAL SCIENCE


Students Performance in English TestThe performance of students in the English Language test is presented in the chart below. Based on the state mean score in the literacy domain, which is 49.77, 143 public secondary schools in 10 LGAs performed below the state mean score.

Fig 6

ABUA/ODUA

AHOADA EASTAHOADA ...

AKUKU-TORUANDONI

ASARI-TORUBONNY

DEGEMAELEM

E

EMOHUAETCHE

GOKANAIKWERRE

KHANA

OBIO/AKPOR

OGU/BOLOOKRIKAOMUMA ONE

OPOBO/N...OYIGBO

PORT-HARC...TAI

0

10

20

30

40

50

60

70

80

Performance in English Test(Students)ENGLISH STATE MEAN SCORE


Students Performance in Mathematics TestThe chart below shows students’ performance in the mathematics test across the LGAs. A general analysis of the scores shows that there was a relatively low performance level in this domain across the schools relative to other learning domains. Similarly low performance was recorded by pupils in the numeracy test at the public primary schools. Out of 293 public secondary schools in all the LGAs surveyed 206 secondary schools (or 70%) in 14 LGAs performed below the state mean score of 45.22. Policymakers are challenged to action to shore up students’ performance in mathematics in all schools irrespective of LGAs. A good performance in mathematics is a sine qua non for advancement to higher levels of education and career in life.

Fig 7

ABUA/ODUA

AHOADA EAST

AHOADA WEST

AKUKU-TORUANDONI

ASARI-TORU

BONNY

DEGEMAELE

ME

EMOHUA

ETCHE

GOKANA

IKWERREKHANA

OBIO/AKPOR

OGU/BOLOOKRIKA

OMUMA ONE

OPOBO/NKOROOYIG

BO

PORT-HARCOURT

TAI0

10

20

30

40

50

60

70

Performance In Mathematics Test(Students)

MATHEMATICS STATE MEAN SCORE


Students Performance in General Science TestThe chart below displays the performance of students in the General science test across the LGAs. The performance level in this learning domain appears exceptional when compared to the two other domains. However 84 secondary schools in 9 LGAs performed below the state mean score - 58.42. Policy measures are required to improve performance of secondary school students in General science.

Fig 8

ABUA/ODUA

AHOADA EAST

AHOADA WEST

AKUKU-TORUANDONI

ASARI-TO

RUBONNY

DEGEM

AELE

ME

EMOHUA

ETCHE

GOKANA

IKWERREKHANA

OBIO/AKPOR

OGU/BOLOOKRIKA

OMUMA ONE

OPOBO/NKOROOYIG

BO

PORT-HARCOURT TA

I0

1020304050607080

Performance in General Science Test(Students)

GENERAL SCIENCE STATE MEAN SCORE


Chapter Five

How well did the Pupils/ Students Perform?It is important to define precisely what learners should have learnt at the end of every level of education. This offers a clear sense of direction to education stakeholders who include the learners, their teachers, parents, school heads, education financiers and policy makers. A minimum level of mastery allows the system to assess its performance and decide the necessary inputs required to achieve such levels of mastery. In this chapter, the performance of pupils/ students is benchmarked against established minimum standards. The desired mastery level which depicts excellent performance is also presented for all the learning domains.

Specification of MMLs and DMLs should meet the purpose of increasing learning attainments and serve as performance goals for the teacher and output indicators for the system. For this, the MML and DML must have, apart from relevance and functionality, the following attributes:

Achievable and RealisticThe minimum mastery level has to be achievable with considerations to the general characteristics in terms of cognitive ability and otherwise of the learners at every level. This could mean that MMLs be set specifically rather that universally with allowances given for the specific socioeconomic, and other factors of different learners in different places. Varying school conditions, socioeconomic and sociocultural contexts, mean that for MMLs to be achievable, these variations have to be considered in setting them. In a country in which achievement levels vary widely with regions, districts, school conditions, socioeconomic profile and other diverse factors, setting realistic and achievable minimum levels necessarily demands a great deal of flexibility.

CommunicabilityThe minimum mastery level should also be set in a form that is easily understood by all stakeholders in education: teachers, pupils, parents, etc. This way, MMLs can function as achievement targets. MMLs must be spelt out in simple enough terms so as to be understandable to all those concerned with the academic growth of the pupils/ students.

Learning ContinuumIt is important to set MMLs in as simple and comprehensible manner as possible, specifying the competencies to be mastered under each learning domain from primary school through secondary school. Learning is best seen as a 'continuum', in which the learning domains are sequenced hierarchically so that the clusters of competencies in one domain build as directly as possible on the competencies in the preceding domain. It is firmly believed that if the children progress systematically through this continuum, mastering the concerned sets


or competencies in each domain before they move on to the next, learning each subsequent domain will be more enjoyable and meaningful, and the achievement of minimum levels of learning will be facilitated. MMLs should be set with this continuum in mind to ensure that they capture the level of knowledge that learners need to have at a certain level in order to comprehend the instructions of the next level in the continuum.

For this study, the minimum mastery level (MML) and desired mastery level (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 within the control limits indicates a possibility to attain the minimum mastery level. The MML/ DML derivation formula is stated below:

μ±3(σ )√n

Where:

µ - Mean score

σ – Standard Deviation

n – Number of LGAs

The table below shows the derived MML and DML for each learning domain.

Table 5.1S/N Domain MML DML State Mean Score

Primary Four1 Literacy 57.2 64.9 57.72 Numeracy 44.9 54.4 49.63 Life Skills 66.9 74.8 70.9

JSS Two1 English 43.7 55.7 49.72 Mathematics 40.0 50.4 45.23 General Science 50.0 66.3 58.4

The minimum mastery level (MML) as stated in table 5.1 above represents satisfactory performance. It follows that pupils who score 57.2% in the Literacy learning domain have performed satisfactorily in that domain as have those who score 44.9% in Numeracy or


66.9% in Life Skills. The desired mastery level (DML) on the other hand depicts good performance. A score of 64.9% in the Literacy domain is translated as good performance. This applies to all the other domains as stated in the table above.Figures 5.1 to 5.6 depict the performance of schools in each local government relative to the derived mastery levels for each of the learning domains at the primary four and JSS 2 levels.


Fig 5.1

ABUA/ODUA/R

AHOADA EAST

/R/

AHOADA WEST

/U/

AKUKU-TORU /U

/

ANDONI /R/

ASARI-TO

RU /U/

BONNY /U/

DEGEM

A /R/

ELEME /

U/

EMOHUA /U

/

ETCHE /

R/

GOKANA /U/

IKWERRE /U/

KHANA /U/

OBIO/AKPOR /U/

OGU/BOLO /R

/

OKRIKA /U/

OMUMA /R/

ONNE /R/

OPOBO/NKORO /R/

OYIGBO /U

/

PORT-HARCOURT /

U/TA

I /U/

0.010.020.030.040.050.060.070.080.0

MASTERY LEVEL IN LITERACYLITERACY AVERAGE STATE MEAN SCORE MML DML

As shown in Fig 5.1 above, most schools performed above the MML in the literacy domain. It can be inferred that most pupils in Rivers State have achieved minimum mastery in literacy. 13 LGAs performed above the DML. Summarily, most pupils in Rivers State public schools have achieved minimum mastery or competence in literacy and a considerable number have attained advanced mastery of the domain.


Fig 5.2

ABUA/ODUA/R

AHOADA EAST /

R/

AHOADA WEST /U/

AKUKU-TORU /U

/

ANDONI /R/

ASARI-TORU /U

/

BONNY /U/

DEGEMA /R/

ELEME /U

/

EMOHUA /U/

ETCHE /R

/

GOKANA /U/

IKWERRE /U/

KHANA /U/

OBIO/AKPOR /U/

OGU/BOLO /R/

OKRIKA /U/

OMUMA /R/ONNE /R

/

OPOBO/NKORO /R/

OYIGBO /U

/

PORT-HARCOURT /U

/TAI /U/

0.010.020.030.040.050.060.070.080.0

MASTERY LEVEL IN NUMERACY.NUMERACY AVERAGE STATE MEAN SCOREMML DML

Although the performance in Numeracy was the lowest of the three learning domains in which primary four respondents were tested, most schools achieved the MML as presented in Fig 5.2 above. In terms of advanced mastery (DML) only 5 LGAS met the mark. Yet, it is impressive that minimum mastery in the numeracy learning domain has been achieved by a majority of the pupils.


Fig 5.3

ABUA/ODUA/R

AHOADA EAST

/R/

AHOADA WEST

/U/

AKUKU-TORU /U

/

ANDONI /R/

ASARI-TORU /U

/

BONNY /U/

DEGEMA /R

/

ELEME /U

/

EMOHUA /U

/

ETCHE /R

/

GOKANA /U/

IKWERRE /U/

KHANA /U/

OBIO/AKPOR /U/

OGU/BOLO /R/

OKRIKA /U/

OMUMA /R/

ONNE /R/

OPOBO/NKORO /R/

OYIGBO /U

/

PORT-HARCOURT /U

/TAI /U/

0.010.020.030.040.050.060.070.080.090.0

MASTERY LEVEL IN LIFE SKILLS.LIFE SKILLS AVERAGE STATE MEAN SCOREMML DML

Performance in life skills was the best of the three learning domains. The chart above shows that all but two of the LGAs achieved the minimum mastery level. 5 LGAs attained the desired mastery level.

Generally, primary four respondents can be said to have performed impressively considering that a large majority achieved minimum mastery in all the learning domains. This implies that they possess the minimum competence expected of them at their current school level. It is also worthy of note that the State mean score in all the learning domains is above the MML.


Fig 5.4

ABUA/ODUA/R

AHOADA EAST /

R/

AHOADA WEST /U

/

AKUKU-TORU /U

/

ANDONI /R/

ASARI-TORU /U

/

BONNY /U/

DEGEMA /R/

ELEME /U

/

EMOHUA /U

/

ETCHE /R

/

GOKANA /U/

IKWERRE /U/

KHANA /U/

OBIO/AKPOR /U/

OGU/BOLO /R/

OKRIKA /U/

OMUMA /R/

ONNE /R/

OPOBO/NKORO /R/

OYIGBO /U

/

PORT-HARCOURT /U

/TAI /U/

0.010.020.030.040.050.060.070.080.0

MASTERY LEVEL IN ENGLISH.ENGLISH AVERAGE STATE MEAN SCORE MML DML

JSS Two students from schools in 18 LGAs on the average performed above the MML in English Language. This suggests that most of the students tested met the minimum competency level in English. In terms of advance competence, schools from only five LGAs achieved the DML.


Fig 5.5

ABUA/ODUA/R

AHOADA EAST

/R/

AHOADA WEST

/U/

AKUKU-TORU /U

/

ANDONI /R/

ASARI-TO

RU /U/

BONNY /U/

DEGEM

A /R/

ELEME /

U/

EMOHUA /U

/

ETCHE /

R/

GOKANA /U/

IKWERRE /U/

KHANA /U/

OBIO/AKPOR /U/

OGU/BOLO /R

/

OKRIKA /U/

OMUMA /R/

ONNE /R/

OPOBO/NKORO /R/

OYIGBO /U

/

PORT-HARCOURT /

U/TA

I /U/

0.010.020.030.040.050.060.070.0

Mastery level in MathematicsMATHEMATICS AVERAGE STATE MEAN SCOREMML DML

The performance in the Mathematics domain was the poorest of the three domains in which JSS 2 student respondents were tested. However, most of the LGAs attained the minimum mastery level. In spite of the fact that mathematics is not an area of strength for most of the tested students, majority of them achieved the expected minimum competence in mathematics. Only a few achieved the DML in this domain.


Fig 5.6

ABUA/ODUA/R

AHOADA EAST

/R/

AHOADA WEST

/U/

AKUKU-TORU /U

/

ANDONI /R/

ASARI-TORU /U

/

BONNY /U/

DEGEMA /R

/

ELEME /U

/

EMOHUA /U

/

ETCHE /R

/

GOKANA /U/

IKWERRE /U/

KHANA /U/

OBIO/AKPOR /U/

OGU/BOLO /R/

OKRIKA /U/

OMUMA /R/

ONNE /R/

OPOBO/NKORO /R/

OYIGBO /U

/

PORT-HARCOURT /U

/TAI /U/

0.010.020.030.040.050.060.070.080.0

Mastery level in General ScienceGENERAL SCIENCE AVERAGE STATE MEAN SCOREMML DML

As shown in the chart above, schools from 16 LGAs performed above the MML and only schools in 7 LGAs achieved the DML. This means most of the tested students have achieved minimum mastery in the General Science domain.

Notably, the state mean scores in all the learning domains surpass the respective MMLs. Policy direction should aim at consolidating this achievement and to surpass this competence level by the next MLA assessment. A higher minimum competence level should be set as target towards which the state should aim.


Chapter Six

Factors that Affect Learning Performance (A Test of Selected Variables)This chapter contains a brief analysis of some sources of variations in the test scores. Here, the relationship between certain characteristics of the respondents and their learning performance is analysed.

A number of variables likely to affect the learning achievement of pupils/ students have been presented in volume four. This chapter however, is but a peek into what could otherwise be an extensive analysis. Specifically, four factors namely: feeding pattern, after-school activities, homework assistance and pre-primary education, are considered in relations to learning achievement.

A review of existing literature on this subject reveals that the above stated factors affect learning achievement and it is from these that we draw the following a priori assumptions:

- Feeding Pattern

A well-fed child should be a better learner when compared with a malnourished child. Children who have breakfast and lunch on school days would not have to grapple with hunger during class lessons. On this basis, we assume that well-fed children should perform better than others who are not well-fed.

- After-School Activities

Learning does not end within the walls of a school. The activities that children engage in after school hours could either reinforce their understanding of what they have learnt at school or erode it. The assumption is that children who engage in home study or attend extra lessons after school would perform better than others who are saddled with house chores, caring for their siblings or commercial activities.

- Homework Assistance

Homework assistance signifies the academic support that a child receives at home. Children who have academic support at home are at an advantage because such assistance could aid their comprehension.

- Pre-Primary Education

Globally, pre-primary education is recognized as crucial to the cognitive development of a child. It is an important foundation that supports the lifelong education pursuit of every individual. It is assumed therefore, that pupils who have pre-primary education would perform better than others who do not.


In the following analysis, randomly selected scores of pupil respondents categorized under the factors stated above are presented for a comparative analysis.


Feeding Pattern

Table 6.1

Breakfast No Breakfast194 206206 179207 161176 206221 218171 217179 198199 236208 202169 199208 160212 163192 170213 146204 160222 194

79 176216 182154 177197 194130 115137 162154 229155 243119 120151 85198 131163 80198 101181 166188 180193 154193 118119 113

84 151164 159158 148140 157149 145173 138160 148236 153182 119213 145172 153203 150224 147197 146210 142206 139

Total 8977 8081Mean 179.54 161.62Std. Deviation 34.79984166 36.5948MIN 79 80MAX 236 243

After-School Activities


The test scores of hundred randomly selected pupils are presented in Table 6.1, distributed by their feeding patterns. The pupils who report that they usually have breakfast before they go to school performed better (mean score: 179.54) than the others who do not (mean score: 161.62). Hungry children are less likely to be attentive to classroom lessons and this could adversely affect their performance.

Policymakers should strongly consider a school feeding programme that provides pupils with breakfast and lunch in school, as this would be beneficial to ensuring that they are in the best nutritional frame for learning.

Table 6.2 presents the scores of hundred randomly selected pupils. The scores are distributed on the basis of the respondents’ after-school activities. Respondents who attend extra lessons after school performed better (mean score: 189.98) than those who engage in other activities such as house chores and commercial activities

Table 6.2

Extra Lessons Others182 203230 163223 234245 161251 172233 189187 107199 192198 210201 129209 196163 188147 189206 180245 167195 147137 205148 198208 207200 218156 186185 214203 195105 153170 164238 190243 136178 162145 136208 214222 121219 149184 98172 168218 185173 156210 211186 135223 126184 88384 105116 156

46 13499 158

160 200175 134182 190156 154188 177164 167


Homework Assistance


Table 6.2 presents the scores of hundred randomly selected pupils. The scores are distributed on the basis of the respondents’ after-school activities. Respondents who attend extra lessons after school performed better (mean score: 189.98) than those who engage in other activities such as house chores and commercial activities

The test scores of hundred pupils selected at random are presented in Table 6.3. The scores are distributed by availability of homework assistance. Contrary to our a priori assumption, pupils who get no assistance doing their homework performed better (mean score: 194.96) than their counterparts who do (mean score: 185.08).

This may be a chance occurrence but policies should be

Table 6.3

Yes No148 207159 176188 162183 229193 200165 158153 234188 232186 155176 170182 182161 158179 247172 257185 250218 269242 236210 242223 255191 250207 170185 241140 222197 190205 163181 158163 168141 98219 211184 185126 88181 214189 188148 189156 147171 205169 207144 192189 209190 163208 201163 205232 177182 191161 173230 184223 178172 157245 227251 178


Pre-Primary Education


The test scores of hundred pupils selected at random are presented in Table 6.3. The scores are distributed by availability of homework assistance. Contrary to our a priori assumption, pupils who get no assistance doing their homework performed better (mean score: 194.96) than their counterparts who do (mean score: 185.08).

This may be a chance occurrence but policies should be

Table 6.4 presents the scores of hundred randomly selected pupils. The scores are grouped according to the pupils’ pre-primary school attendance or otherwise. Pupils who have pre-primary education have a lower means score (178.54) compared to others who do not (189.62). This is contrary to our a priori assumption given the world acclaimed importance of pre-primary education.

Table 6.4

Had Had None160 192194 198206 194207 160176 146221 170171 163179 199199 171208 109169 128208 180212 111213 114204 115206 227218 227217 227179 224206 224199 227236 221222 227

79 224216 227154 221130 224137 224154 188155 137119 144151 132198 195163 186198 159181 188188 195193 219193 225154 214180 217166 210101 230

80 205131 206

85 198162 204227 201195 188227 166



Table 6.4 presents the scores of hundred randomly selected pupils. The scores are grouped according to the pupils’ pre-primary school attendance or otherwise. Pupils who have pre-primary education have a lower means score (178.54) compared to others who do not (189.62). This is contrary to our a priori assumption given the world acclaimed importance of pre-primary education.

Determinants of Learning AchievementA number of factors influence the learning achievement of pupils. They include factors within and outside of the school environment. This study considered various factors and the findings are presented in volumes II, III, and IV of the report. Here is a snapshot of what was found:

Gender differencesGender parity in learning achievement has been an object of international concern. In many climes, a certain gender could be hindered by factors within the sociocultural environment and so perform poorly. Female pupils have been particularly susceptible to this and only recently have interventions to increase girl child education and improve the learning achievement of girls begun to yield fruits.

This study made the following findings in Rivers State:

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.

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. Generally, girls performed better than boys across the various Local Government Areas.

Locational differencesUsually, physical and social infrastructure is concentrated in urban areas and as such necessary learning resources might be inadequate in rural schools, thereby affecting the learning achievement of rural pupils. The level of adult illiteracy in rural areas might also mean that rural pupils do not get the academic support they need at home compared to urban pupils who are more likely to have educated adults around them to offer academic support.

This study found that there is no extreme disparity in learning achievement on locational basis in Rivers sate.

Other factorsOther factors that can influence learning achievement were categorised into four groups as follows: socio-economic factors, parental contributing factors, environmental/access factors and teacher quality. Each group contains sub-factors. The factors were estimated using econometric techniques and the following findings were made:

Parent Educational Level contributes 3 per cent to learning achievement at both primary and secondary levels. Free education policy contributes 30 per cent at both levels. Absence of transportation fare and provision of free school tables and chairs contribute 4.1 and 4.4 per cent respectively at both levels –primary and secondary schools. For secondary school, students’ perception of teachers’ attitude contributes 46.2 per cent, which is the most contributing factor under this category. Existence of physical and learning facilities contribute 4.6 per cent. Female students increase their learning performance by 8.2 per cent. Existence of playground contributes 10.6 per cent. Existence of well-equipped library contributes 12.5 per cent. Statistically, there is no


difference between urban and rural learning performances; by implication, the learning performance gap has been bridged. Contrarily, students trekking distance of 31 minutes and above lose in learning performance.

Detailed analysis and findings in these areas are contained in Volumes: II, III and IV.


Conclusion and Recommendations

1. Schools in the state are quite satisfactorily distributed as the majority of school children and teachers report that it takes them less than 10 minutes to get to school. This is coupled with the fact that the majority walk to school. This is a situation that will reduce the rates of lateness and absenteeism. The close proximity of home to school should encourage the rate of parent/teacher interaction as well as reduce the school children’s space for truancy.

2. The study reveals that school children’s enthusiasm for going to school is quelled by what they perceive as physical abuse from their peers as well as their teachers. The fear of bullying and of corporal punishment rank first and third highest on the list of reasons why school children sometimes do not want to go to school.

3. Based on the data supplied by the respondents, the government has some way to go in the provision of school infrastructure. Most schools lack libraries, computer facilities, toilets and medical facilities. The majority of available infrastructure lacks functionality due to a lack of equipment and/or maintenance. The most commonly available facilities are playgrounds. Without the necessary facilities, students’ capacity for expression and expansion is reduced.

4. The results of this study show that the Rivers state government has to a great extent levelled the educational playing field in the state. This is reflected in the outcome of the competence tests.

5. There were noticeable disparities in the performance of students and pupils across the three learning domains. Pupils tended to do better than the students. A reason put forward for this is the fact that students have more distractions- mobile phones, internet, hormonal issues- and responsibilities- babysitting, income-related activities- than pupils and therefore have less time to focus on their studies, especially after school. Another possible explanation is that more primary schools than secondary schools have been renovated and equipped at this point. This perhaps may have given the pupils a learning advantage over the students and it is predicted that when secondary schools are similarly renovated and equipped, students’ performance will improve.

6. Head teachers believe that automatic promotion is a panacea for disaster and they list it as a major contributing factor to the poor performance of pupils. The head teachers assert making pupils earn their promotions is a way to make them take their academics more seriously and teach them a valuable life lesson going forward in life.

7. The majority of parents lack a tertiary education which puts them at a disadvantage in the job market. With low-paying jobs, these parents may lack the financial muscle


to fully cater for their children’s’ education. Children with less-educated parents may also lack the requisite academic support at home.

8. Parents revealed that they still spend money on items that statutorily, they should not be charged for. These items include ‘school fees’, uniforms, text books and school furniture. This points to acts of sabotage within the school system as well as ignorance on the part of the paying parents.

9. The majority of teachers stated their intentions to remain permanently in the teaching profession. The percentage of teachers who indicated a desire to change career at some point tallies closely with the percentage of teachers who are trained in professions other than education.

10. Further detailed analyses of the possible relationships discussed in this volume are presented in our companion volumes 2 to 4 titled:

Vol. 2 Gender and Learning Performance in Rivers State Vol. 3 Rural -Urban Differences in Learning Performance in Rivers State Vol. 4 Determinants of Learning Performance in Rivers State

Recommendations Given that the majority of students walk to school, it is necessary to ensure that the

roads are safe for them. Road safety officials should be made available to control traffic and assist children as they go to school. Also, stop signs, slow down signs and zebra crossings should be present in school districts so as to reduce students’ exposure to traffic accidents.

The key to ending bullying lies in getting the students to respect and be considerate to one another. There is the need for all schools to have fully functional guidance counselling departments whose jobs would be to build student camaraderie through counselling and group bonding exercises.

Government reforms have had a profoundly positive effect in the schools in which they have been implemented. There is therefore a need to speed up the rate of implementation so all schools can be at par.

Promotion of pupils should be merit-based and not automatic as the former brings the best out of the students. Automatic promotion perhaps explains why the achievement gap widens as students get older. Having been undeservedly rewarded in primary school, students will find it difficult to cope with merit-based system of secondary education. They will also perform poorly because they lack a solid preparatory background.

Given that most parents possess educational qualifications that put them in the low-income category, it is essential that government’s educational subsidies benefit as many people as possible. This will be achieved through stricter policing of the educational system i.e. Ministry officials and school staff to prevent them from extorting parents through illegal and bogus charges such as exam fees and


extramural fees. A public education tracking survey needs to be conducted to highlight absenteeism and to ensure that material supplies get to those they are meant for.

Professional educationists should get first consideration for teaching jobs as they are more likely than their counterparts from other disciplines to be in it for the long term.

Teacher training courses should be frequent and compulsory. The state must draw up a set of disciplinary rules that guide teacher/student

relations i.e. what acts constitute abuse and what acts are permitted. Parents must be encouraged to take up active roles in their children’s educational

experience. A school management board comprising parents, community representatives, NGOs and other stakeholders should be actualized. In addition to providing financial support, parents must be encouraged to regularly liaise with teachers and to provide afterschool academic support as much as they can. Suggestions should be made to them on how to draw up afterschool timetables for their children that include ample time for academic activities. They must also be involved in teacher recruitment, transfer, and promotion.

Inter-agency cooperation must be encouraged in the state. Schools, medical authorities, security agencies and other relevant public service providers must be telephonically and electronically connected at all times so they can reach out to each other whenever they need to.

It is necessary to introduce a performance-based conditional cash transfer system targeted at children from low income parents.

The formation of parent-teacher associations should be encouraged and supported both legally and financially. An institutional framework should be developed to guide their activities.


Comparison of Survey findings with those from other studiesThe Monitoring Learning achievement survey has been carried out in many countries across the globe since it was first introduced in 1992, as emphasis has grown on functional education, education that translates into skill and knowledge acquisition, as opposed to education for education sake. This section contains a comparison of the findings of this MLA survey in Rivers State with those reviewed in Chapter two.

There are many similarities, typical of the MLA methodology. For example, in terms of methodology, all the studies use test questions in specified learning domains administered to learners in a selected class. Questionnaires were used to collect information on the characteristics of learners, their school and home environments, the quality of their teachers, their parents’ socioeconomic backgrounds, and other factors that could influence their learning outcomes. In all the studies, sampling was mindful to be representative of the region being surveyed. The sample population generally included: learners, their parents, teachers, and school administrators.

The fact that MLA is a product of a clamour for functional education is buttressed by the learning domains in which learners are examined in most of the studies: Literacy, Numeracy and Life skills. These domains represent a learner’s ability to communicate effectively in a given language (usually English Language, in Botswana pupils were also tested in the Setswana language), to do simple sums and carry out numeric operations required in everyday life. It also evaluates their ability to manage their everyday personal affairs and deal with challenges that come with daily living.

The studies also considered disparities in learning achievement along locational and gender lines. For example, in this study of Rivers State, it was found that pupils/ students from urban areas performed better than those from rural areas in the literacy learning domain. Similar locational disparities were found in the study in Ghana, and it was attributed to the fact that learning resources were not evenly distributed amongst urban and rural districts. Rural districts received fewer resources. In Botswana, gender disparities in learning achievement were discovered, with girls outperforming boys. Similar findings were made in this study but it was more specific to learning domains than general. Boys performed better in Numeracy, Mathematics and General Science, while girls did better in Literacy and English Language.

Similarities also resonate among the various MLA studies in terms of the factors that affect learning achievements. Some factors common to all the studies include: school environment, pupils’ socioeconomic conditions, and availability of learning materials, parental education, and home environment. These factors are both endogenous (within the school environment) and exogenous (outside the school environment). The table below presents a comparison of key elements of the various MLA studies.


Studies Surveyed population/ Sample Size

Survey Instruments

Learning domains Minimum Mastery Level

Major Findings Factors that affect learning achievement

MLA is Rivers State (2013)

-18, 135 pupils/ students-18,135 parents-3,004 teachers-916 school heads

-Test questions-Questionnaires

-Pupils -The best performance amongst Primary Four pupils was in Life skills. For the JSS two students it was in General science.-The Primary four pupils and JSS two students performed lowest in the numeracy and mathematic learning domains respectively.-Generally, the performance can be considered impressive as most pupils/ students achieved the set minimum mastery levels.

-School environment-Teacher quality-Parental education-Students’ socioeconomic characteristics

- Literacy 57.2%-Numeracy 44.9%-Life Skills 66.9%-Students-Mathematics 40.0%-English Language 43.7%-General Science 50.0%

MLA in Botswana1

-5,540 pupils-159 teachers-68 head teachers


-Literacy in Setswana

- -The performance of pupils was generally weak in all the learning domains.-Pupils performed best in the life skills test.-Performance varied significantly across gender with girls outperforming boys.

-School environment-School location-Pupil’s Parental background-Pre-primary education

-Literacy in English --Numeracy --Life Skills -

MLA in Kenya2

-4,436 pupils-733 teachers


-Reading - -Majority of the pupils attained minimum

-Pupil absenteeism-Language spoken at -Mathematics -

1 Standard Four Assessment Report on the Monitoring Learning Achievement Survey Project, Ministry of Education, Botswana, 1999.

-193 head teachers competency levels in reading and mathematics.- Pupils in urban areas performed better than pupils in rural areas in all the learning domains.-Boys did better than girls in both the reading and mathematics tests.

home-Pupil’s family background- School environment (availability of learning materials, condition of school buildings)

-HIV/ AIDS knowledge test

-

MLA in Ghana3

-Pupils-Teachers-Education administrators

-Test questions-Interviews (teachers, administrators, head teachers, senior members of the Ministry of Education)

-English Language - -Level of teacher motivation-Reluctance of some individual parents to provide basic needs for their children-Low enthusiasm and commitment to learning on the part of pupils-Teacher quality-Parents’ Poverty

-Mathematics -

Regional -Pupils -Test questions -Literacy - -The Literacy test had the -School curriculum

2 The SACMEQ III Project in Kenya: A Study on the Conditions of Schooling and the Quality of Education, SACMEQ, 20123 Mitchell Group, 2009. Basic Education Quality in Ghana: Progress and Problems , USAID1| P a g e A r b i t r a g e C o n s u l t L t d E m a i l : a r b i t r a g e c o n s u l t @ g m a i l . c o m

+ 2 3 4 ( 0 ) 8 0 2 3 3 2 3 3 7 8 o r + 2 3 4 ( 0 ) 8 0 7 2 5 7 8 1 4 5

Monitoring Learning Achievement Survey (1999)4

-Teachers-Parents-School heads

-Questionnaires highest grade.-Overall, performance in Numeracy was poor.

-School environment-Home learning environment

-Numeracy --Life Skills -

MLA Survey in Nigeria (2003)5

-Pupils-Teachers-Parents


-Literacy - -In all the areas tested the pupils in private schools performed better than their public schools’ counterparts.

-The urban schools performed better than the rural schools.

-Boys performed slightly better than girls.

-Pupils who had pre-primary education did better than pupils who did not.

-Life Skills recorded the lowest mean score of all the learning domains.

-Numeracy --Life Skills -

4 Chinapah, V.,1999. Handbook on Monitoring Learning Achievement Towards Capacity Building, Paris UNESCO5 Federal Ministry of Education, 2003. Nigeria Education Sector Analysis: Assessment of Learning Achievement of Primaries Four and Six Pupils in Nigerian Schools. Draft Report2| P a g e A r b i t r a g e C o n s u l t L t d E m a i l : a r b i t r a g e c o n s u l t @ g m a i l . c o m

+ 2 3 4 ( 0 ) 8 0 2 3 3 2 3 3 7 8 o r + 2 3 4 ( 0 ) 8 0 7 2 5 7 8 1 4 5

ReferencesArbitrage Consult Limited, 2013. Monitoring Learning Achievement in Rivers State: A Preliminary Survey, Abuja.

Chinapah, V., 1999. Handbook on Monitoring Learning Achievement: Towards Capacity Building , Paris: UNESCO.

Federal Ministry of Education, 2003. Nigeria Education Sector Analysis: Assessment of Learning Achievement of Primaries Four and Six Pupils in Nigerian Schools. Draft Report.

Henderson, T., A., Mapp & L, K., 2002. A New Wave of Evidence: The Impact of School, Faamily, and Community Connections on Student Achievement. Annual Synthesis

Ministry of Education , 1999. Standard Four Assessment Report on the Monitoring Learning Achievement Survey Project, Botswana: Ministry of Education .

Mitchell Group, 2009. Basic Education Quality in Ghana: Progress and Problems, USAID.

SACMEQ, 2012. The SACMEQ III Project in Kenya: A Study of the Conditions of Schooling and the Quality of Education, Nairobi: Kenya National Examinations Council.

Uguanyi, N. a., 2010. Air Pollution and its Possible Health Effects in Rural Dwellers in Rivers State

MLA in Rivers State, An Overview

Documents

r b i t r

mla surveyin rivers

uses of mla

mla surveyin nigeria

mla surveyin ghana

g e c o n s u

study area

economic assessment