Digitally Signed by: Content manager’s Name DN : CN = Webmaster’s name O = University of Nigeria, Nsukka OU = Innovation Centre

Ugwoke Oluchi C.

Faculty of Education

Department of Science Education,

UNIVERSITY MATRICULATION EXAMINATION SCORES AS PREDICTORS OF FIRST YEAR GRADE POINT AVERAGE

OF STUDENTS IN NIGERIAN UNIVERSITIES IN SOUTH-SOUTH, NIGERIA.

AYAWEI, EREFETEI .K PG//PhD/05/4

2

UNIVERSITY MATRICULATION EXAMINATION SCORES AS PREDICTORS OF FIRST YEAR GRADE POINT AVERAGE

OF STUDENTS IN NIGERIAN UNIVERSITIES IN SOUTH-SOUTH, NIGERIA.

BY

AYAWEI, EREFETEI .K

PG//PhD/05/40059

DEPARTMENT OF SCIENCE EDUCATION, FACULTY OF EDUCATION,

UNIVERSITY OF NIGERIA, NSUKKA

OCTOBER 2013

i

UNIVERSITY MATRICULATION EXAMINATION SCORES AS

PREDICTORS OF FIRST YEAR GRADE POINT AVERAGE OF STUDENTS IN NIGERIAN UNIVERSITIES IN

SOUTH-SOUTH, NIGERIA.

A PhD THESIS SUBMITTED TO THE DEPARTMENT OF SCIENCE EDUCATION,

FACULTY OF EDUCATION, UNIVERSITY OF NIGERIA, NSUKKA

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE AWARD OF THE DEGREE OF DOCTOR OF PHILOSOPHY IN

MEASUREMENT & EVALUATION

BY

AYAWEI, EREFETEI .K PG/PhD/05/40059

OCTOBER, 2013

ii

iii

CERTIFICATION

AYAWEI, EREFETEI K, a postgraduate student in the Department of Science

Education with Reg. No. PG/PhD/05/40059 has satisfactorily completed the

requirement for the award of the doctorate Degree in Philosophy of Science Education

(Measurement and Evaluation).

The work embodied in this thesis is original and has not been submitted either in

part or full for any other diploma or degree of this University or any other institution.

_____________________

Erefetei K. Ayawei

Student

iv

DEDICATION

This work is dedicated to the memory of my late parents’ Mr. Joseph Motto & Mrs.

Janet F. J. Ayawei (nee Ekubo) and to the honour of Jehovah God for his mercies as well as all

my HELPERS.

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ACKNOWLEDGEMENT

With utmost sense of humility, I am most grateful to my supervisor Prof. B.G. Nworgu

who gave me every support I needed. If I had worked at his speed I would have graduated a

long while. He deserves more gratitude than can be expressed here. To Dr. (Mrs.) L.N.

Nworgu, my supervisor’s wife, your words of encouragement literally spurred me to this point

when I was at the verge of abandoning this programme.

To Prof. A. A. Ali, Prof. D.N. Ezeh, Prof. Uchenna Eze, Dr. B.C. Madu, Prof. K.O.

Usman, Dr. A. O. Ovute and Dr. J. J. Agah, Dr. (Mrs.) F.O. Ezeudu, Dr. Christian A. Egbulefu,

Dr. Samuel I. Igbacha, I owe you gratitude. To Prof. F.A. Okwo and Prof. S.A. Ezeudu who

made very useful comments to enrich the content and quality of this work, I am most grateful.

Bro. Obinna Oje, Dr. Davidson Numonde and Chief (Dr.) K. I. Sintei, you were a bundle of

support at every point. To every staff of the Department of Science Education, your labour will

be ever remembered.

I also wish to appreciate Elder (Dr.) Emmanuel O. Denenu & Hon. (Mrs.) Victoria P.

Denenu and every member of the Intercessors Fellowship of Bayelsa (IFB) for their immense

spiritual and moral support. To my father in the Lord, His Lordship, Bishop Ebi S. Belepeigha,

presiding bishop, Global Victory International Ministries, Yenagoa, I am most grateful. I wish

to specially appreciate Bro.Tari MacDonald & Sis. Tari Nyingifa, Dcn. Popo I. & Sis. Ovieni

Popo Jonah, Ch. Freedom & Lady Deborah Etebu, Rev. Segun & Pst. (Mrs.) S. Favour

Balogun all of Global Victory International Ministries, Yenagoa for their support.

To a Mother-in-Israel, Lady (Mrs.) C.N. Nnebedum who made a home for me away from

home, and to the children, particularly Ms. Chinasa F. Ukwueze, thanks for your

encouragement and support.

To Mrs. Yenesom George, former Director of Personnel SUBEB thanks. You were more

than a friend. Mrs. Arangaebi, Director, School Services, Dr. J. Beredugo, Director, Teacher

Training and Mr. Eboh Mazi Amon Chief Admin Officer all of SUBEB, Bayelsa State, I

vi

sincerely appreciate your contribution.

I must pay tribute to my wife, Evang. Mrs. Rhoda E. Ayawei who was more than a pillar of

support all through the programme. To the children: Idimu Emmanuel Idimu, Yeinpatei

Ayawei, Ebiemi Ayawei, Charity Ayawei and Peace Ayawei we can thank God. I also

appreciate the goodwill of Unduemi Yabefa, Angatimi Yabefa, Pretei Yabefa, Ayibamietei

Yabefa and Ebipa Yabefa. Thanks for your support.

To my father, High Chief, Joshua E. Ayawei-Olo, thanks for your encouragement at all

times. You desired to see this day and it has come to pass. To my brothers and sisters: Chief

Godwill & Mrs. Alice G. Ayawei, Bishop Prosper & Rev. (Mrs.) Stella P. Ayawei, Apostle

Afatei Ayawei (Olomiewei I of Koluama) and family, Hon. Nimibofa & Lady (Mrs.) Diepreye

N. Ayawei, Surv. Ebigba & Mrs. Gloria Ebi Ayawei, Mrs. Praise Iniye Ernest (nee Ayawei)

Ebimene Ayawei, Sis. Judith S. Igho (nee Ayawei), Mrs. Suoyo kwomo (nee Ayawei), Ms.

Diepreye Ayawei, Bro. Ebinimi Ayawei, Sis. Emotimi Ayawei, Godday Owika, Mrs. Rose

Tariah (nee Ayawei) and Ms. Florence Ayawei, thanks for placing me on a pinnacle of glory.

God has done it for us.

My gratitude goes to M. Kokobaiye Angaye, former Exams & Records Officer, NDU,

Egberiwarebo Ebilade of Admissions Office, NDU and all other personnel who provided the

relevant data that gave the result to this study.

Finally, I must express my eternal gratitude to Jehovah God for His mercies and the

immeasurable grace to complete this programme. To many more persons’ whose names are not

mentioned here, I appreciate your enormous contribution to my success.

vii

TABLE OF CONTENTS

Title page - - - - - - - - - - - i

Approval page - - - - - - - - - - ii

Certification - - - - - - - - - - iii

Dedication - - - - - - - - - - - - iv

Acknowledgement - -- - - - - - - - - v

Table of content - -- - - - - - - - vii

List of tables - - -- - - - - - - - - xi

List of figures - - - - - - - - - - - - xii

Abstract - - - -- - - - - - - - - xiii

CHAPTER ONE: INTRODUCTION - - - - - - - - 1

Background to the problem - - - - - - - - - 1

Statement of the Problem- - - - - - - - - - 11

Purpose of the Study - - - - - - - - - 12

Significance of the Study- - - - - - - - - - 13

Scope of the Study- - - - - - - - - - - 15

Research Questions- - - - - - - - - - - 16

Hypotheses - - -- -- - - - - - - 16

CHAPTER TWO: LITERATURE REVIEW--- - - - - - 18

A. Conceptual framework - - - - - - - - - - 18

Concept of Unified Tertiary Matriculation Examination (JAMB-UTME) - - - 18

Concept of Post-Universities Matriculation Examinations (PUME) Screening tests - - 19

Concept of test validity - - - - - - - - - 21

Predictive validity - - - - - - - - 25

Procedure for calculating predictive validity - - - - - - 28

Factors affecting predictive validity - - - - - - - - 30

viii

The concept of moderator variables - - - - - - - - 35

Statistical tests for detecting and estimating moderator influence in predictive studies - 39

Statistical implications of moderated.multiple regression analysis- - - - - 42

B. Theoretical Framework - - - - - - - - - - 47

A Point-To-Point Theory - - - - - - - - - 47

Classical Test Theory - - - - - - - - - 48

C. Empirically Related Studies. - - - - - - - - - 49

Studies on predictive validity - - - - - - - - 49

Studies on moderator variables - - - - - - - - - 54

D. Summary of Review of Literature - - - - - - - - - 60

CHAPTER THREE: RESEARCH METHOD - - - - - - 62

Design of the study-- - - - - - - - - - 62

Area of the study-- - - - - - - - - - - 62

Population of the study-- - - - - - - - - - 62

Sample and sampling technique - - - - - - - - 63

Source data collection - - - - - - - - - - 63

Validation of the instrument - - - - - - - - - - 63

Reliability of instrument - - - - - - - - 64

Method of data collection-- - - - - - - - - - 64

Method of data analysis-- - - - - - - - - - - 64

CHAPTER FOUR: RESULTS - - - - - - - - - 70

Research question One - - - - - - - - - 70

Hypothesis One - - - - - - - - - - 71

Research question Two - - - - - - - - - 72

Hypothesis Two - - - - - - - - - - 72

Research question Three - - - - - - - - - 72

Hypothesis Three - - - - - - - - - - 73

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Research question Four - - - - - - - - - - 73

Hypothesis Four - - - - - - - - - - 73

Researcher question Five - - - - - - - - - 76

Hypothesis Five - - - - - - - - - - - 80

Research question Six - - - - - - - - - - 80

Hypothesis Six - - - - - - - - - - 87

Research question Seven - - - - - - - - - 88

Hypothesis Seven - - - - - - - - - - 94

Research question eight - - - - - - - - - 95

Hypothesis Eight - - - - - - - - - - - 98

Research question Nine - - - - - - - - 98

Hypothesis Nine - - - - - - - - - - 101

Summary of results - - - - - - - - - 103

CHAPTER FIVE: DISCUSSION OF RESULTS, CONCLUSION, IMPLICATIONS,

RECOMMENDATIONS, AND SUMMARY OF THE STUDY - - - - 104

Discussion of the results - - - - - - - - - - 104

1) The predictive validity of UTME - - - - - - - - 104

2) The predictive validity of PUME - - - - - - - - - 113

3) The predictive validity of the combination of UTME and PUME - - - - 106

4) The influence of gender on the predictive validity of UTME scores - - - - 108

5 The influence of gender on the predictive validity of PUME scores - - - - 109

6) The influence of field of study on the predictive validity of UTME scores - - - 110

7) The influence of field of study on the predictive validity of PUME scores - - - 111

8) The influence of proprietorship on the predictive validity of UTME scores - - 113

9. The influence of proprietorship on the predictive validity of PUME scores - - - 115

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Conclusion - - - - - - - - - - - 116

Educational implications - - - - - - - - - 119

Limitations of study - - - - - - - - - - 122

Recommendations - - - - - - - - - - 122

Suggestions for further studies - - - - - - - - - 123

Summary of the study - - - - - - - - - 124

References - - - - - - - - - - - 128

APPENDICES - - - - - - - - - - - - 143

Appendix A: List of universities in the south-south geopolitical zone - - - 143

Appendix B: Instrument for data collection- - - - - - - - 144

Appendix C: Letter for access to data - - - - - - - - - 146

Appendix D: Hierarchical Multiple Regression (HMR) output on the combination of

UTME and PUME scores with FYGPA - - - - - 147

Appendix E: HMR output on the influence of gender on UTME scores with FYGPA - - 150

Appendix F: HMR output on the influence of gender on PUME scores with FYGPA - - - 153

Appendix G: HMR output on the influence of field of study on UTME scores with

FYGPA - - - - - - - - - - 156

Appendix H: HMR output on the field of study on PUME scores with regard to

FYGPA - - - - - - - - 162

Appendix I: HMR output on the influence of proprietorship of institution on the

predictive validity of UTME with regard to FYGPA - - - - - 168

Appendix J: HMR output on the influence of proprietorship of institution on

the predictive validity of PUME score with regard to FYGPA - - - 171

Appendix K: Converted UTME and PUME scores - - - - - - - - - 174

Appendix L: C_UTME scores, gender and Interaction term - - - - - - 187

Appendix M: C_PUME scores, gender and Interaction term - - - - - - 199

Appendix N: C_ UTME scores, field of study and Interaction term - - - - 211

Appendix O: C_ PUME scores, field of study and Interaction term - - - - 231

Appendix P: C_ UTME scores, proprietorship and Interaction term - - - - 235

Appendix Q: C_PUME scores, proprietorship and Interaction term - - - - 247

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LIST OF TABLES

Table 1: Model summary of hierarchical multiple regression analysis of UTME and PUME

with FYGPA - - - - - - - - 70

Table 2: Summary of coefficients of hierarchical regression analysis for UTME and PUME

with FYGPA - - - - - - - - 71

Table 3: Summary ANOVA of hierarchical regression analysis for UTME and PUME

with FYGPA - - - - - - - - - - - 73

Table 4: Model summary of Hierarchical Regression for X1, G and X1G with FYGPA - 74

Table 5: Summary of coefficients of hierarchical regression analysis for X1, G and X1 * G with FYGPA - - - - - - - - - 74

Table 6: Model summary of Hierarchical Regression for X2, G and X1 G with FYGPA - - 77

Table 7: Summary of coefficients of hierarchical regression analysis for X2, G and X2* G with FYGPA - - - - - - - 78

Table 8: Model summary of Hierarchical Regression for X1, F and X1F with FYGPA - - 80

Table 9: Summary of coefficients of hierarchical regression analysis of

C_X1, F and C_X1F - - - - - - - 81

Table 10: Model summary of Hierarchical Regression for X2, F and X2F with FYGPA - 88

Table 11: Summary of coefficients of Hierarchical regression analysis of X2, F and X2*F - - - - - - - - - - 89

Table 12: Model summary of Hierarchical Regression X1, P and X1P with FYGPA - 95

Table 13: Summary of coefficients of hierarchical regression analysis of X1, P and X1P with FYGPA - - - - - - - - 96

Table 14: Model summary of Hierarchical Regression for X2, P and X2P with FYGPA - 99

Table 15: Hierarchical Regression Analysis coefficients of X2, P and X2P with FYGPA- 99

xii

LIST OF FIGURES

Figure :1 Moderator Model - - - - - - - - 37

Figure 2: Regression lines predicting Ŷ (FYGPA) as a function of X1 (UTME scores) for G (gender) - - - - - - - - - 76

Figure 3: Regression lines predicting Ŷ (FYGPA) as a function of X2 (PUME scores) for gender (G) - - - - - - - - 79

Figure 4: Regression lines predicting Ŷ (FYGPA) as a function of X1 (UTME scores) for field (F0 and F1) - - - - - - - - 84

Figure 5: Regression lines predicting Ŷ (FYGPA) as a function of X1 (UTME scores) for field (F0 and F2) - - - - - - - 85

Figure 6: Regression lines predicting Ŷ (FYGPA) as a function of X1 (UTME scores) for field (F0 and F3) - - - - - - - 86

Figure 7: Regression lines predicting FYGPA as a function of UTME (X1) scores for

field (F0 and F4) - - - - - - - 87

Figure 8: Regression lines predicting Ŷ (FYGPA) as a function of X2 (PUME scores) for

field (F0 and F1) - - - - - - - - - 91

Figure 9: Regression lines predicting Ŷ (FYGPA) as a function of X2 (PUME scores) for field (F0 and F2) - - - - - - - - - 92

Figure 10: Regression lines predicting Ŷ (FYGPA) as a function of X2 (PUME scores) for field (F0 andF3) - - - - - - - - - 93

Figure11: Regression lines predicting Ŷ (FYGPA) as a function of X2 (PUME scores) for field (F0 and F4) - - - - - - - - - 94

Figure 12: Regression lines predicting Ŷ (FYGPA) as a function of X1 (UTME scores) for proprietorship - - - - - - - - - 97

Figure 13: Regression lines predicting Ŷ (FYGPA) as a function of X2 (PUME scores) for proprietorship - - - - - - - - 101

xiii

ABSTRACT

This study investigated the predictive validity of University Matriculation Examination

Scores and the influence of gender, field of study and proprietorship of institution on the

relationship between the matriculation examinations scores and students’ first year grade point

average (FYGPA). Participants in this study consisted of 564 undergraduate (352 male and 212

female) students whose records were obtained from one federal-owned university and one

state-owned university. The study was guided by 9 research questions and 9 hypotheses tested

at 0.05 level of significance. The study adopted a correlational design and collected data from

universities using the Institution and Student Characteristic Pro Forma (ISCP). The data

collected was analyzed using hierarchical multiple linear regression analysis. The major

findings of this study were as follows: (1) UTME scores did not significantly predict FYGPA

(F1, 562 = 1.98, p = .160); UTME scores explained 0.4% of the variance of FYGPA. (2) PUME scores significantly predicted FYGPA (F1, 562 = 194, p = .000); PUME scores also explained 25.8% of the variance of FYGPA. (3) The combination of UTME scores and PUME scores

significantly predicted FYGPA (F2, 562 = 97.34, p = .000); and also explained 25.8% of the variance of FYGPA. (4) The interaction between UTME scores and gender did not

significantly enhance the predictive validity of UTME scores with regard to FYGPA (∆F3, 560 = 3.39, p = .068); and explained 0.6% unique increase in the variance of FYGPA. (5) The

interaction between PUME scores and gender significantly increased the predictive validity of

PUME scores with regard to FYGPA (∆F 3,560 = 8.66, p =.003); and also explained 1.1% unique increase in the variance of FYGPA (6) The interaction between UTME scores and field

of study significantly enhanced the predictive validity of UTME scores with regard to FYGPA

(∆F9,554 = 4.74 p = .001); the interaction explained 3% unique increase in the total variance of FYGPA (7) The interaction between PUME scores and field of study significantly influenced

the predictive validity of PUME scores with regard to FYGPA (∆F9,554 = 10.29, p=.000);the also explained 4.9% unique increase in the variance of FYGPA (8) The interaction between

UTME scores and proprietorship of institution did not significantly enhance the predictive

validity of UTME scores with regard to FYGPA (∆F (3,560) = 1.08, p=.300); the interaction accounted for only 0.2% unique increase in the variance of FYGPA (9) The interaction

between PUME scores and proprietorship of institution significantly enhanced the predictive

validity of PUME scores with regard to FYGPA, (∆F3,560 = 6.17, p=.013); the interaction explained 0.8% unique increase in the variance of FYGPA. One of the implications of this

study is that PUME screening tests serve as a quality control measure in the university system.

Among other things it was recommended that rather than seek for the proscription of the

PUME screening tests, JAMB should redesign the UTME such that it will be have a higher

predictive validity.

.

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CHAPTER ONE

INTRODUCTION

Background to the study

A test or examination is an assessment intended to measure an individual's level of

knowledge, skill, aptitude, physical fitness, or classification in many other topics (e.g., beliefs)

in a particular area. A test according to Nworgu (2006) is a quantification of the behaviour of a

candidate based on his or her response to the questions set in a particular area. Thus a test score

is a piece of information, usually a number, which conveys the performance of an examinee on

a test. It is a summary of the evidence contained in an examinee's responses to the items of a

test that are related to the construct or constructs being measured. Ogundokun and Adeyemo

(2010) observed that examination marks or scores assigned to a candidate is an indicator of his

or her cognitive achievement in a particular at a given time or over a period of time.

One of the several reasons for developing and administering a test and grading

candidates with test scores is the selection of candidates to fill identified vacant spaces. These

vacant spaces could be for a job or admission of students into institutions of learning.

According to Mehrens and Lehmann (1975) the selection of candidates to fill the vacant places

either in an institution for admission purposes or establishment for the purpose of employment

or the selection of personnel either into the civil service or the military necessitated the conduct

of selection or placement tests. The idea is that, the spaces are fewer than the number of

candidates applying at a particular time and there are specific skills and abilities needed for

success in the expected field. Therefore, selection or placement or entrance examination breeds

stiff competition.

These tests are developed in such a manner that performances in them reflects the

likelihood of success in a similar environment after being exposed to the skills and training in

the envisaged field of engagement. For instance, Grolund (1970) stated that tests used for

placement or selection purposes, performs two basic functions: ascertaining that the candidate

2

possesses the knowledge and skills needed to begin the planned instruction or engagement and

secondly, to ascertain the extent to which the candidate has already mastered the objectives of

the envisaged programme. Thus in order to ascertain that candidates’ possesses the prerequisite

knowledge and skills, universities in Nigeria now uses an applicant's test score on both the

Unified Tertiary matriculation Examination (UTME) and Post Universities Matriculation

Examination (PUME) screening tests as just one of their many admission criteria to determine

if an applicant should be admitted into one of its undergraduate programs. The other criteria in

this case may include the applicant's senior school certificate examination results or its

equivalent. The reason being that those admitted are the most suitably qualified candidates.

The UTME is developed, administered and graded by the Joint Admissions and

Matriculation Board (JAMB). The Board was established, through Decree No.2, 1978 by the

then Federal Military Government of Nigeria, as an agency of the federal-government and an

examining body. Its principal responsibility is to conduct a national matriculation examination

common for candidates seeking admission into all Nigerian universities thereby centralizing

the admission system. This notion is conveyed in the introduction to the Joint Admissions and

Matriculation Board Act 1989:

“… An act to establish the Joint Admissions and Matriculation Board to

administer a centralized admissions system for universities, polytechnics and colleges

of education...” (Joint Admissions and Matriculation Board Act, 1989

Before its establishment and the conduct of UTME, each of the existing universities

conducted her own matriculation examination. The result was that the admission processes

were untidy and uncoordinated. Adamu (1994) and Harbor-Peters (1999) observed that there

were vacant and unfilled spaces in some universities because of multiple offers of admissions,

multiple application and multiple examinations written by students at that time. Nworgu (2006)

observed that the decentralized university admission system created an allowance for

admission irregularities, malpractices and lack of comparability of standards. Afemikhe (2008)

3

also noted that generally there was untidiness and lack of coordination in the admission system

into universities. Similarly, Ukwuije and Orluwene (2010) observed that there were multiple

admissions, poor logistics, and high cost of application as well as travel expenses, tribalism,

regional tendencies, corruption and non-uniformity of standards in the entrance examinations

across different universities. Omodara (2010) stated that there had existed educational

imbalance occasioned by disparity of educational opportunities between the regions in which

the universities were sited and those outside as well as differing admission standards by the

different universities. Uju and Ezeudu (2010) argued that there were several irregularities in the

matriculation examination which were conducted by the respective universities.

While the above where some of the obvious reasons for the establishment of the Board,

the more important reason was the unity of the country and reduction of regional tendencies.

Asein and Lawal (2007) argued that the need to foster national unity among the different ethnic

groups which were recovering from an avoidable 30- month long war necessitated the

establishment of the Board and the centralizing of the admission processes into Nigerian

universities. In summary, the National Policy on Education with regard to universities stated as

follows:

“…admission of students and recruitment of staff into universities and other institutions

of higher learning should be on a broad national basis…” (NPE: 24/26).

The JAMB administered matriculation examinations had several advantages over the

individual universities conducted matriculation examination. First, it provided candidates the

opportunity to obtain a single form and chose an examination centre closest to them without

necessarily travelling to their preferred university for the examination. Secondly, it reduced the

influence of state of origin because candidates had the opportunity of choosing universities far

away from their state of residence. Third, the UTME ensured that all candidates seeking for

admission to tertiary institutions in Nigeria write the same examination thereby ensuring

uniformity and comparability of standards of performance between successive years, zones,

4

states and even candidates (applicants).

However, the validity of the UTME scores which is the correlation coefficient between the

UTME scores and university grades, either the first year Grade point Average (FYGPA) or the

cumulative Grade Point Average (CGPA), has been a concern for users of the UTME and

critics. One of the criticisms of the UTME scores is that they do not adequately predict

individual students’ university grades. For example, Obioma and Salau (2007) observed that

the UTME scores was the least predictor of both the first year grade point average (FYGPA)

and final year cumulative grade point average (CGPA), accounting for 1.5% of the variance in

FYGPA and 0.6% of final CGPA. In a similar study conducted by Ojerinde and Kolo (2009)

the authors observed that UTME scores accounted for a very low amount of variance (2.8%) in

the FGPA.

Others have argued that the scores students obtain in the UTME are not their true scores,

suggesting they may have been influenced by external influences. For instance, Ifedili and

Ifedili (2010) stated that the admission decisions based on UTME scores have created an

access route for malpractice compliant students to be admitted into courses and programmes

they are least qualified for admission. Consequently it has led to a loss of educational equality

and opportunities among applicants and created unfairness in the admission process. Uju and

Ezeudu (2010) also argued that examination malpractice induced by psychological factors such

as fear, stress, insufficient preparation for the examination, low academic ability, laziness

among other things have resulted in seemingly unreliable UME scores. Consequently the

universities have offered admission to unqualified candidates. Omede (2010) stated that

because there seems incongruence between UTME scores and expected course demands. The

author argues that this incongruence exists because the scores candidates obtained in the

examination were induced by external influences that manifested at the time. Consequently

many matriculated student had changed courses which they were originally admitted, to other

courses which seem to be less academically demanding. This is not necessarily due to interest

5

in the new course but necessitated by lack of commensurate ability to match the demands of

the former course or discipline.

These criticisms necessitated the birth of the Post-Universities Matriculation Examination

(PUME) screening tests. Thus the 2005/2006 school year would be long remembered because

it ushered in the PUME screening tests. The PUME otherwise called the Screening Tests are

university-dependent matriculation examination designed and conducted to test the consistency

of performance standards of applicants or candidates who apply for university admission in a

current school year. According to Isine, Deji-Folutile and Amakeodo (2005), the Federal

Government of Nigeria approved the request of the committee of Vice-Chancellors to further

screen candidates to determine the quality of student as reflected in their UTME scores. To

qualify for the PUME, the candidate may have sat for the Unified Tertiary matriculation

Examination (UTME) in the current year and meet a university determined cut-off score/point.

As currently designed the PUME is a screening test, hence different universities adopt different

methods for the screening exercise. In some universities, the screening tests are oral interviews

while in some others it is standardized achievement test. Consequently the criteria for

admission also vary between institutions.

Some universities admit students based on an aggregate of the UTME and PUME

screening test scores. The average performance of the candidates is now assessed in relation to

faculty and departmental cut-off point for possible admission/placement. Proponents see the

PUME screening tests as a great leveller which allows demonstration of consistent individual

ability and a remedial measure that permit universities to make better decisions about those

students for whom UTME scores may not provide wholly consistent information about their

abilities as required for university admission.

However the post-university matriculation examination (PUME) screening tests are not

without its criticisms. First is the concerns of and fear expressed by parents, guardians’ and the

candidates. This group argues that the PUME screening tests will breed favouritism and state

6

of origin bias in university admissions. Some candidates fear that their admission and those of

their loved ones will depend on the strength of the personal relationship between parents,

guardians or relatives with university authorities. The implication is that children of the poor in

the society may not gain university education as they will not have equal access to the

authorities.

Second, the establishment (approval) and subsequent conduct of the PUME screening

tests will lead to lack of uniformity of entrance examination standards which existed before the

commencement of the UTME. Third, some critics believe that apart from breeding issues

relating to state of origin and personal relations in admission decisions, the PUME screening

tests are avenues by university authorities to raise funds both for the institution, cyber café

operators and bank officials. This group contends that there are several in-built charges that

make these forms much more expensive than the UTME. Fourth, there is the opposition from

JAMB official who view the intrusion of the PUME screening tests as unlawful and a subtle

attempt by university authorities to render their employments redundant by performing their

statutory responsibility. For instance, Ifedili and Ifedili (2010) noted that JAMB official

complained bitterly about the PUME screening process as universities usurping their

mandatory roles. For instance JAMB officials argued before the Nigerian Senate that there is

no law mandating the universities to conduct matriculation examination for university

admission.

The dependent or criterion variable was first year grade point average (FYGPA). The

FYGPA of a student is obtained after the first year of study in a particular institution. Most

Nigerian universities uses the 5-point scale ranging from A=5, B=4, C=3, D=2 to E=1 and

F=fail. It is the cumulative grade of the student’s first and second semester examination.

The independent variables (focal predictors) are the candidate’s Unified Tertiary

matriculation examination (UTME) scores and post-universities matriculation examination

(PUME) screening test scores. UTME scores are obtained from candidates who sat for the

7

Unified Tertiary Matriculation Examination conducted by the Joint Admissions and

Matriculation Board. Unlike the Scholastic Aptitude Test (SAT) which is an aptitude test in

which candidates sit for mathematics and verbal aptitude skills, the UTME is a multiple-choice

achievement test with the Use of English compulsory for all candidates and three other subjects

relevant to a candidate’s preferred course of study. The possible total obtainable score of a

candidate is 400 points. On the other hand, PUME scores are obtained by candidates who were

qualified to take the Screening Tests of their preferred universities after meeting a university-

dependent cut-off score. The cut-off score of most federal universities are higher than state

universities. For instance in the 2013/2014 academic year the cut-off score for all federal

universities was pegged at 180 points while state universities cut-off score was 150 points.

These scores qualify the candidate for the Screening Tests and not for university admission.

The structure, form and maximum score of these screening tests are university dependent and

vary from one university to the other. A score in the UTME or PUME screening test is

supposed to be an indicator of the academic ability of an aspiring university undergraduates

and a forecast of what a student can do as well as evidence of the academic background of the

student.

The moderator variables examined in this study are: gender, field of study and

proprietorship of institution because pre-existing subgroups such as these offers easily

identifiable and theoretically meaningful sources of moderator variables. According to Sharma,

Durand and Gur- Arie (1981) a moderator variable is one which systematically modifies either

the form and/or strength of the relationship between a predictor and a criterion variable. It is

believed that properly accounting for these moderator variables in a multiple variables study

will provide for an improved level of prediction and explanation – other than the predictive

validity coefficients that are often reported. Moderator variables are examined because the

classic validation theory used in explaining the predictor – criterion relationship could not

account for complex phenomena especially in cases where the relationship between the

8

criterion variable and predictor variables could be influenced or enhanced by a third variable

called the moderator variable. Specifically, Capoor and Norman (1976) stated that moderator

variables can affect the relationship between the predictor and criterion therefore properly

accounting for their moderating effects can enhance the explanatory power of research analysis

particularly in a multiple regression approach.

Gender in this study is understood to mean the biological and physiological

characteristics that define men and women and not gender in terms of the socially constructed

roles, behaviours, activities, and attributes that a given society considers appropriate for men

and women. With regard to the admission of candidates into Nigerian universities, there are no

different cut-off marks or points for females and males students.

Field of study is here defined as a branch of knowledge that is taught and researched at the

college or university level. The Longman Interactive English Dictionary (2000) defines field as

a department within a university e.g. engineering. Therefore by faculty or field of study means

the branch of study the student chooses to specialize in the university. With regard to

admission into undergraduate programmes in Nigerian universities the cut-off mark is field or

faculty dependent. The fields or faculties of the medical sciences, law and engineering

generally have higher cut-off marks than other faculties or fields of study.

Proprietorship is understood to mean the ownership of the institution. There are two types

of institutions in terms of ownership in Nigeria. These are the public universities and private

universities. Private universities are directly controlled and managed by a non-governmental

organization (e.g. a faith-based organization, trade union, business enterprise or an individual),

or its Governing Board consists mostly of members not selected by a public agency. On the

other hand, public universities are controlled and managed directly by a public education

authority or by a governing body (council, committee etc.), most of whose members are

appointed by a public authority or elected by public franchise. Additionally public universities

in Nigeria are separated into two. These are the federal or state universities. Federal

9

universities are controlled and managed directly by a federal authority or by a governing body

(council, committee etc.), most of whose members are appointed by the Federal Government of

Nigeria. State universities, on the other hand, state universities are controlled and managed

directly by the respective state governments or by a governing body (council, committee etc.),

most of whose members are appointed by the respective state governments.

The federal universities are basically funded by the federal government, while the state

universities are principally funded by the respective state governments with occasional grants

from the Federal Government through her agencies such as the Education Trust Fund (ETF)

and the private universities are owned and funded by private individuals or corporate

organizations. Generally the tuition fees of federal universities are much lower than either the

state or private universities. However, because of the lower tuition fees, they have the largest

student population than either the state or private universities which put undue pressure on the

resources and infrastructure of the respective institutions.

With regard to admission into undergraduate programmes in Nigerian universities the cut-

off mark is university dependent. The federal universities generally have higher cut-off marks

than state universities. For instance in the 2013/2014 school year the cut-off score for all

federal universities was 180 marks whereas the cut-off score for state universities was 150

marks.

Studies exist that provide evidence that moderator variables have influence on the predictive

validity of criterion measures. For instance, Zeidner (1987), JAMB (2007) hypothesized that

the relationship between aptitude test scores and grade point average (GPA) could be

moderated by the age of the candidate taking the test at a particular time. The results of these

studies showed that indeed predictive values differed significantly across different age groups

as hypothesized. Similarly Ojerinde and Kolo (2009) and Ojerinde and Ojo (2009) also tested

the hypothesis that the predictive validity of UTME scores in relation to first year grades could

be moderated by gender. The results showed predictive values higher for male students than

10

female students. Ramist, Lewis and McCamley (1994) showed that women scores were under-

predicted while male SAT scores were over-predicted.

Predictive validity is the extent to which performance on a test is related to later

performance that the test was designed to predict. For example, the UTME and PUME

screening tests are taken by university-bound students to predict their future performance in

college namely, their college GPA. A score in the UTME or PUME screening test is supposed

to be an indicator of the academic ability of an aspiring university undergraduates and a

forecast of what a student can do. If students who scored high on these tests tend to have high

GPAs in colleges, then we can say that the UTME and PUME scores have good predictive

validity. But if there is no significant relation between UTME and PUME scores and college

GPA, then we would say the UTME and PUME scores has low or poor predictive validity,

because it did not predict what it was supposed to. Nworgu (2006) noted that predictive

validity, a form of criterion-related validity provide evidences that make a test instrument

standard. Hence, establishing the predictive validity of the matriculation examination scores is

a means of providing standardization evidences of the examinations. Schmidt and Hunter

(1998) stated that, in terms of practical value, predictive validity is the most important property

of a personnel assessment method because the predictive validity coefficient is directly

proportional to the practical economic value of the assessment method.

A great deal of research has been done on the predictive validity of UTME scores but the

correlations obtained from these predictive validity studies vary greatly and are typically quite

low. However, most of the research on the prediction of first year GPA has not taken into

cognizance the PUME scores as well as the influence of contextual (Moderator) variables.

The fact remains that if the PUME will be used as a selection examination for admission into

Nigerian universities, its predictive power need to be determined. Similarly the influences of

other contextual matters such as gender, field of study and proprietorship of institution on the

11

predictor-criterion relationship need to be examined. This will help the researcher properly

account for the moderating influence of these elements in predictive validity studies.

Since the UTME and PUME are all designed to help in identifying the candidates who

possesses the prerequisite academic ability for success in university programme in Nigerian

universities, the specific measure (dependent variable) used was the first year GPA of the

2006/2007 academic session

Therefore, the goal in this dissertation was to extend the understanding on the predictive

validity of both UTME scores and PUME scores in relation to FYGPA (the criterion variable);

and also to explain the influence of some categorical moderator variables in the relationship

between the criterion and predictors.

Statement of the problem

Candidates seeking admission into Nigerian universities are now faced with the task of sitting

for two compulsory matriculation examinations. These are the Unified Tertiary Matriculation

Examination (UME) and Post-Universities Matriculation Examination (PUME). Candidates are

offered admission based on the average scores of these two examinations according to

departmental/faculty cut-off marks. The persistent poor performance of students who were

admitted into the different programmes in the universities through the nationally conducted

UTME, despite the success, and sometimes, very high scores, necessitated the PUME

screening tests. The observed evidences of low correlation or relationship between the UTME

scores and subsequent outcome of interest – university grades which is represented by the first

year grade point average (FYGPA) became a source of worry and concern to all and sundry. It

becomes vital to examine the predictive strength of the Universities Matriculation Examination

Scores (UMES) that is the UTME scores and PUME scores, with regard to the FYGPA of

students, to ascertain either of the two is a better predictor.

On the other hand, Capour and Norman (1976) observed that moderator variables can

affect the relationship between the predictor and criterion; hence a proper accounting for their

12

moderating effects can enhance the explanatory power of research analysis particularly in a

multiple regression approach. Pre-existing groups such as those based on gender, field of study

and proprietorship of institution offers identifiable and theoretically meaningful sources of

moderator variables.

Some studies have been conducted in the predictive validity of UTME scores and

PUME scores separately. For instance Uju and Ezeudu (2010), JAMB (2007) reported that

there was low correlation between UTME scores and FYGPA, while Owie (2010) observed

that whereas there was a positive correlation between UTME scores and FYGPA and there was

negative correlation between PUME scores and FYGPA. Similarly, Ojerinde and Kolo (2009)

and Ojerinde and Ojo (2009) had observed that contextual variables significantly enhanced the

predictive validity of UTME scores with regard to FYGPA. These contradictory reports and

research results has led to this present study of the predictive validity of UTME scores and

PUME scores with regard to FYGPA as well as the influence of some contextual variables.

Thus framed in the form of a question: are PUME scores better predictors of FYGPA than

UTME scores? What amount of influence do contextual (moderator) variables have on the

relationship between university matriculations examination scores (UMES) and FYGPA?

Purpose of the study

The general purpose of the study was to determine the predictive validity of UTME scores and

PUME test scores on undergraduate students’ performance in Nigerian universities. Specifically,

the study determined:

1. The predictive validity of UTME scores with regard to first year GPA among undergraduates

in Nigerian universities.

2. The predictive validity of PUME scores with regard to first year GPA among undergraduates in

Nigerian universities.

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3. The predictive validity of the combination of UTME scores and PUME scores with regard to

first year GPA among undergraduates in Nigerian universities.

4. The influence of gender on the predictive validity of UTME scores with regard to first year

GPA among undergraduates in Nigerian universities.

5. The influence of gender on the predictive validity of PUME scores with regard to first year

GPA among undergraduates in Nigerian universities.

6. The influence of field of study on the predictive validity of UTME scores with regard to first

year GPA among undergraduates in Nigerian universities.

7. The influence of field of study on the predictive validity of PUME scores with regard to first

year GPA among undergraduates in Nigerian universities.

8. The influence of proprietorship of institution on the predictive validity of UTME scores with

regard to first year GPA among undergraduates in Nigerian universities.

9. The influence of proprietorship of institution on the predictive validity of PUME scores with

regard to first year GPA among undergraduates in Nigerian universities.

Significance of the Study

This research which examined the predictive validity of University Matriculation

Examination Scores is significant theoretically and practically.

Theoretically, it is significant because theoretical information had revealed that information

with the highest validity seems to have a point-to-point correspondence with the criterion. This

theory explains that the predictive validity of a test is increased to the extent that there is

congruence between measured skills and expected skills. The outcome of the finding is a test of

the validity of the University Matriculation Examinations Scores (UMES) to ascertain if there

is a correspondence between scores obtained at the point of entry and grades at the end of first

14

year of university education.

Furthermore, the addition of theoretical information on moderator variables provides an

increased understanding on the effects or influence of some contextual variables on the

relationship between predictors and criterion.

With respect to the practical significance of this study, the predictive validity of

UTME scores and PUME scores is significant in many respects and would mean different

things to different people. First it is an attempt to increase the knowledge base in the already

existing literature in predictive studies. Predictive studies are significant because they help to

explain the predictive strength of the focal predictor variables (UTME scores and PUME

scores) in relation to the criterion variable (the first year grade point average) which is a

measure of the cognitive abilities of students in Nigerian universities. Furthermore, it has

explained the influence of some categorical variables–namely gender, field or faculty of study

and proprietorship of institution in the relationship between university matriculation

examination scores (UTME scores and PUME scores) and first year grade point average. The

study of contextual variable is important because in some cases the predictive efficiency of an

independent variables and/or form of relationship with a dependent or criterion variable may

vary systematically as a function of another (variable or other variable

Secondly, the findings make contribution to research efforts that are geared or designed

towards improving the UTME and PUME test. Discussion based on the analysis of data

obtained directly from the respective institutions will help the examining authorities (JAMB

and the individual Universities) to reconsider some aspects of either their instrument or the

process of the administration of the test. Additionally, it has provided a comparative analysis of

student performance across institutions in terms of proprietorship, different fields of study and

the gender (sex) of the students. Since this study was a step forward in the traditional predictive

studies in which the relationship between predictor and criterion variable(s) is analyzed, it is

hoped that as the study explores the contextual variables, the interactive effect has provided a

15

greater insight into the complexities that surround the “low predictive phenomenon between

predictor and criterion variables. The analysis and explanation of the outcomes of the data has

also provided an x-ray of the relative strength and weaknesses of the UTME scores and PUME

scores.

In the same vein the result of this study will be useful to the legislators, university

authorities and JAMB. This is so because, the results provided will support the argument for

and against PUME, and for and against the continued relevance of the monopoly of JAMB’s

UME. This is crucial as the continued existence of the PUME has become a debate in the

National Assembly. More so, the universities which have had the misfortune of justifying the

PUME can have empirical data/facts to pursue their case.

Furthermore, future research on the predictive validity of university entrance examination

may also explore several contextual variables such as school climate, teacher quality,

infrastructure in school, number of student in school in relation to study facilities, age of the

institution, proprietorship including private owned universities, etc. in the prediction of college

performances from entry scores.

For parents, their misconceptions about the PUME screening tests as an avenue to enrich

university authorities and a tool for admitting students with close ties to school administrators

will be minimized.

Scope of study

The study covered universities in the South-South geopolitical zone of Nigeria. The study used

students who were admitted into 10 public universities through the selection examinations of

UTME and PUME. They were students who had completed their first year of study

successfully in federal and state universities and those whose records were available for

collection. The South–South has thirteen (13) universities established between 1970 and

2002. Out of these, there are four (4) federal universities, six (6) state universities and three (3)

16

private universities. Furthermore out of the 6 state universities, 3 are specialized universities of

science and technology.

The criterion variable is first year GPA, the focal predictor variables are UTME scores,

PUME scores and a combination UTME and PUME scores, while the moderator variables are

gender, field of study and proprietorship of institution (state university or federal

university).The study examined the predictive validity of UTME and PUME test scores with

regard to first year grade point average of undergraduates in universities in the South-South

zone of Nigeria as well as the influence of categorical variables on the prediction

Research questions.

1. What is the predictive validity of UTME scores with regard to first year GPA of undergraduate

students in Nigerian universities?

2. What is the predictive validity of PUME scores with regard to first year GPA of undergraduate

students in Nigeria universities?

3. What is the predictive validity of the combination of UTME and PUME scores with regard to

first year GPA of undergraduate students in Nigerian universities?

4. What is the influence of gender on the predictive validity of UTME scores with regard to first

year GPA of undergraduate students in Nigerian universities?

5. What is the influence of gender on the predictive validity of PUME scores with regard to first

year GPA of undergraduate students in Nigerian universities?

6. What is the influence of field of study on the predictive validity of UTME scores with regard to

first year GPA of undergraduate students in Nigerian universities?

7. What is the influence of field of study on the predictive validity of PUME scores with regard to

first year GPA of undergraduate students in Nigerian universities?

17

8. What is the influence of proprietorship of institution on the predictive validity of UTME scores

with regard to first year GPA of undergraduate students in Nigerian universities?

9. What is the influence of proprietorship of institution on the predictive validity of PUME scores

with regard to first year GPA of undergraduate students in Nigerian universities?

Hypotheses

This study was guided by the following null hypotheses (Ho) tested at p < 0.05.

1. The predictive validity of UTME scores with regard to first year GPA of undergraduates in

Nigerian universities is not statistically significant.

2. The predictive validity of PUME scores with regard to first year GPA of undergraduates in

Nigerian universities is not statistically significant.

3. The predictive validity of the combination of UTME scores and PUME scores with regard to

first year GPA of undergraduates in Nigerian universities is not statistically significant

4. The predictive validity of UTME scores with regard to first year GPA of undergraduate

students do not differ significantly according to gender.

5. The predictive validity of PUME scores with regard to first year GPA of undergraduate

students do not differ significantly according to gender.

6. The predictive validity of UTME scores with regard to first year GPA of undergraduate

students do not differ significantly according to field of study.

7. The predictive validity of PUME scores with regard to first year GPA of undergraduate

students do not differ significantly according to field of study

8. The predictive validity of UTME scores with regard to first year GPA of undergraduate

students do not differ significantly between federal-owned and state-owned universities.

18

9. The predictive validity of PUME scores with regard to first year GPA of undergraduate

students is not different significantly between federal-owned and state-owned universities

19

CHAPTER TWO

LITERATURE REVIEW

The literature review is arranged under the following sections:

1. Conceptual framework

a. Concept of Unified Tertiary Matriculation Examinations (UTME)

b. Concept of Post-Universities Matriculation Examinations (PUME) Screening tests in

Nigeria.

c. Concept of test validity

d. The concept of predictive validity

e. Procedure for calculating predictive validity

f. Factors affecting predictive validity

g. The concept of moderator variables

h. Statistical tests for detecting and estimating moderator influence in predictive studies

i. Factors affecting the estimate and analysis of the influence of moderator variables.

2. Theoretical Framework

a. Point-To-Point Theory

b. Classical Test Theory

3. Empirically Related Studies.

a. Studies on predictive validity.

b. Studies on moderator variables

c. Studies on UTME scores and PUME scores

Summary of Review of Literature

Conceptual framework

The Concept of Unified Tertiary Matriculation Examination (JAMB-UTME)

The Unified Tertiary Matriculation Examination (UTME), as it is now called, is a

selection achievement test for candidates seeking admission into Nigerian universities. The

20

questions in the different subject areas are developed, administered and graded by the Joint

Admissions and Matriculation Board (JAMB) which was established by Decree No. 2, 1978 by

the then Federal Military Government. Prior to the conduct of the UTME, each of the existing

universities conducted her own entrance or matriculation examination for candidates seeking

admission. Each candidate enters for English Language and three other subjects relevant to

his/her chosen course of study. The total score a candidate is expected to obtain is 400 points

One of the several reasons for the UTME was the need to unify the matriculation

examinations that were being conducted by the different universities at that time. For instance

Adamu (1994) stated that the establishment of the Board was as a result of the initiative of

Nigerian Committee of Vice-Chancellors (CVC) which was worried about multiple

applications for admissions and multiple offers of admissions into Nigerian universities that

was granted to students.

Secondly, and perhaps the most important factor was the need to create national harmony

and cohesion. Asein and Lawal (2007) observed that apart from centralizing the admission

processes, JAMB as one of the post-civil war reconstruction institutions was intended to

provide a platform for students to be admitted into universities in states other than their states

of origin or region thereby fostering the much needed national unity among the tribes in the

country which was recovering from a civil war at the time of its establishment.

The Concept of Post Universities Matriculation Examinations (PUME) screening tests

The Post-Universities Matriculation Examination (PUME) screening tests as the name

suggests are exercises conducted by individual university to further reassess candidates who

chose the particular university during the nationally conducted Unified Tertiary Matriculation

Examination (UTME). Candidates who sit for these screening tests are applicants seeking for

undergraduate admission into the university in the current year of academic activities. The

centre for each PUME examination is centralized within a campus or campuses of the

university. There are certain criteria which a candidate would meet in order to sit for the

21

screening test of the particular university. First, the candidate may have sat for the UTME in

the current application year and obtained a university dependent cut-off score to qualify for

entry into the PUME screening test or exercise (200 for most Federal universities and about

180 for most state universities in the UTME). Secondly, the particular university may have

been chosen as a first or second choice. It is important to note that the PUME screening tests,

for now, are not complementary to the UTME, since candidates not qualified to enter in for the

PUME without the UTME scores. Furthermore candidates are admitted into the preferred

university based on the aggregate performance in the two matriculation examinations.

Obviously, the idea of the PUME is to provide additional information about the commensurate

ability of the student as reflected in the UTME scores to ascertain if the scores the candidate

obtained reflected his/her actual ability. According to Oyedeji (2011) the PUME screening test

is a quality control measure designed by the universities in Nigeria to select the best and most

qualified candidates for admission into Nigerian universities (especially public universities)

and to instill discipline in the university admission process

Similarly, Bassey, Joshua and Joshua (2010) stated that the university administrators seemed

base their argument for introducing the PUME on poor quality of students admitted into the

universities. In other words, the quality of the students produced by the universities is a

function of the quality of the students who were admitted through the matriculation

examination (UME).

According to Ifeanyi (2011) the PUME screening tests provide students the opportunity

to be admitted on merit rather than on special marks obtained from special centre’s and

fraudulent practices. Similarly Lawal, Ossai and Ekundayo (2010) stated that the PUME

screening tests were introduced in the university admission system to raise the quality of

students who seek for admission into the universities because there were discrepancies between

the high UME scores some students obtained and their actual performance upon admission or

enrolment in the university of choice. In the same vein, Owolabi (2009) stated that the PUME

22

was a child of circumstances because of the suspicion that undergraduate students GPA’s of

Nigerian universities did not justify their JAMB/UTME scores. Summing up the arguments,

Obioma and Salau (2007) stated that the justification for the conduct of the Screening exercises

was because there was a consistent low correlation between candidates UTME scores and

subsequent university grades as represented in their CGPA’s.

The concept of test validity

Determining the validity of a test is one of the ways of gathering information from such test to

ensure that the test is accurate. Walk (2005) stated that an understanding of the concept of test

validity is important, because it is the most important criterion, for it determines whether the

test truly measures what it is expected to measure. According to Ebel and Frisbie (1991), the

understanding of the concept of test validity is the foundation for test fairness and the proper

administration and use of tests and other instruments of assessment. Messick (1980) describes

validity as the foundation of testing. That is to say, the quality of a measurement instrument is

determined by its validity. There is a relationship between validity and university entrance

examinations. An entrance examination, which is an instrument for selecting candidates for a

given programme is expected to provide evidence that those successful in the selection

examination or process will do equally well (according to the degree of their success) in the

programme they are admitted. Invariably, the quality of the pre-selection examination is an

evidence of its validity. In other words validity is the evidence of test quality from the

judgment made on the test score obtained at a particular time. For instance, Kane (2008) stated

that the need for the validation of test is derived from legal, scientific and social expectations

that the claims, decisions and judgment to be made based on a (particular) test score justifiable.

Early writers such as Guilford cited in Garson (2008) stated that validity can be equated

with establishing that constructed scales have correlation with a dependent variable in an

intended manner. The author stated that the codification of validity into four types namely:

content validity, construct validity concurrent validity and predictive validity (the latter two

23

being referred to as criterion related validity) came into being in 1954.

However, in recent times there have been strong arguments concerning the unitary theory of

validity as opposed to those who uphold the traditional typology. Within the unitary theory,

there are those who argue that construct validity is the only validity and all other types are

purely dimensions of construct validity in terms of response to the questions raised and

answers given. There are others in the unitary group who believe that content validity is the

only form of validity and all other types are forms of content validity subsumed under it.

Messick (1989) cited in Garson (2008) and Sireci (2007) focused on the interpretation and uses

of test scores and argues that construct validity is the only form of validity with multiple

standards for assessing various components; relevant content, based on sound theory or

rationale, internally consistent body of items, externally correlated with related measures,

generalizable across populations and time and explicit in its social consequences on the test

takers. The authors argued that content validity focuses on labeling constructs; internal validity

focuses on bias on research design and statistical validity focuses on assumptions of meeting

empirical procedures. Furthermore, Ross (2007) also holds the construct-validity unitary

concept. The author argued that historically validity involves three steps which are all

embedded in construct validity, that is, theorizing to develop an hypothesis regarding the

behaviour of a person during a testing situation, gathering data and drawing inference from the

data developed to test the hypothesis.

The other school of thought on the unitary concept of validity focuses on content. For

instance Lissitz and Samuelson in Kane (2008), Ross (2008), Sireci (2008) and Gorin (2008)

argue that content validity is an umbrella term for validity and referred to the other types of

validity (criterion-related validity, theory-based evidence, and evidence on consequence) as

indicators of validity and went further to state that validity is a property of the test independent

of its interpretation or use of the test. Content validity, the authors argues provides operational

definition as indicators of score meaning.

24

However, authors such as Nworgu (2006), Gorin (2008), still hold the traditional

meaning of validity as the extent to which a test measures what it is intended to measure. That

is the test items must measure some intended objectives developed from a hypothesis of the

object measured and the purpose of the test which will provide a basis for judgment about its

validity. For instance, Ferrara in Gorin (2008) placed validity in two terms:

knowledge, skills, processes and strategies (KSPS) about which the test

user would like to make inferences and the observed KSPS which are

applied by the examiners when solving an item (p460).

Some of the traditionalist such as Kane (2008) makes a case for argument based approach to

validation and defined validity as an evaluation of the interpretation and uses of test results.

That in evaluating theory, it is good to operationally define meaning. The author stated that the

argument based approach to validation specifies the inferences and assumptions implicit in an

interpretation or use of test scores and evaluates the possibility of these inferences and

assumptions using appropriate evidence which for or against provides an overall evaluation of

the validity.

In any case, both the content-specific proponent of validity and the construct relevant

authors have all accepted that there are four types of validity, namely: content validity,

construct validity, predictive and concurrent validity (criterion-related validity) though they

emphasized that the criterion-related validity and construct validity are subsumed under

content validity while construct proponents argue that criterion-related validity and content

validity are subsumed under construct validity. For the purpose of this study as Nworgu (2006)

observed there are four types of validity, namely content validity; construct validity

(discriminant validity and convergent validity), predictive validity and concurrent validity

(criterion-related validity).

25

Types of validity

Content validity

According to Cronbach and Meehl (1955) content validity occurs whenever we assess the test

items as representing a sample of universe of items in which the investigator is interested.

Also Nworgu (2006) stated that content validity occurs when the experiment provides adequate

coverage of the subject being studied. This includes measuring the right things as well as

having an adequate sample. Samples should be both large enough and be taken for appropriate

target groups. The perfect question gives a complete measure of all aspects of what is being

investigated. However in practice this is seldom likely, for example a simple addition does not

test the whole of mathematical ability. Content validity is related very closely to good

experimental design. A high content validity question covers more of what is sought..

Construct validity

According to Cronbach (1955), Denga (1987) and Nworgu (2006) construct validity is

involved whenever a test is to be interpreted as a measure of some psychological construct,

attribute or quality that are assumed to be represented in a test performance to explain some

psychological theory. Construct validity occurs when the theoretical constructs of cause and

effect accurately represent the real-world situations they are intended to model. This is related

to how well the experiment is operationalized. A good experiment turns the theory (constructs)

into actual things that can be measured. Sometimes just finding out more about the construct

(which itself must be valid) can be helpful. Construct validity is thus an assessment of the

quality of an instrument or experimental design. It says 'does it measure the construct it is

supposed to measure'. Without construct validity, one is likely to draw incorrect conclusions

from the experiment. Construct validity has two forms: convergent validity and discriminant

validity.

Convergent validity occurs where measures of constructs that are expected to correlate do

so. Convergent validity is the degree to which concepts that should be related theoretically are

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interrelated in reality.

Discriminant validity occurs where constructs that are expected not to relate do not, such

that it is possible to discriminate between these constructs. Discriminant validity is

the degree to which concepts that should not be related theoretically are not interrelated in

reality. Convergence and discrimination are often demonstrated by correlation of the measures

used within constructs. Convergent validity and discriminant validity together demonstrate

construct validity.

Predictive validity

Cronbach and Meehl (1955), Fitzgerald (1999), and Garson (2008), stated that predictive

validity is intended to predict how a person will perform at a later date on a different of

assessment of his/her abilities using the performance measures of the present. Asher and

Sciarrino (1974) stated that predictive validity is a measure of agreement between results

obtained by an evaluated instrument and results obtained from more direct and objective

measurements, which is often quantified by the correlation coefficient between the two sets of

measurement obtained for the same target population. Therefore, predictive validity is an

attempt to approximate the future performance of an individual using present performance.

Nworgu (2006) argued that predictive validity determines how accurate an instrument of

measurement administered now on a subject or group of subjects can predict a criterion

measurement. Predictive validity is an indicator of the capacity of how a test taken now will

mirror or predict the future performance and behaviour of an examinee or test taker after an

exposure to the future objectives or programme. Some authors have looked at predictive

validity as a determination of statistical properties of a test. For instance, Thorndike and Hagen

(1961) states that predictive validity is primarily an empirical and statistical evaluation of a test

and an indicator of the degree of correlation of the test's score with some chosen criterion

measure of success. Theoretically, the more the correlation, the more effective the particular

test mirrors the criterion that was measured. This idea is also shared by Ahmann and Glock

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(1958) who stated that an instrument possesses a predictive value to the extent that predictions

of future pupil behaviour made on the basis of the instrument are found to be accurate. This

measures the extent to which a future level of a variable can be predicted from a current

measurement. Also, differential validity and incremental validity have been identified as

two forms of predictive validity.

Differential validity is the outcome of a computed validity coefficient for different

subgroups such as gender, colour, race of examinees in which there are significant variations

among the different subgroups.

Sirenci and Talento-Miller (2006) stated that a test is said to have exhibited differential

validity, if the utility of a set of predictors does not hold up over particular groups of examinees

(e.g., male and female) which ordinarily shouldn't be so. Linn (1978, 1982, and 1984) defined

differential validity as the differences in the size of the correlation or validity coefficients for

different groups of examinees. This is measured by fitting separate regression lines for each

group and then testing for statistically significant difference between the slopes of intercept.

Also Young (2001) explained that differential validity refers to the situation where a test

is predictive for all groups but to different levels of validities. In other words, the test lacks

equivalent validities for the different groups of examinees. The question about differential

validity is, therefore, a question about whether the correlation between the predictors and the

criterion are different for the different identifiable groups of examinees. The groups in this

respect could be gender, faculty of study, type of institution, age of the establishment of the

institution, etc. On the other hand, differential prediction refers to the situation where the

derived prediction equations for the different subgroups of examinees are significantly

different from one group to another group. The question about differential prediction,

therefore, is a question that relates to whether the predictions models obtained for the different

subgroups of examinees is different. Linn (1978, 1982), Shepard (1987) stated that differential

prediction is determined by comparing regression systems for equality of regression slopes and

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equality of regression intercepts in the respective prediction equations across the groups of

interest.

Linn (1982) stated that both differential validity and differential prediction are important in

the validation of the scores on a test. However, differential prediction is the more crucial

because differences in prediction have more relevance when considering fairness in selection

than do differential validities. In any case, research on both differential validity and differential

prediction are important because they consistently show evidence of differences in the

prediction equations across subgroups of examinees On the other hand, Kyei-Blankson (2005)

defined differential prediction as a statistical research outcome where the prediction equation

and standard of errors of estimate obtained from analyses have significant variation among

different subgroup of examinees. That is to say, a single prediction equation will not be useful

for the different subgroup of examinees.

Incremental validity on the other hand refers to the degree in which a test improves on

decisions that can be made from existing information, such as the base rate of the attribute

being measured and other measures that are available. The term is also used to denote the

validity of a test arising from successive refinements or improvements of it in the light of

experience or evidence, usually including the removal or replacement of test items that turn out

to be problematic or that yield different results from the others.

For example, Bridgeman (2002) while undertaking a meta-analysis of the writing tests of

the SAT I found out that in four colleges in New Jersey, the incremental validity of writing

tests to the prediction of FYGPA or English course grades ranged from 0.004 to 0.016 for the

four colleges. Furthermore, Bridgeman and Lewis (1991) established the fact that writing tests

had greater predictive value in courses that were more likely to use essays in the determination

of course grades, than others, which did not necessarily use essays in the determination of

course, grades such as in the engineering.

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Procedure for calculating predictive validity

Over the years, res