A COMPARATIVE STUDY OF STUDENTS ACADEMIC CONCEPTS USING JAMB SCORES AND CGPA, (A CASE OF BENUE STATE UNIVERSITY, MAKURDI)

A COMPARATIVE STUDY OF STUDENTS ACADEMIC CONCEPTS USING JAMB SCORES AND CGPA, (A CASE OF BENUE STATE UNIVERSITY, MAKURDI)

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ABSTRACT

This research compare the students’ academic performance using JAMB scores and CGPA in Benue state University Makurdi, and the level at which the divergence in grades started is of paramount importance. Two faculties in the institution were selected. The multiple regression analysis carried out shows that JAMB scores as well as yearly GPAs can predict the final CGPA. From the student (t) distribution it was observed that the model contribute information to the yearly GPAs. A correlation analysis revealed that there is both positive and negative weak correlation between JAMB scores and final CGPA for the two groups. From the hypothesis tested it was observed that: there is a relationship between JAMB scores, yearly GPA and the final CGPA for both 21 and 22 graduates. Graduates with 21 differ greatly from those with 22 at graduation

INTRODUCTION

The system of academic in Benue State University (BSU) was established on the ground that knowledge should be disseminated without hindrance. Candidates are admitted into the first degree regular programmes of the University through the Joint Admissions and Matriculation Board (JAMB) examinations, direct entry, pre-science programme, continuing Education Programme (CEP), and inter-university transfer. But the researcher based mainly on JAMB as a mode of admission of students in the University. This is because this body of examination (JAMB) was established by the Federal Government of Nigeria through Act 2 of 1978 to regularize the intake of students into the Universities and solve the multiple admissions problem given to some candidates at the expense of others. Like other examination bodies in Nigeria, JAMB has been subjected to a series of criticisms. But the researcher is not interested in these criticisms. But is interested in finding out at what level during the course of study of students admitted through JAMB (with high or low scores) did divergence in grades begin, when compared with their yearly cumulative grade point averages.

Examination in Nigerian schools is dated back to the arrival of formal education. As a former British colony, the system of examinations in Nigeria took after the British system. In the University setting, success in and examination is being assessed through the cumulative grade point average obtained by students in all courses registered from year one to the final year. As such, a student is deemed to have performed very well to the level of second class upper division if the cumulative grade point average is between 3.50 and 4.49, or first class if cumulative grade point average is 4.50 and above on a 5-point scale. Hence, the cumulative grade point average determines the success level of a student from one semester to another. The grading of the cumulative grade point average is such that 4.50 and above is first class, 3.50 to 4.49 is second class upper division (21), 2.40 to 3.49 is second class lower division (22), 1.50 to 2.39 is third class, 1.00 to 1.49 is ordinary pass degree while below 1.00 is failure.

Statement of the Problem

Over the years there has been a sharp disparity between the students’ academic performance at entry point and their final CGPAs. At a certain level during the course of study of students admitted into the University, there comes a divergence in grades. To sort out the level at which this divergence started and to identify whether there exists a relationship between the entry point scores (JAMB Scores) and the final CGPAs is the most concern of this work. One wonders at what level did this divergence start. This is the problem of the study. The researcher is interested in only those that graduated with a second class upper division and a second-class lower division. To address the stated problem, the following research questions were raised:

1.      At what level did the divergence in grades set in?

2.      Is there any equality between the grade point averages of students with 21 and those with 22?

3.       Is there any correlation between students’ grade point at graduation and their entry point scores?

Aim and objectives

The aim of this research work is to predict the students’ academic performance using JAMB scores and CGPA. Thus the objectives are;

1.       To determine when the ‘divergence in grade’ started to appear in their course of studies by examining the contributions of their 4th year work, 3rd  year work, their 2nd year work, their 1st year work, and their JAMB scores which  represents their “entry behaviour”;

2.      To see whether the final CGPA can be predicted on the basis of the variables mentioned in 2 above;

3.      To test the equality of the two covariance matrices for 21 and 22 students;

HYPOTHESES

The following hypotheses were formulated to aid in solving the aforementioned problems and would be tested for rejection or acceptance at 5% level of significance:

1. H0: there is no relationship between the entry point scores, the yearly GPAs and the final CGPA of graduates with 21 and 22,

H1: There exists a relationship between their entry point scores, the yearly GPAs and the final CGPA of graduates with 21 and 22;

2. H0: Graduates with 21 do not differ greatly from those with 22 at graduation,

H1: Graduates with 21 differ greatly from those with 22 at graduation.

REVIEW OF THE LITERATURE

Daniels, et al (1970), conducted a research about education in Europe on the screening of students, problems of assessment and prediction of academic performance. Here they defined the term academic success as the scholastic standing of a student at a given moment. It refers to how an individual is able to demonstrate his or her intellectual abilities. This scholastic standing could be explained as the grades obtained in a course or groups of courses, and the  way in which a student has attained the grades including the time he or she passed examination two after passing examination one. They therefore argued that a prediction of a future examination result could be made with reasonable success on the basis of the results of an earlier examination and that grades may serve as prediction measures and as criterion measures. As a measure of prediction, Dockery, (1986) investigated the effects of intelligence quotient on academic achievement and found that achievement scores increased as the intelligence quotient increased. Eysenck, (1995) agreed with this finding and remarked that intelligence quotient testing has been extremely successful on the practical level predicting academic success from early childhood to university degree. Findings made by Al-shorayye, (1995) and Adeyemi, (1998) led credence to this point. Findings made by Peers and Johnston (1994) confirmed the validity of the number and grade of passes in the year and final year University performance. Findings made by Gay (1996) in the USA also confirmed the fact that high school grades are predictors of college grades. In the same vein, Entwistle and Wilson (1977) too, found that students with three ‘A’ level passes did better than students with two in the university. St. Thomas, (1982) studied the relationship between the first semester grade point average (GPA) of Nursing students at Vermont College and their scores on the Nursing State Board examination. The study sought to determine whether a GPA of 1.75 (which is currently required for progression in the nursing program beyond the first semester) could predict success in the State Board Examination. The study revealed that while there was a significant relationship between GPA and Nursing Board Score, a GPA of 1.75 failed to predict success in the examination. However, on the basis of a linear regression analysis, she observed that failure in the Nursing Board examination could be predicted with a 95% level of confidence for those students with a first semester GPA below

1.5. Based on her findings, she recommended that the GPA required for continuation beyond the first semester be lowered from 1.75 to 1.50. Nwokike (2001) studied the relationship between JAMB Scores and Final Grades of Federal Polytechnic Oko Diplomats’. From his analysis based on the correlation between the variables, he observed that there was a weak positive correlation between JAMB Scores and Final Grades of Federal Polytechnic Oko Diplomats’ and concluded that both JAMB scores and Diplomats’ Grades were low. From these observations, he recommended that centralized data banks within tertiary institutions should be established. He again suggested that there should be a connection of tertiary andresearch institutions to the internet for information flow and exchange. He went further to recommend a re-organization of JAMB, Academic departments and Examination/ Record departments of Federal Polytechnic Oko so as to make them more relevant and functional. He finally recommended the acquisition of statistical packages (computer software) by tertiary and research institutions for use in statistical analysis. Sulaiman and Mohezar (2006) identified key predictors of Master of Business Administration (MBA) students’ academic performance. The authors measured performance by the students’ cumulative grade point average. They found out that a student’s undergraduate grades are the best predictors of their MBA academic performance followed by the undergraduate discipline. They also found that age, ethnicity, gender and years of work experience had no bearing on academic performance. Ray (2008) in her study to determine the correlation between High School Assessment Program (HSAP) Scores and various measures of classroom achievement such as overall GPA, end of course scores and SAT/ACT Scores of Berea High School (BHS). Surveys were also distributed to all current BHS teachers. These surveys were designed to determine teachers’ perspective of the HSAP as a measurement of BHS student’s achievement. The researcher discovered from her analysis that HSAP scores correlate strongly with other measures of student’s achievement. While all correlations were above r=0.5, the weakest correlations were those involving GPA .Survey results, according to her findings show that teachers feel uncomfortable while preparing students for the HSAP. She concluded her findings by saying that the results show that HSAP is a valid assessment of students. In her recommendations, she suggested that teachers and administrators at Berea High School need to examine the causes of the weaker correlation of GPA versus HSAP scores. In addition, teachers should be trained to better prepare students for the HSAP. Elsevier (2009) carried out a study to identify the relationship between academic scores of school subjects and the performance in national qualified examination for registered professional nurses (NQEX – RPN). From the analysis done by the researcher, the following were observed:

1)      Out of thirty four subjects which were included in the two year nursing curriculum under study, nine nursing subjects were of statistical significance and were positively related with the performance in NQEX-RPN;

2)       Year 1 grade point average (GPA) of nursing subjects was significantly correlated with the performance in NQEX – RPN but not year 2 GPA;

3)      The performance of two subjects in NQEX – RPN, namely Fundamental Nursing and Psychiatric – Community Nursing, were not significantly correlated with their related school subjects. The conclusion drawn from the findings by the researcher is that the academic scores in only half of the nursing subjects were found to be weakly associated with the performance in NQEX – RPN, although the association was statistically significant. Also, performance in NQEX – RPN was not associated with the final year GPA. Thus, the nursing curriculum and teaching contents may need to be re-designed in order to match with NQEX – RPN.

Groove & Wasserman (2004) carried out a study on individual semester – by – semester undergraduate grade point average for each of the eight semesters of the collegiate academic life cycle for five entire student cohorts for the classes of 1998, 1999, 2000, 2001 and 2002 at a large private University in North East USA. In their study, they observed a “Check-mark” pattern: Students’ grades fell in the second semester, rose thereafter and slumped in the last academic terms. Attrition and participation in the Greek system explain over half of the longitudinal change in academic achievement. A comparison of the five cohorts of students by these researchers indicate a rate of grade inflation comparable to that obtained for multi school studies covering the period 1960 to the late 1990s.

According to Kirby, et al (2005) in their study on the relationship between college grade point average (GPA) and discount rates, observed that their findings were consistent with the idea that people who discount the future more highly tend to show poorer academic performance. Their findings also showed that discount rates for real delayed monetary rewards were consistently negatively correlated with GPA. Nippert (2001) examined the effects of, academic and social integration, external influences, and institutional satisfaction on the education degree attainment of students who began their college experience at two-year – colleges. The findings of his study were consistent with previous research and confirmed the relationship of college academic activities and college grade point average with student persistence. He also observed that students’ willingness to re-enroll in their fresh men college was also found to positively influence educational degree attainment. Plant et al (2005) studied on why study time does not predict grade point average across college students. Their work drew upon the theoretical frame work of deliberate practice in order to clarify why the amount of study by college students is a poor predictor of academic performance. They proposed a model where performance in college, both cumulative and for a current semester was jointly determined by previous knowledge and skills as well as factors indicating quality (e.g. study environment) and quantity of study. The findings support the proposed model and indicate that the amount of study only emerged as a significant predictor of cumulative GPA when the quality of study and previously attained performance were taken into consideration. Strauss & Volkwein (2002) compared students’ performance and growth in 2– and 4- year institutions. In their study, they examined the organizational characteristics of higher education institutions in relationship to student performance and growth. The study found that organizational measures of mission, size, wealth, complexity and selectivity were statistically represented by the 2-year versus 4-year college mission. Findings indicate that 2-year and 4-year campuses indeed exert significantly different influences on undergraduate GPA and self- reported intellectual growth. They also observed that High School percentile rank and college classroom experiences were better predictors of cumulative GPA at 4-year institution while student effort was a better predictor of GPA at 2-year institutions. Whereas the most important predictors of cumulative GPA include: pre college measures such as high school percentile rank and standardized Assessment Test score (SAT score). The most influential predictors of students’ intellectual growth are campus experiences including classroom vitality, peer support, student effort, commitment and involvement. They concluded by saying that when other variables have been controlled, students at 2-year institutions receive   and students at 4-year campuses experience more growth. Williford et al (2001) investigated the relationship between participation in an extended orientation course and student academic performance, student retention and student graduation. Ten years of participants in Ohio University’s freshman “University Experience” course were compared with comparable non- participants. In the comparison of student academic performance, the effects of students’ prior academic achievement and students’ measured academic aptitude were controlled. First-year retention and four, five, and six-year graduation rates were compared. In most years of the study, participating students’ year-end GPA was higher than non-participants’, retention rates were higher, and four, five and six-year graduation rates were higher. Ubokong (1993) found that performance in a lower level examination was significantly related to the performance in a higher level examination in his study on the relationship between the performance (academic) at a lower level examination and that of the higher level examination. Other researchers, Omonyo (2001) and Adelugba (2003) found no significant relationship between the performances in lower level examinations and performance in higher institutions. Adeyemi (2009), investigated on the mode of entry as a predictor of success in the final year bachelor of education degree examinations in Universities in Ekiti and Ondo States, Nigeria. The findings revealed that pre-degree mode of entry are the best predictor of success in the final year bachelor of education degree in the Universities.  Considering these divergent findings, this study is intended to examine the predictive value of students’ academic performance in Benue State University (BSU) through mode of admission in relation to yearly grade point average and final cumulative grade point average. This study will determine the distance between the entry points scores (JAMB scores) and the yearly grade point averages and at what level the divergence in grades start.

METHODOLOGY

This research is necessary since the study is based on the relationship between the JAMB scores, the yearly GPAs and the final CGPA of graduates of Benue state University (BSU) Makurdi and thus, the attempt at determining whether there is a relationship between the entry point scores and the final CGPAs of the graduated students

 Population of study:

There are six (6) faculties in Benue state University Makurdi, as at the time of research; four faculties out of these six have already graduated students. Therefore all the four faculties form the target population. Out of this population a sample of two faculties was selected from which two departments each were also selected. Altogether samples of four departments were selected for this study. Another sample of thirty (30) students who made second class upper division (21) and another 30 who made second class lower division (22) was selected from all the departments selected. This makes it a total of 60 students (graduates) from each department. Therefore 60 students X 4 = 240 students (graduates).

The faculties, the departments and the number of students (graduates) chosen for this study are shown in the table below;

Table 1.0

Faculties

Departments

Number of 2nd class upper division

Number of 2nd class lower division

Arts

Psychology

30

30

Sociology

30

30

Management

Accountancy

30

30

Economics

30

30

Research procedures

For the collection of sample population of students (graduates) grade point averages, a multistage sampling procedure was applied. These were obtained from the departments selected for this work. The JAMB scores of the students (graduates) were also collected alongside their yearly GPAs and final CGPAs.


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