The Expected CGPA formula

Journal of Educational Research in Developing Areas, 2022

INTRODUCTION: Since the introduction of credit unit system in our tertiary institutions, indices of performance (Cumulative Grade Point Average (CGPA) has been used as an instrument of assessing students' performance from one semester to another. PURPOSE: The purpose of this study is to interpret mathematically the meaning of "up to date total credits units registered" as in the definition of CGPA and its implications on students' performance in the award of certificate. METHODOLOGY: The study adopted the comparative research method, the student information book (student Handbook) of various institutions were used as guide on how these institutions defined CGPA. Example was given to illustrate how calculations are done based on the definition given using a Diploma program which is a two years' program. RESULTS: The up-to-date total credit units registered may include the carry-over courses which will be included in computing the CGPA of that semester. However, when this method was applied to two students who had scored the same grades, one graduating in normal two years of the program and the other one in three years of the same program due to carry-overs, their final CGPAs were not the same even though they had the same grades in all the courses (see Tables 2, 4, 6 & 7). But when "the up-to-date total credit units prescribed" was used, their final CGPAs were the same (see Tables 8 & 9). RECOMMENDATIONS: Since the graduates from the various institutions do vie for the same openings on the job market even though different methods were used in computing their CGPA which determined the class of certificate they hold, it is necessary therefore, that the method of computing the CGPA be standardized in this country. This can only be achieved if explicit definition of CGPA is given.

Grade Point Average (GPA) and Cumulative Grade Point Average (CGPA) are very crucial to students in presenting their academic performance. However, it is quite tedious and time consuming to forecast GPA and CGPA based on recent CGPA manual calculation. Thus, GPA and CGPA Forecast Calculator(GCFC) is developed to enhance the forecasting process and output. GCFC will be beneficial to many users such as students, Academic Advisor or known as “Penasihat Akademik” (PA) and administrator of the higher education. For students, GCFC can help them in forecasting their GPA and CGPA for the coming semester based on current semester CGPA result and Credit Hours. The result based on GCFC can be an indicator for students’ coming academic performance and this can motivate them to work harder in order to achieve good result and at the same time to be graduated on time (GOT). For PA, GCFC can help them in motivating the students to obtain excellent results and GOT. GCFC can also give benefit to the ...

Information and Knowledge Management, 2013

Since the advent of course system of education in tertiary institutions world-over, Cumulative Point Average (CGPA) has been in use as an Assessment Instrument instead of Cumulative Weighted Average Mark (CWAM). Consequently, mapping of percentage marks into an n-grade points system which is required to generate the much needed CGPA has become necessary. Countless methods of mapping have been witnessed across different tertiary institutions. In addition, the number of grade point, 'n' varies from institutions to institutions. While it is a universal fact that 'n' can take any value less than 100, it is nevertheless important to know that the value of 'n' has never been greater than 12. In Nigerian tertiary institutions, the value of 'n' varies between 4 and 7 while 5 is the most common. However, simply equating 'n' to 100 is not sufficient to convert the percentile system to an n-grade points system in order to generate the required CGPA. It is discovered that there is no sound mathematical method employed to relate the CGPA ranges normally used to classify degree to the percentage scores earned by individual students. This paper (paper 2) is primarily written to establish the required parameters and the most suitable format of an n-grade points system which is referred to as a Non-Graded Fail Grading System with a fail grade, 'F' assigned a zero value (NGF/GS F=0) while another paper (paper 3) presents the development of the required mathematical relationship between CGPA and percentage scores ranges. The grading systems of a few universities in Nigerian are analysed in this section to see how much they comply with the principles and theory presented in papers 2 & 3. The National Universities Commission (NUC)'s directives of Minimum Academic Standard (MAS) are also considered along. 2.1 University 'A' (UA) Grading System The grading system being used by University 'A', UA (Table 1) is examined and compared with the principles articulated in papers 2 & 3. Their basic parameters (m, n, [M H + 1], M L) are used to calculate the expected CGPA ranges (when F = 0 & d = 1 and F = d =1). This is presented in Tables 2 and 3

F1000Research

Cumulative grade point average (CGPA) is a system for calculation of GPA scores and is one way to determine a student's academic performance in a university setting. In Nigeria, an employer evaluates a student's academic performance using their CGPA score. For this study, data were collected from a student database of a private school in the south-west geopolitical zone in Nigeria. Regression analysis, correlation analysis, and analysis of variance (F-test) were employed to determine the study year that students perform better based on CGPA. According to the results, it was observed that students perform much better in year three (300 Level) and year four (400 Level) compared to other levels. In conclusion, we strongly recommend the private university to introduce program that will improve the academic performance of students from year one (100 level).

The Quality Assurance and Accreditation Council has proposed a common credit and qualification framework for Sri Lankan University system in order to maintain the consistency and comparability of university level qualifications, and to promote student mobility by creating more flexible arrangements for students learning. To minimize the drastic variations, all degree programmes were categorized in to six and the framework reworded for each. This study only focuses on the framework developed for Arts, Humanities and Social Sciences degree programmes. This study was mainly based on generated data. The marks of students were generated from a multivariate normal distribution to accommodate the correlation of the marks. Marks of thousand students for fourty subjects were generated using Minitab 14 and then they were converted into grade points. Final results, (class/pass) obtained under Cumulative Grade Point Average (CGPA) method and final average method were then compared. The reason behind using hypothetical data instead of having actual data was the inability of obtaining actual results data. The research findings illustrate the inefficiency of the proposed new method as it always underestimates performance of students, relative to the existing final average method of deciding on final class/pass of student. The cutoff CGPA values were redefined so as to maintain consistency with existing method of Final Average.

Ranking tertiary institutions provides a good motivation, since it engenders healthy competition among stakeholders to strive for excellence. The issue of concern now might be finding a fair measure of the various criteria for this purpose. When institutions are endowed differently, then one fair criterion of assessing them would be to find an algorithm to measure their academic impart on the students by the level of output during the tertiary education. At the moment, there is the GPA which measures the output of the students during this period. What remains is to find a similar measure – a default estimate of students’ output, using their in-take grades, so that the difference between the CGPA and the in-take grade index (SIGI) will provide some measure of the level of impact. A departure, positively or negatively, from the SIGI will determine how well the student was affected, giving the prevailing conditions specific to the institution. This is the objective of the study. The study proposed an algorithm using the procedures of performing principal component factor analysis to obtained weights specific to the six subject areas used to admit students into tertiary institutions, by subjecting the entire data of a group of students to factor analysis procedures. These weights are subsequently used in the final formula to compute the SIGI, after testing and ascertaining the fitness of the factor model. To test the algorithm, records of some 618 past students of Ho Polytechnic, taken randomly from the past three academic years, were used. It was revealed that the level of output during tertiary education has dropped or increased marginally than those who had the same increased tremendously. The model could be of great help to regulatory authorities in assessing tertiary institutions, so that appropriate intervention could be made for better academic performance. It could also be used as admission criteria when the grades of group of students are analysed to determine who to admit. Also, after studying the trend for some time within an institution, certain class of students could be given the chance if there is evidence from the model that they can do better when admitted. The model is hereby recommended to stakeholders in the educational front. The focus of subsequent studies would be to apply similar robust methods, used here, to diagnose the current GPA system as a measure of the student’s academic performance in terms of its robustness, validity, fairness and accuracy. This is in line with proposing an alternate grading system which satisfies the criteria of robustness, validity, fairness and accuracy. Keywords: Education; Factors; Grading; Academic Impart; Factor Loading; Performance.

Asian Journal of Probability and Statistics

This paper considered the effect of student's entry requirements, Secondary school type and Cumulative Grade Point Average of the 2014/2015 final year students of the four faculties of the Taraba State University. Primary data was collected through the use of a questionnaire from the respondents of the selected programmes from each faculty. Correlation Analysis was carried out on the students', CGPA's at lower levels, UTME score, SSCE results and Secondary school type. It was discovered that only CGPA at the end of 300 level has significant relationship with CGPA at the current level while the stepwise regression analysis shows that only CGPA at 300 level is the best predictors of students' graduation CGPA all other variables are not significant and regression analysis was used to established models for predicting graduation CGPA. Based on the findings of the study, it can therefore be concluded that entry requirements have no effect in determining the performance...

International Journal of Advanced Research in Innovative Discoveries in Engineering and Applications[IJARIDEA], 2019

This Policy Document surveys and assesses the scholarly presentation of the understudies by methods for target measure that mirrors their scholastic accomplishment on a trimester premise (GPA) and nonstop premise (CGPA). The Policy Document and strategies plan to characterize the methodology in ascertaining the evaluation point normal (GPA) and total point normal (CGPA) of understudy. The Policy Document and methodology apply to all understudies of the University, both acknowledged as new understudy or student from another school. This Policy Document additionally guarantees that understudies continue to fitting system and progress in like manner. Thus, the college enables understudy to change their scholarly program inside the school or to another school. This Policy Document and techniques plan to give rules to understudies who wish to change their scholarly program either inside the school or to another school.

Research on humanities and social sciences, 2012

The purpose of the research was to determine if SSCE scores, session and sex of students imparts negatively or positively on each student FCGPA score at the tertiary level. Data were compiled from the student records of various departments. The information sought were on gender, the session (morning or evening), the cumulative grade points average and the Senior Secondary School Certificate Examination(SSCE) scores of the 2006 to 2009 year group of students. The multiple linear regression with interaction was used to analysis the data. It was found that students who to attend the morning session on the average obtain higher FCGPA than their evening counterparts. It was also identified that there is no relation between a student’s sex and his or her cumulative grade points average (CGPA) at 5% significance level. Also a student who enters Koforidua Polytechnic with the “best SSCE” scores obtains the highest cumulative grade point average (CGPA). Keywords : multiple linear regression...