Leveraging What We Know to Enhance Short-Term and Long-Term Retention of University Students

2009 ◽  
Vol 11 (3) ◽  
pp. 407-430 ◽  
Author(s):  
Don Whalen ◽  
Kevin Saunders ◽  
Mack Shelley
Keyword(s):  
High School ◽  
Learning Community ◽  
Grade Point Average ◽  
Financial Aid ◽  
Technology Use ◽  
Female Gender ◽  
Grade Point ◽  
Logistic Regression Models ◽  
Cumulative Grade Point Average ◽  
Cooperative Institutional Research Program

Logistic regression models of students' 1-year retention and 6-year retention/graduation for the fall 2000 entering class of students at a research-extensive university in the Midwest were estimated by combining university, financial aid, and Cooperative Institutional Research Program data ( n = 1,905; 45% female, 87% Caucasian, 75% in-state). Statistically significant predictors of retention to the second year were first-year cumulative grade point average, financial aid variables, learning community membership, information technology use in high school, and in-state residence. Six-year retention/graduation was predicted significantly by the students' last registered term cumulative grade point average, number of years living on campus, transfer credits, financial aid variables, gender, ability measures (high school rank, ACT composite score), in-state residence, and female gender.

scholarly journals Impact of the foundation program and high school grade in predicting the cumulative grade point average (CGPA) among the graduates of the nursing program at the Ministry of Health Educational Institutes in Oman

2018 ◽  
Vol 8 (12) ◽  
pp. 98
Author(s):  
Said A. Alghenaimi ◽  
Maiyasa G. Al-Saadi ◽  
Hamed K. Al Reesi
Keyword(s):  
High School ◽  
Grade Point Average ◽  
Nursing Program ◽  
First Year ◽  
School Grade ◽  
Grade Point ◽  
Cumulative Grade Point Average ◽  
High School Grade ◽  
Foundation Program ◽  
One Year

Background and objective: Higher education has witnessed significant changes in order to provide quality education that meets the needs of the 21st century. To be in par with international best practices, the foundation program was established to prepare the high school leavers for higher education in Oman, a middle-eastern country. The aims of this study were to (1) assess the relationship between students’ high school scores and their cumulative grade point average (CGPA) among the graduates of the nursing program in Oman, and (2) compare the CGPA of the student who attended the general foundation program (GFP) compared to the ones who did not attend the GFP. Methods: Secondary data analysis approach was used to access the alumni files one year before and one year after the implementation of the GFP. A retrospective approach was used to gather data from the alumni files, which included high school grade, whether the graduates have attended the foundation program or not, their first year Grade point average (GPA), and their CGPA.Results: Six hundred twenty-seven (n = 627) graduates were recruited from two cohorts, one attended the GFP (n = 287; 45.8%) and the others did not attend the GFP (n = 340; 54.2%). Majority of the participants who were included in this study were female graduate (n = 535; 85.3%). The students who attended the GFP were found to have higher first year GPA and higher CGPA compared to those who did not attend the GFP. High Diploma Scores and First Year GPA were significant predictors of the graduation CGPA of the graduates who did not enroll in the GFP whereas First Year GPA was the main predictors of the CGPA of the graduates who attended the GFP. It was also obvious that the first year GPA showed a higher significant correlation with CGPA among GFP attenders (r = 0.912, p < .01) in comparison to non GFP attenders (r = 0.775, p < .01).Conclusions: This study sheds light into the impact of foundation program on the overall students’ performance in the nursing program. It significantly reveals that GFP, has a positive impact on the overall CGPA, as it equipped the students with the necessary study skills and increased their English proficiency levels.

Diploma Program Graduates’ CGPA as Predictor of Success in the Teachers’ Professional Licensing Written Exam Result with Gender Analysis

2017 ◽  
Vol 26 (4) ◽  
pp. 321-335
Author(s):  
Yoseph Shumi Robi
Keyword(s):  
Grade Point Average ◽  
Gender Analysis ◽  
Grade Point ◽  
Cumulative Grade Point Average ◽  
Professional Licensing ◽  
Valid Predictor ◽  
Predictor Of Success ◽  
Diploma Program ◽  
Graduating Students ◽  
Exam Result

The purpose of this study was to investigate the extent to which diploma graduates’ Cumulative Grade Point Average (CGPA) predicts their success in teachers’ professional licensing written exam result (TPLWER). A total of 588 graduating students (317 males and 271 females) were included in the study. Correlation, simple regression analyses, and independent sample t-test were employed on the data. The result revealed a statistical significant correlation between CGPA and TPLWER. CGPA appeared to be valid predictor of success of TPLWER and accounted for 33.40% of the variation in TPLWER. The results indicated statistically significant gender differences in diploma graduates’ CGPA and TPLWER.

scholarly journals Predicting Freshman Grade Point Average From College Admissions Test Scores and State High School Test Scores

AERA Open ◽  
2016 ◽  
Vol 2 (4) ◽  
pp. 233285841667060 ◽  
Author(s):  
Daniel Koretz ◽  
Carol Yu ◽  
Preeya P. Mbekeani ◽  
Meredith Langi ◽  
Tasmin Dhaliwal ◽  
...  
Keyword(s):  
High School ◽  
Grade Point Average ◽  
Test Scores ◽  
College Admissions ◽  
Grade Point ◽  
Admissions Test

Prediction of Cumulative Grade Point Average: A Case Study

2020 ◽  
pp. 33-42
Author(s):  
Anan Sarah ◽  
Mohammed Iqbal Hossain Rabbi ◽  
Mahpara Sayema Siddiqua ◽  
Shipra Banik ◽  
Mahady Hasan
Keyword(s):  
Grade Point Average ◽  
Grade Point ◽  
Cumulative Grade Point Average

scholarly journals Evaluation of the scholastic performance of students in 12 programs from a private university in the south-west geopolitical zone in Nigeria

F1000Research ◽  
2019 ◽  
Vol 8 ◽  
pp. 154
Author(s):  
Roseline O. Ogundokun ◽  
Marion O. Adebiyi ◽  
Oluwakemi C. Abikoye ◽  
Tinuke O. Oladele ◽  
Adewale F. Lukman ◽  
...  
Keyword(s):  
Academic Performance ◽  
Grade Point Average ◽  
Private School ◽  
Private University ◽  
Study Data ◽  
The South ◽  
Grade Point ◽  
Cumulative Grade Point Average ◽  
South West ◽  
University Setting

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).

scholarly journals Supervised Learning Applied to Graduation Forecast of Industrial Engineering Students

2022 ◽  
Vol 11 (1) ◽  
pp. 325-337
Author(s):  
Natalia Gil ◽  
Marcelo Albuquerque ◽  
Gabriela de
Keyword(s):  
Machine Learning ◽  
High School ◽  
Logistic Regression ◽  
Supervised Learning ◽  
Grade Point Average ◽  
Engineering Students ◽  
Learning Algorithm ◽  
Industrial Engineering ◽  
Machine Learning Algorithm ◽  
Grade Point

<p style="text-align: justify;">The article aims to develop a machine-learning algorithm that can predict student’s graduation in the Industrial Engineering course at the Federal University of Amazonas based on their performance data. The methodology makes use of an information package of 364 students with an admission period between 2007 and 2019, considering characteristics that can affect directly or indirectly in the graduation of each one, being: type of high school, number of semesters taken, grade-point average, lockouts, dropouts and course terminations. The data treatment considered the manual removal of several characteristics that did not add value to the output of the algorithm, resulting in a package composed of 2184 instances. Thus, the logistic regression, MLP and XGBoost models developed and compared could predict a binary output of graduation or non-graduation to each student using 30% of the dataset to test and 70% to train, so that was possible to identify a relationship between the six attributes explored and achieve, with the best model, 94.15% of accuracy on its predictions.</p>

Predicting success in teacher education: Revisiting the influence of high school GPA, admission, and standardized test scores on academic and licensure performance

2020 ◽  
Vol 10 (2) ◽  
pp. 1-17
Author(s):  
Apler J. Bansiong ◽  
Janet Lynn M. Balagtey
Keyword(s):  
High School ◽  
Teacher Education ◽  
Grade Point Average ◽  
Test Scores ◽  
Standardized Test ◽  
Standardized Test Scores ◽  
Degree Programs ◽  
Licensure Examination ◽  
Grade Point ◽  
Admission Variables

This predictive study explored the influence of three admission variables on the college grade point average (CGPA), and licensure examination ratings of the 2015 teacher education graduates in a state-run university in Northern Philippines. The admission variables were high school grade point average (HSGPA), admission test (IQ) scores, and standardized test (General Scholastic Aptitude - GSA) scores. The participants were from two degree programs – Bachelor in Elementary Education (BEE) and Bachelor in Secondary education (BSE). The results showed that the graduates’ overall HSGPA were in the proficient level, while their admission and standardized test scores were average. Meanwhile, their mean licensure examination ratings were satisfactory, with high (BEE – 80.29%) and very high (BSE – 93.33%) passing rates. In both degree programs, all entry variables were significantly correlated and linearly associated with the CGPAs and licensure examination ratings of the participants. These entry variables were also linearly associated with the specific area GPAs and licensure ratings, except in the specialization area (for BSE). Finally, in both degrees, CGPA and licensure examination ratings were best predicted by HSGPA and standardized test scores, respectively. The implications of these findings on admission policies are herein discussed.

Working on Grade Point Average, test Accuracy, and Attendance of High School Students

1996 ◽  
Vol 78 (1) ◽  
pp. 41-42 ◽  
Author(s):  
Grant Lenarduzzi ◽  
T. F. McLaughlin
Keyword(s):  
High School ◽  
High School Students ◽  
Grade Point Average ◽  
Test Scores ◽  
Grade Point Averages ◽  
Test Accuracy ◽  
Lower Grade ◽  
School Students ◽  
Grade Point ◽  
School Year

The present analysis examined grade point averages (GPA), subject-matter test scores, and attendance for 274 students enrolled in a high school at the beginning of the 1992–1993 school year by the number of hours worked per week in the previous year (1991–92) and in the current school year (1992–1993). The over-all outcomes indicated that working fewer than 10 hours per week had small adverse effects on each measure. Students working from 10 to 20 hours per week had lower grade point averages and attendance. Students working over 20 hours per week had depressed test scores and grade point averages and more absences than other students who worked less or did not work.

Love and Other Grades

2015 ◽  
Vol 19 (1) ◽  
pp. 81-97 ◽  
Author(s):  
Julia Schmidt ◽  
Brian Lockwood
Keyword(s):  
Academic Performance ◽  
Romantic Relationships ◽  
Grade Point Average ◽  
Romantic Relationship ◽  
University Administrators ◽  
Student Body ◽  
Data Set ◽  
Grade Point ◽  
Logistic Regression Models ◽  
Adolescent Students

Of the few studies that have examined the effects of romantic relationships on academic performance, most have been concerned with adolescent students. This study analyzes a data set of more than 300 students at a midsized, private University in the northeast United States to determine if participating in a romantic relationship predicts grade point average or course attendance. The results of multivariate analyses indicate that being in a romantic relationship while in college is significantly associated with class absences, but not with grade point average. Specifically, logistic regression models show that participation in a romantic relationship more than doubles the odds of failing to attend three or more class meetings per course in a semester. Practical implications of these findings include the consideration of romantic relationships among the undergraduate student body by university administrators and faculty when attempting to address course attendance concerns. Additionally, this study suggests that future researchers examine the characteristics of romantic relationships and romantic partners in order to more fully understand how such relationships might affect the academic performance of university students.

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