مقارنة القدرة التنبؤية لمعدل الثانوية العامة الأردنية ومعدلات الثانوية للبرامج الأجنبية للطلبة الأردنيين بالمعدل التراكمي في الجامعات الأردنية الحكومية = Comparing the Predictive Ability of the Jordanian General Secondary Education Average GSEA and Foreign High School Averages for Jordanian Students with the Grade Point Average GPAs at Jordanian Public Universities

2016 ◽  
Vol 43 (2) ◽  
pp. 637-662
Author(s):  
حيدر إبراهيم ظاظا ◽  
جهاد خليل المشايخ
Keyword(s):  
High School ◽  
Secondary Education ◽  
Grade Point Average ◽  
Public Universities ◽  
Predictive Ability ◽  
Grade Point

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

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.

Nontraditional and Traditional Student Persisters and Nonpersisters in the Community and Technical College

1984 ◽  
Vol 4 (1) ◽  
pp. 47-57 ◽  
Author(s):  
ALAN D. SMITH ◽  
MICHAEL N. SUGARMAN
Keyword(s):  
College Students ◽  
High School ◽  
Nontraditional Students ◽  
Grade Point Average ◽  
Technical College ◽  
School Grade ◽  
Grade Point ◽  
Community And Technical College ◽  
High School Grade ◽  
The University

A study was conducted with Community and Technical College students enrolled at the University of Akron, a major urban university, during the 1978–1979 academic year. Students were divided into traditional and nontraditional persisters and nonpersisters, and if they were placed on academic probation, they were removed from the study. These students were given modified National Center for Higher Education Management Systems (NCHEMS) questionnaires for program completers and noncompleters. The questions tested for varying degrees of satisfaction with the University and reasons for withdrawal concerning various academic, socioeconomic, and environmental press variables. In addition, selected demographic variables from the student masterfile were tested, along with the questionnaire responses in 99 research hypotheses using multiple linear regression and corrected for multiple comparisons. Results indicate that 13 hypotheses were found to significantly discriminate between traditional and nontraditional community college students. The persisting nontraditional students appeared to be more satisfied with the University concerning a few variables, greater proportion attended part-time, during the day, enrolled for less hours, and had a greater high school grade point average than their traditional counterparts. The nonpersisting, nontraditional students were similar to their persisting counterparts, except that traditional nonpersisting students had a higher high school grade point average, lived at greater distances from the school, and attended day time classes as compared to nontraditional students.

Including the Assessment of Nontraditional Factors in Pharmacy School Admissions

2005 ◽  
Vol 39 (4) ◽  
pp. 721-726 ◽  
Author(s):  
David A Latif
Keyword(s):  
Grade Point Average ◽  
College Admissions ◽  
Clinical Performance ◽  
Data Extraction ◽  
Relevant Literature ◽  
Predictive Ability ◽  
Cross Sectional ◽  
Grade Point ◽  
Higher Education Admissions ◽  
Admissions Test

OBJECTIVE: To review the relevant literature regarding the predictive ability of cognitive measures (ie, Pharmacy College Admissions Test [PCAT] scores and prepharmacy grade point average [GPA]) on both academic and clinical performance and discuss the inclusion of nontraditional assessment during the admissions process. DATA SOURCES: Articles were identified through searches of International Pharmaceutical Abstracts (1970–April 2004), MEDLINE (1966–January 2004), and ERIC (1966–April 2004) using the key words admissions variables, predictors of success, Pharmacy College Admissions Test, grade point average, cognitive variables, and noncognitive variables. STUDY SELECTION AND DATA EXTRACTION: Cross-sectional, longitudinal, and retrospective studies, as well as reviews, regarding pharmacy school and other higher education admissions' variables were included in this review. DATA SYNTHESIS: Many pharmacy school admissions committees give a majority weight to the traditional cognitive markers of prepharmacy GPA and PCAT scores when selecting viable applicants. Doing so may be problematic due to the magnitude of the relationship between traditional cognitive predictors and pharmacy school performance. CONCLUSIONS: Based on this review, a cogent argument is advanced for the need to examine, in addition to PCAT scores and GPAs, such nontraditional factors as empathy, citizenship, and ethical behavior. This may increase the predictive ability of preadmission factors on pharmacy school didactic and clinical performance. Schools of pharmacy can do this through questionnaires and interviews designed to assess nontraditional variables.

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