scholarly journals Predictive Analysis of Higher Education Graduation and Retention in Saudi Arabia u sing Multinomial Logistic Regression

2021 ◽  
Vol 3 (6) ◽  
pp. 1-8
Author(s):  
Ahmed Bagabir ◽  
◽  
Mohammad Zaino ◽  
Ahmed Abutaleb ◽  
Ahmed Fagehi ◽  
...  
Keyword(s):  
Higher Education ◽  
Logistic Regression ◽  
Undergraduate Students ◽  
Degree Completion ◽  
Multinomial Logistic Regression ◽  
At Risk Students ◽  
Retention Rates ◽  
First Year ◽  
Important Indicator ◽  
Admissions Policy

It is suggested that this study contributes by establishing a robust methodology for analyzing the longitudinal outcomes of higher education. The current research uses multinomial logistic regression. To the knowledge of the authors, this is the first logistic regression analysis performed at Saudi higher education institutions. The study can help decision-makers take action to improve the academic performance of at-risk students. The analyses are based on enrollment and completion data of 5,203 undergraduate students in the colleges of engineering and medicine. The observation period was extended for ten academic years from 2010 to 2020. Four outcomes were identified for students: (i) degree completion on time, (ii) degree completion with delay, (iii) dropout, and (iv) still enrolled in programs. The objectives are twofold: (i) to study the present situation by measuring graduation and retention rates with benchmarking, and (ii) to determine the effect of twelve continuous and dummy predictors (covariates) on outcomes. The present results show that the pre-admission covariates slightly affect performance in higher education programs. The results indicate that the most important indicator of graduation is the student's achievement in the first year of the program. Finally, it is highly suggested that initiatives be taken to increase graduation and retention rates and to review the admissions policy currently in place.

scholarly journals The Transition to STEM Higher Education: Policy Recommendation – Conclusions of the readySTEMgo-Project

2018 ◽  
Vol 8 (2) ◽  
pp. 10
Author(s):  
Greet Langie ◽  
Maarten Pinxten
Keyword(s):  
Higher Education ◽  
At Risk ◽  
Higher Education Policy ◽  
Early Stage ◽  
At Risk Students ◽  
Retention Rates ◽  
First Year ◽  
Policy Recommendations ◽  
Policy Recommendation ◽  
Key Skills

For Europe to remain at the forefront of scientific and technological devel-opment, the current shortage of persons trained in these fields at secondary and higher education has to be overcome. The readySTEMgo project aims to improve the retention rates of higher education STEM programmes by the identification of at-risk students in an early stage. We successfully identified a number of key skills that are essential for first-year achievement in a STEM programme. Additionally, we investigated which intervention tools can support at-risk students and evaluated their effectiveness. Based on the output of this research project four policy recommendations are formulated.

Redesigning Prediction Algorithms for At-Risk Students in Higher Education

2019 ◽  
pp. 232-250 ◽  
Author(s):  
Dennis Foung
Keyword(s):  
Higher Education ◽  
At Risk ◽  
Logistic Regression ◽  
Academic Writing ◽  
Industry 4.0 ◽  
Classification Tree ◽  
At Risk Students ◽  
Higher Education Administrators ◽  
Writing Courses ◽  
Education Administrators

Use of algorithms and data mining approaches are not new to Industry 4.0. However, these may not be common for students and educators in higher education. This chapter compares various classification techniques: classification tree, logistic regression, and artificial neural networks (ANN). The comparison focuses on each method's accuracy, algorithm, and practicality in higher education. This study made use of a dataset from two academic writing courses in a university in Hong Kong with more than 5,000 records. Results suggest that classification trees and logistic regression can be easily used in the higher education context, but ANN may not be applicable in higher educational settings. The research team suggests that higher education administrators take this research forward and design platforms to realize these classification algorithms to predict at-risk students.

Peer interaction as mechanism for providing timely and accessible feedback to a large undergraduate class

2017 ◽  
Vol 54 (2) ◽  
pp. 119-130
Author(s):  
Estelle Trengove
Keyword(s):  
Higher Education ◽  
Undergraduate Students ◽  
Peer Interaction ◽  
Large Body ◽  
First Year ◽  
Learning Approaches ◽  
Effective Feedback ◽  
Giving Feedback ◽  
Undergraduate Class

Feedback to students on their work is recognized as crucially important in higher education, but as classes at universities become larger, it is becoming more and more difficult for teachers to give their students effective feedback. There is a large body of work on giving feedback on essays and postgraduate writing, but there is very little on giving feedback to undergraduate students in engineering classes. Feedback has particular value if it facilitates students’ learning. It is therefore not necessary for the teacher to give feedback – feedback from peers is equally valuable if it facilitates learning. This paper explores the comments submitted by students about a peer interaction that was introduced in a first-year engineering class. It investigates whether this intervention could comprise effective feedback by comparing the format of the intervention and the student comments to two models from the literature on feedback. The analysis shows that the intervention was successful in providing feedback that was helpful to students in the sense that it helped to draw them into deeper learning approaches.

Human Capital Theory and Internal Migration: Do Average Outcomes Distort Our View of Migrant Motives?

2017 ◽  
Vol 14 (2) ◽  
pp. 237-250 ◽  
Author(s):  
Martin Korpi ◽  
William A.V. Clark
Keyword(s):  
Higher Education ◽  
Human Capital ◽  
Logistic Regression ◽  
Internal Migration ◽  
Metropolitan Areas ◽  
Multinomial Logistic Regression ◽  
Human Capital Theory ◽  
Capital Theory

By modelling the distribution of percentage income gains for movers in Sweden, using multinomial logistic regression, this paper shows that those receiving large pecuniary returns from migration are primarily those moving to the larger metropolitan areas and those with higher education, and that there is much more variability in income gains than what is often assumed in models of average gains to migration. This suggests that human capital models of internal migration often overemphasize the job and income motive for moving, and fail to explore where and when human capital motivated migration occurs.

Character Strengths and First-Year College Students’ Academic Persistence Attitudes: An Integrative Model

2018 ◽  
Vol 46 (5) ◽  
pp. 608-631 ◽  
Author(s):  
Brandon R. Browning ◽  
Ryon C. McDermott ◽  
Marjorie E. Scaffa ◽  
Nathan R. Booth ◽  
Nicole T. Carr
Keyword(s):  
Higher Education ◽  
College Students ◽  
Undergraduate Students ◽  
Academic Integration ◽  
Student Persistence ◽  
Structural Equation ◽  
Character Strengths ◽  
Integrative Model ◽  
Institutional Commitment ◽  
First Year

Higher education scholars produce the majority of research on student persistence. However, counseling psychologists may be uniquely situated to help students persist toward graduation by enhancing strengths. The present study integrated counseling and higher education models to examine college students’ character strengths (i.e., hope and gratitude) as predictors of student persistence variables (i.e., academic integration and institutional commitment). Drawing on higher education theories of persistence, we examined the mediating effects of academic integration on the associations between character strengths and institutional commitment among first-year undergraduate students ( N = 653). Controlling for social support, greater academic integration mediated the associations between character strengths and institutional commitment in a structural equation model. Consistent with higher education theories emphasizing academic integration as a precursor to institutional commitment, character strengths may be important for understanding academic integration and persistence. Implications for prevention and the integration of counseling psychology and higher education perspectives are discussed.

scholarly journals The Contribution of Learning and Mental Health Variables in First-Year Students' Profiles

2021 ◽  
Vol 12 ◽  
Author(s):  
Fotios S. Milienos ◽  
Christos Rentzios ◽  
Leen Catrysse ◽  
David Gijbels ◽  
Sofia Mastrokoukou ◽  
...  
Keyword(s):  
Mental Health ◽  
Higher Education ◽  
At Risk ◽  
Undergraduate Students ◽  
Emotion Dysregulation ◽  
Educational Institution ◽  
First Year ◽  
International Studies ◽  
First Year Students ◽  
Student Profiles

International studies focus on the successful transition into higher education, which is considered crucial for both the students and the educational institution in the context of students' learning and adjustment in higher education. The aim of the current study was to identify student profiles that include cognitive, metacognitive, and motivational aspects of learning, but also aspects of resilience, emotion dysregulation, and anxiety. The sample consists of 316 Greek undergraduate students (18.7% males and 81.3% females). The results showed four different (meta)-cognitive-emotional learner profiles: the emotionally stable and highly adaptive learner; the emotionally dysregulated and at risk learner; the emotionally dysregulated and highly adaptive learner; the emotionally stable and at risk learner. Emotionally dysregulated and at risk learner has a lower GPA than the emotional stable and highly adaptive learner, the emotionally dysregulated and highly adaptive learner and the emotionally stable and at risk learner.

scholarly journals A controlled intervention to improve freshman retention in a STEM-based physiology major

2020 ◽  
Vol 44 (3) ◽  
pp. 334-343
Author(s):  
Miriam Leary ◽  
Aimee Morewood ◽  
Randy Bryner
Keyword(s):  
At Risk ◽  
Student Perceptions ◽  
Teaching And Learning ◽  
At Risk Students ◽  
Retention Rates ◽  
Control Group ◽  
First Year ◽  
Freshman Retention ◽  
Retention Group ◽  
And Mathematics

Using a Scholarship of Teaching and Learning lens, this study systematically examined if a targeted intervention in at-risk students within a science, technology, engineering, and mathematics (STEM)-based physiology program would elicit positive student perceptions and higher retention rates into the second year. Those students who were considered at risk for attrition (retention; n = 82) were compared against a control group (non-retention; n = 165), and outcomes were evaluated with an End-of-Semester Survey and university enrollment data. Students in the retention group reported more favorable responses to questions pertaining to a first-year seminar course and academic advising. By the start of the following (spring 2019) semester, 48 students transferred out of the program (20%) with little difference between groups (non-retention 19%; retention 22%). At the start of fall 2019 term, 55% of the 2018 freshman class were retained within the program (non-retention 66%; retention 39%), and 85% were retained within the university (non-retention 91%, retention 74%). The intervention was successful in eliciting positive student perceptions of the major, but did not improve retention of at-risk students within the physiology major.

scholarly journals Encountering American higher education: First-year academic transition of international undergraduate students in the United States

2022 ◽  
Vol 6 (2) ◽  
pp. 148-165
Author(s):  
Masha Krsmanovic
Keyword(s):  
Higher Education ◽  
Undergraduate Students ◽  
The United States ◽  
First Year ◽  
Domestic Students ◽  
Academic Transition ◽  
Academic Challenges ◽  
American Higher Education ◽  
Academic System ◽  
Institutional Services

This study explored how international undergraduate students perceive their academic transition into American higher education. Schlossberg’s (1984) 4S Transition Theory served as the framework for exploring what academic challenges, if any, international students experience during their first year of undergraduate studies in a new cultural and educational setting. The findings revealed that students’ academic transition into the U.S. higher education was characterized by difficulties in understanding the academic system of their new environment; overcoming educational, instructional and pedagogical differences; building social relationships with domestic students; and receiving the support necessary from the appropriate institutional services.

scholarly journals Exploring the “At-Risk” Student Label Through the Perspectives of Higher Education Professionals

2020 ◽  
Author(s):  
Nick Dix ◽  
Andrew Lail ◽  
Matt Birnbaum ◽  
Joseph Paris
Keyword(s):  
Higher Education ◽  
At Risk ◽  
Undergraduate Students ◽  
Thematic Analysis ◽  
At Risk Students ◽  
Institutions Of Higher Education ◽  
Education Professionals ◽  
Higher Education Professionals ◽  
Risk Definition ◽  
At Risk Student

Institutions of higher education often use the term “at-risk” to label undergraduate students who have a higher likelihood of not persisting. However, it is not clear how the use of this label impacts the perspectives of the higher education professionals who serve and support these students. Our qualitative study explores the descriptions and understandings of higher education professionals who serve and support at-risk students. We use thematic analysis (Braun & Clark, 2006) to interpret our data and develop our themes. These themes include conflicting views of the “at-risk” definition, attempts to normalize at-risk, fostering relationships, and “at-promise.”

Sign in / Sign up

Export Citation Format

Share Document