Retention in Higher Education: An Agent-Based Model of Social Interactions and Motivated Agent Behavior

Toward a New Predictive Model of Student Retention in Higher Education

Journal of College Student Retention: Research, Theory & Practice, 2015

Journal of College Student Retention_ Research, Theory & Practice-2015-Kerby-1521025115578229.pdf

Journal of College Student Retention: Research, Theory and Practice, 2015

Theoretical models designed to predict whether students will persist or not have been valuable tools for retention efforts relative to the creation of services in academic and student affairs. Some of the early models attempted to explain and measure factors in the college dropout process. For example, in his seminal work, Tinto defined retention as a longitudinal process incorporating both the academic potential of the student and institutional social systems, thus creating a directional model based on continual variance in social commitments that influence academic performance. Others expanded the earlier theoretical models to test the predictive capabilities of these models using logistical regression and structural equation modeling to project college retention rates. As public sectors push for performance-based accountability in federal and state agencies, higher education funding becomes directly linked to academic performance. Critics of performance-based accountability in higher education contend that these funding structures undermine the mission of the university system and negatively impact retention in higher education. As Astin suggested, the structure of the American college system is a great deal more complex than the elementary concept of supply side economics. Additionally, due to globalization and aggressive progress in information technology, a shift from laborintensive, information-age economies to a knowledge-based economy has created

Higher Education: Factors and Strategies for Student Retention

HETS Online Journal

Education emerged out of the necessity different countries had for better-prepared workers. Well-educated citizens are responsible for taking the best measures for society’s social, financial, and political development (Claudio, 2002). Nevertheless, higher education institutions confront the problem of retaining students and helping them finish their academic degrees. This led me to research the role educational institutions have in retaining students and what should professors do at Bronx Community College (BCC) and other institutions.Objectives: Present academic offering factors related to the pedagogic process and social demands which can affect the retention of students in universities and Bronx Community College. Present strategies that can help with social demands and academic offering factors which influence the retention of students in universities and Bronx Community College. Promote strategies recommended by some retention models (Tinto, 1975, 1987; Bean and Metzner, 1986;...

Comparison of Student Retention Models in Undergraduate Education from the Past Eight Decades

2017

Student retention and completion rates are challenging issues in higher education. In the academic domain, pressure exists for every institution to come up with strategies that support student success from enrollment through graduation without compromising academic or accreditation standards. This paper presents the findings from a review of student retention models dating back to over eight decades to identify the key factors for retention. Specific recommendations for adaptive and sustainable retention agenda are made. Critical implications of this review directly impact institutional policy makers, researchers, faculty, and decision makers and provide a framework for the development and implementation of viable, adaptive retention initiatives and strategic plans.

Evaluation of a Conceptual Model of Student Retention at a Public Urban Commuter University

2014

A new conceptual model of student retention was developed and evaluated for first-year retention and for second-year retention of students at an urban, mid-western commuter university. The model captured the joint effects of academic engagement and environmental factors on academic performance and persistence of commuter students in their first two years of college attendance. The academic engagement and environmental factors incorporated into the model included: pre-college academic achievement, Deep Learning, Study Time per Week, College Math Readiness, Major Selection, Hours of Employment, receiving (or not receiving) a Pell Grant Award and Financial Concerns. Structural equation modeling techniques were utilized to simultaneously assess the quality of the theoretical construct known as Deep Learning and to test the hypothesized causal paths linking the engagement and environmental factors to the college grades and student retention. Results indicated that when controlling for precollege academic achievement, Deep Learning, Study Time per Week, and College Math Readiness had positive effects on First-year Grades. Working outside campus 21 or more hours per week negatively impacted First-year Grades. First-year Grades and Pell Grant Award were significantly related to First-year Retention, but Financial Concerns were found to have a negative effect on retention. When applied to second-year students, Deep Learning and Major Selection were found to have significant effects on Second-year Grades. Factors that positively influenced Second-year Retention were Grades, Major Selection ix and Pell Grant Award, while Financial Concerns lowered the likelihood of Second-year Retention. Based on these results I suggest that institutional efforts in engaging students in a deep learning-based curriculum, encouraging major and career exploration, and providing college-financing resources can create pathways to greater academic success and persistence among commuter students.. Research on Commuter Student Retention Research on commuter students who, as a group, account for a large majority of students on campuses across the nation (Jacoby, 2000) is needed because there are few theoretical frameworks that are directly targeted to them (Baum, 2005). The lack of indepth examinations of commuter students means that there is still much to learn about the interactions and involvement of students in the college environment. Such studies may reveal valuable results to help guide institutions in meeting the retention needs of commuter students as well as those of sub-populations such as the academically underprepared or specific minority groups. Commuter students are a heterogeneous group in terms of demographic backgrounds and developmental needs. In comparison to residential four-year colleges and universities, commuter institutions tend to have greater proportions of economically and/or academically disadvantaged student populations because of lower tuition costs and closer proximity to their work and home communities. Research on the impact of commuting on student retention indicates that residential students tend to have higher retention rates than the commuter students (Pike, 1999; Pike, Schroeder, & Berry, 1997). However, as Beal and Noel (1980) point out, while being a commuter student is a risk factor for dropout behavior, it is not as significant as other factors such as low academic achievement, limited educational aspirations, indecision about major/career goal, inadequate financial resources, economic disadvantage, or being a first-generation college student. Thus, while there are common factors that could promote or hinder retention of both residential and commuter students, Note. bunstandardized path coefficient; SEstandard error. *p < .05; **p < .01; ***p < .001. Measures of pre-college academic achievement (High-school GPA and ACT Composite score) and of academic engagement (Study Time per Week and Deep Learning) had significant indirect effects on Second-year Retention. Among these four variables the indirect effect on retention from High-school GPA was the highest (b = .286, p <.001). The indirect effects on retention from the other three variables were small. The direct effects from Second-year GPA, Major Selection, Pell Grant Award and Financial Concerns on Second-year Retention were found significant. Major Selection also had a significant indirect effect on retention. Based on the standardized coefficients of the direct effects, Pell Grant Award (β = .730, SE = .180, p < .01) was the most significant predictor of Second-year Retention (β = 1.034, p < .01), followed by Major Selection (β = .598, SE = 0.235, p < .05), Second-year GPA (β = .326, SE = .08, p < .001) and Financial Concerns (β =-.256, SE = .08, p <.01).

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