Predicting Student Retention and Academic Success at New Mexico Tech PDF Download

Author: Julie Luna
Publisher:
ISBN:
Category : Academic achievement
Languages : en
Pages : 224

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Author: Norelle Irene Shlanta
Publisher:
ISBN:
Category : College student development programs--United States
Languages : en
Pages : 158

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Author: Alan Seidman
Publisher: Rowman & Littlefield
ISBN: 1475872364
Category : Education
Languages : en
Pages : 359

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Book Description
College student retention continues to be a top priority among colleges, universities, educators, federal and state legislatures, parents and students. While access to higher education is virtually universally available, many students who start in a higher education program do not complete the program or achieve their academic and personal goals. In spite of the programs and services colleges and universities have devoted to this issue, student retention and graduation rates have not improved considerably over time. College Student Retention: Formula for Student Success, Third Edition offers a solution to this vexing problem. It provides background information about college student retention issues and offers the educational community pertinent information to help all types of students succeed. The book lays out the financial implications and trends of retention. Current theories of retention, retention of online students, and retention in community colleges are also thoroughly discussed. Completely new to this edition are chapters that examine retention of minority and international students. Additionally, a formula for student success is provided which if colleges and universities implement student academic and personal goals may be attained.

Author: Ruba Alkhasawneh
Publisher:
ISBN:
Category : Education, Higher
Languages : en
Pages :

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Book Description
Understanding the reasoning behind the low enrollment and retention rates of Underrepresented Minority (URM) students (African Americans, Hispanic Americans, and Native Americans) in the disciplines of science, technology, engineering, and mathematics (STEM) has concerned many researchers for decades. Numerous studies have used traditional statistical methods to identify factors that affect and predict student retention. Recently, researchers have relied on using data mining techniques for modeling student retention in higher education [1]. This research has used neural networks for performance modeling in order to obtain an adequate understanding of factors related to first year academic success and retention of URM at Virginia Commonwealth University. This research used feed forward back-propagation architecture for modeling. The student retention model was developed based on fall to fall retention in STEM majors. The overall freshman year GPA was used to model student academic success. Each model was built in two different ways: the first was built using all available student inputs, and the second using an optimized subset of student inputs. The optimized subset of the most relevant features that comes with the student, such as demographic attributes, high school rank, and SAT test scores was formed using genetic algorithms. A further step towards understanding the retention of URM groups in STEM fields was taken by conducting a series of focus groups with participants of an intervention program at VCU. Focus groups were designed to elicit responses from participants for identifying factors that affect their retention the most and provide more knowledge about their first year experiences, academically and socially. Results of the genetic algorithm and focus groups were incorporated into building a hybrid model using the most relevant student inputs. The developed hybrid model is shown to be a valuable tool in analyzing and predicting student academic success and retention. In particular, we have shown that identifying the most relevant student inputs from the student's perspective can be incorporated with quantitative methodologies to build a tool that can be used and interpreted effectively by people who are related to the field of STEM retention and education. Further, the hybrid model performed comparable to the model developed using the optimized set of inputs that resulted from the genetic algorithm. The GPA prediction hybrid model was tested to determine how well it would predict the GPA for all students, majority students and URM students. The root mean squared error (RM. S.E) on a 4.0 scale was 0.45 for all students, 0.47 for majority students, and 0.45 for URM students. The hybrid retention model was able to predict student retention correctly for 74% of all students, 79% of majority students and 60% of URM students. The hybrid model's accuracy was increased 3% compared to the model which used the optimized set of inputs.

Author: Black, Ruth Claire
Publisher: IGI Global
ISBN: 1522559493
Category : Education
Languages : en
Pages : 230

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Book Description
Online degree programs have long faced the issue of retention and engagement from their students. Proper support and guidance for students can encourage continuation in these programs, and can help lead to student success. Coaching for Student Retention and Success at the Postsecondary Level: Emerging Research and Opportunities is a pivotal reference source that provides vital research on the application of student support systems as a promising intervention for post-secondary retention and student success. While highlighting topics such as student assessment, online programs, and professional identity, this publication explores support strategies that boost retention, as well as the methods of using support and guidance to promote student success. This book is ideally designed for educational professionals, educational organizations, educational administrators, universities, and academics seeking current research on the effects of guidance on student retention rates and success.

Author: Alma Norma Rodriguez
Publisher:
ISBN:
Category : Academic achievement
Languages : en
Pages : 202

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Author:
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 764

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Author: Rebecca Jane Brown
Publisher:
ISBN:
Category : Developmental reading
Languages : en
Pages : 166

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Author: Sandra L. Christenson
Publisher: Springer Science & Business Media
ISBN: 1461420172
Category : Psychology
Languages : en
Pages : 839

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Book Description
For more than two decades, the concept of student engagement has grown from simple attention in class to a construct comprised of cognitive, emotional, and behavioral components that embody and further develop motivation for learning. Similarly, the goals of student engagement have evolved from dropout prevention to improved outcomes for lifelong learning. This robust expansion has led to numerous lines of research across disciplines and are brought together clearly and comprehensively in the Handbook of Research on Student Engagement. The Handbook guides readers through the field’s rich history, sorts out its component constructs, and identifies knowledge gaps to be filled by future research. Grounding data in real-world learning situations, contributors analyze indicators and facilitators of student engagement, link engagement to motivation, and gauge the impact of family, peers, and teachers on engagement in elementary and secondary grades. Findings on the effectiveness of classroom interventions are discussed in detail. And because assessing engagement is still a relatively new endeavor, chapters on measurement methods and issues round out this important resource. Topical areas addressed in the Handbook include: Engagement across developmental stages. Self-efficacy in the engaged learner. Parental and social influences on engagement and achievement motivation. The engaging nature of teaching for competency development. The relationship between engagement and high-risk behavior in adolescents. Comparing methods for measuring student engagement. An essential guide to the expanding knowledge base, the Handbook of Research on Student Engagement serves as a valuable resource for researchers, scientist-practitioners, and graduate students in such varied fields as clinical child and school psychology, educational psychology, public health, teaching and teacher education, social work, and educational policy.

Author:
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 464

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Book Description
Includes proceedings of the association's annual convention.