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Showing 1 to 15 of 29 results Save | Export
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Ortigosa, Alvaro; Carro, Rosa M.; Bravo-Agapito, Javier; Lizcano, David; Alcolea, Juan Jesus; Blanco, Oscar – IEEE Transactions on Learning Technologies, 2019
This paper presents the work done to support student dropout risk prevention in a real online e-learning environment: A Spanish distance university with thousands of undergraduate students. The main goal is to prevent students from abandoning the university by means of retention actions focused on the most at-risk students, trying to maximize the…
Descriptors: At Risk Students, Dropout Prevention, Undergraduate Students, Distance Education
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Davidson, J. Cody; Wilson, Kristin B. – Community College Journal of Research and Practice, 2017
Historically, higher education research has focused on traditional students (i.e., recent high school graduates at a residential, 4-year institutions), but community college students are quickly becoming the new traditional student (Jenkins, 2012). In the fall of 2011, more than one third (36%) of all students enrolled in postsecondary education…
Descriptors: Higher Education, Community Colleges, Dropout Characteristics, Dropout Rate
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Hang, Bui Thi Thuy; Kaur, Amrita; Nur, Abdul Hamid Busthami – Malaysian Journal of Learning and Instruction, 2017
Purpose: Student motivation for positive academic outcome and persistence at school is significantly affected by personal and environmental factors. Anchored in self-determination theory, this study tested a motivational model which looked at how support in terms of perceived teacher autonomy and from school administration constituted the key…
Descriptors: Foreign Countries, Self Determination, Motivation Techniques, Models
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Chadli, Abdelhafid; Bendella, Fatima; Tranvouez, Erwan – Educational Technology & Society, 2015
In this paper we present an Agent-based evaluation approach in a context of Multi-agent simulation learning systems. Our evaluation model is based on a two stage assessment approach: (1) a Distributed skill evaluation combining agents and fuzzy sets theory; and (2) a Negotiation based evaluation of students' performance during a training…
Descriptors: Learning Motivation, Student Evaluation, Skills, Simulation
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Mah, Dana-Kristin – Technology, Knowledge and Learning, 2016
Learning analytics and digital badges are emerging research fields in educational science. They both show promise for enhancing student retention in higher education, where withdrawals prior to degree completion remain at about 30% in Organisation for Economic Cooperation and Development member countries. This integrative review provides an…
Descriptors: Educational Research, Data Collection, Data Analysis, Recognition (Achievement)
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Wexler, Jade; Pyle, Nicole; Fall, Anna Maria – Preventing School Failure, 2015
Project GOAL is a systematic dropout prevention model including individual and peer-mediated group interventions for at-risk students. This article provides an overview of the Project GOAL model and describes a 2-year experimental pilot study of Project GOAL with a cohort of eighth-and ninth-grade students in a low-income school district in the…
Descriptors: Dropout Prevention, Intervention, Secondary School Students, Pilot Projects
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Bernstein, Larry; Edmunds, Julie; Fesler, Lily – Society for Research on Educational Effectiveness, 2014
Students entering high school in 9th grade face a formidable challenge. The transition to high school from 8th grade brings with it increased risks for all students. For example, students in 9th grade are anywhere from three to five times more likely to fail a class than students in any other grade. Similarly, ninth grade retention rates are…
Descriptors: Achievement Gap, Readiness, High School Students, Student Adjustment
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Essa, Alfred; Ayad, Hanan – Research in Learning Technology, 2012
The need to educate a competitive workforce is a global problem. In the US, for example, despite billions of dollars spent to improve the educational system, approximately 35% of students never finish high school. The drop rate among some demographic groups is as high as 50-60%. At the college level in the US only 30% of students graduate from…
Descriptors: Artificial Intelligence, Computer Graphics, Computer Interfaces, Statistical Analysis
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Kraska, Marie – Journal of Industrial Teacher Education, 2008
This manuscript addresses learning communities (LCs) as a strategy to retain graduate students until program completion. Definitions of LCs and their early development are presented. The benefits of LCs to groups of students with common interests are discussed. In addition, reasons for early graduate student attrition are included. Common models…
Descriptors: Graduate Students, Student Attrition, Academic Persistence, Cooperative Learning
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Chau, Yen – State Education Standard, 2009
By now people are all too familiar with the disheartening numbers: approximately 7,000 students drop out each day, which means nearly one-third of high school students will not graduate with their peers. The statistics are even more staggering for minority and low-income students, especially in the nation's largest urban districts, where less than…
Descriptors: Dropout Prevention, Dropouts, State Action, State Programs
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McMillan, James H.; Reed, Daisy F. – Clearing House, 1994
Integrates existing literature with the authors' research that examines resiliency (students in danger of dropping out of school who are able to develop stable, healthy personas and are able to recover from or adapt to life's stresses or problems). Suggests a model to explain resiliency that can be used to better understand why these students have…
Descriptors: Academic Persistence, Dropout Characteristics, Dropout Prevention, Dropout Research
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Seidman, Alan – College and University, 1996
Recent research on college student attrition is examined for trends, and it is suggested that the common perspective on retention and attrition is too narrow; it should be viewed from three perspectives: within-course retention; program retention; and institutional retention rate. Recommended for retention (R) is early (E) identification (Id) plus…
Descriptors: Academic Persistence, College Administration, Dropout Characteristics, Dropout Prevention
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Berger, Joseph B.; Milem, Jeffrey F. – Research in Higher Education, 1999
This study refined and applied an integrated model of undergraduate persistence (accounting for both behavioral and perceptual components) to examine first-year retention at a private, highly selective research university. Results suggest that including behaviorally based measures of involvement improves the model's explanatory power concerning…
Descriptors: Academic Persistence, College Students, Dropout Prevention, Higher Education
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Roblyer, M. D.; Davis, Lloyd – Online Journal of Distance Learning Administration, 2008
Virtual schooling has the potential to offer K-12 students increased access to educational opportunities not available locally, but comparatively high dropout rates continue to be a problem, especially for the underserved students most in need of these opportunities. Creating and using prediction models to identify at-risk virtual learners, long a…
Descriptors: Prediction, Predictor Variables, Success, Virtual Classrooms
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Billson, Janet Mancini; Terry, Margaret Brooks – College and University, 1987
Colleges and universities are increasingly committed to achieving enrollment stability through raising student retention rates. The student retention model is designed to guide institutions toward enhancing both involvement and institutional fit for as many students as feasible, thereby increasing student retention. (MLW)
Descriptors: Academic Persistence, Admission Criteria, College Attendance, College Students
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