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Radovan, Marko – Turkish Online Journal of Distance Education, 2019
Supporters of distance education highlight the many advantages of online learning as compared to face-toface education, such as greater openness, diversity of teaching materials, adjustment to student learning styles, the speed of learning, and more. Despite the advantages, the growing number of programs, and the increased acceptance of distance…
Descriptors: School Holding Power, Models, Distance Education, Electronic Learning
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
Archer, Elizabeth; Prinsloo, Paul – Assessment & Evaluation in Higher Education, 2020
Assessment and learning analytics both collect, analyse and use student data, albeit different types of data and to some extent, for various purposes. Based on the data collected and analysed, learning analytics allow for decisions to be made not only with regard to evaluating progress in achieving learning outcomes but also evaluative judgments…
Descriptors: Learning Analytics, Student Evaluation, Educational Objectives, Student Behavior
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
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)
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
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
Maurer, Richard D. – Phi Delta Kappan, 1982
Describes Project Intercept in Ossining (New York), which cut the high school's dropout, absence, and failure rates by involving teachers, students, and families. The program uses four major strategies--teacher/staff inservice training, alternative academic programs, student training in social and interpersonal skills, and family intervention…
Descriptors: Dropout Prevention, Dropouts, Models, School Holding Power
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

Priest, Douglas; Milne, Jonathan – Journal for Higher Education Management, 1991
Enrollment management differs from admissions in its concern for students at every stage of their association with the college. As such, it must address retention issues. Academic advising can contribute to improved retention, but to be effective it must be appropriate. A number of advising models are currently in use. (MSE)
Descriptors: Academic Advising, College Administration, Dropout Prevention, Enrollment

Holmes, Sharon L.; Ebbers, Larry H.; Robinson, Daniel C.; Mugenda, Abel G. – Journal of College Student Retention, 2001
Reviews research and theory on factors cited as contributing to the retention and graduation of African-American students attending predominantly white institutions. Proposes a model to help such institutions provide positive learning experiences for African-Americans. The model has three stages: (1) recruitment considerations, (2) the first-year…
Descriptors: Black Students, College Freshmen, College Outcomes Assessment, Dropout Prevention

Brown, James M.; Kayser, Terrence F. – Journal of Industrial Teacher Education, 1985
Presents a model based on person-environment fit that is designed to increase retention of students with unique educational needs in postsecondary vocational education programs. The specific details that surround the development of this model are examined and are related to the nature and extent of the problem. (CT)
Descriptors: Dropout Prevention, Dropout Rate, Educational Needs, Individual Needs

Smith, Alan D. – College Student Journal, 1982
The University of Akron, a major urban university, has experienced unusually high attrition rates for students enrolled in the two largest colleges. The university has attempted to meet this problem by committee recommendations and questionnaire/demographic data gathering and analysis, which has resulted in some success. (Author/RC)
Descriptors: College Students, Dropout Prevention, Higher Education, Models

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

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