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Deciphering the Attributes of Student Retention in Massive Open Online Courses Using Data Mining Techniques
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Gupta, Shivangi; Sabitha, A. Sai – Education and Information Technologies, 2019
Aimed at a massive outreach and open access education, Massive Open Online Courses (MOOC) has evolved incredibly engaging millions of learners' over the years. These courses provide an opportunity for learning analytics with respect to the diversity in learning activity. Inspite of its growth, high dropout rate of the learners', it is examined to…
Descriptors: Retention (Psychology), Online Courses, Learner Engagement, Electronic Learning
Visual Analysis for Monitoring Students in Distance Courses
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Weiand, Augusto; Manssour, Isabel Harb; Silveira, Milene Selbach – International Journal of Distance Education Technologies, 2019
With technological advances, distance education has been frequently discussed in recent years. The learning environments used in this course usually generates a great deal of data because of the large number of students and the various tasks involving their interaction. In order to facilitate the analysis of the data, the authors researched to…
Descriptors: Foreign Countries, Distance Education, Online Courses, Visualization
Using Big Data to Predict Student Dropouts: Technology Affordances for Research
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Niemi, David; Gitin, Elena – International Association for Development of the Information Society, 2012
An underlying theme of this paper is that it can be easier and more efficient to conduct valid and effective research studies in online environments than in traditional classrooms. Taking advantage of the "big data" available in an online university, we conducted a study in which a massive online database was used to predict student…
Descriptors: Higher Education, Online Courses, Academic Persistence, Identification
Predicting Student Attrition with Data Mining Methods
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Delen, Dursun – Journal of College Student Retention: Research, Theory & Practice, 2012
Affecting university rankings, school reputation, and financial well-being, student retention has become one of the most important measures of success for higher education institutions. From the institutional perspective, improving student retention starts with a thorough understanding of the causes behind the attrition. Such an understanding is…
Descriptors: Higher Education, Student Attrition, School Holding Power, Prediction
Dropout Identification: A Preliminary Study of the Pasco School District.
Noth, Nancy; O'Neill, Barbara – 1981
This study, which examined the demographic and educational characteristics of students who leave school before completing the twelfth grade, aimed to identify descriptive and predictive data on the potential school dropout in the Pasco School District of Washington State. The project was conducted as an initial step toward developing a data…
Descriptors: Data Collection, Data Processing, Dropout Characteristics, Dropout Prevention
Graduate and Early Leaver Follow-Up Survey Results, 1977-1978.
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Foellinger, Juanita; Aspinwall-Lamberts, Julie – 1980
A survey was conducted during Spring 1979 to assess the employment and/or educational activities of Lane Community College (LCC) vocational students who either graduated or dropped out during 1977-78. Members of the survey sample, comprised of 442 graduates and 306 early leavers, were asked to indicate: (1) the full-time/part-time status of their…
Descriptors: Age, Allied Health Occupations Education, Business Education, College Graduates