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Direct linkYukselturk, Erman; Ozekes, Serhat; Turel, Yalin Kilic – European Journal of Open, Distance and E-Learning, 2014
This study examined the prediction of dropouts through data mining approaches in an online program. The subject of the study was selected from a total of 189 students who registered to the online Information Technologies Certificate Program in 2007-2009. The data was collected through online questionnaires (Demographic Survey, Online Technologies…
Descriptors: Online Courses, Distance Education, Dropout Characteristics, Prediction
HANSEN, M. DUANE; WENZEL, GUSTAVE G.
INSTEAD OF FOCUSING ON STUDENT CHARACTERISTICS, AS DO MOST DROPOUT STUDIES, THIS ONE (1) CONSIDERS SPECIFIC INSTITUTIONAL CHARACTERISTICS OF GRADING PRACTICES, (2) ANALYZES THESE PRACTICES WITHIN A GIVEN TERM INSTEAD OF OVER SEVERAL YEARS, AND (3) BROADENS THE DEFINITION OF ATTRITION TO INCLUDE BOTH FAILURE AND WITHDRAWAL. IT ATTEMPTS TO IDENTIFY…
Descriptors: Data Processing, Dropout Rate, Dropout Research, Followup Studies
PDF pending restorationIngels, Steven J.; And Others – 1992
This manual has been produced to familiarize data users with the procedures followed for data collection and processing of the first follow-up dropout component of the National Education Longitudinal Study of 1988 (NELS:88). Necessary documentation is also provided for use of the data files. The base-year population covered by the NELS:88 included…
Descriptors: Data Collection, Data Processing, Databases, Dropout Research
Bower, Cathleen; Meyers, Ed. – 1976
The NCHEMS Information About Students (IAS) project has as one of its primary goals the development of procedures and materials to assist institutions of postsecondary education in conducting attrition studies. It was the intent of the IAS project to develop and pilot test a questionnaire and accompanying procedures that would help institutions…
Descriptors: Data Analysis, Data Processing, Dropout Characteristics, Dropout Research
