Distance Education Attrition
Angie Parker, Gonzaga University, United States
IJET Volume 1, Number 4, ISSN 1077-9124 Publisher: Association for the Advancement of Computing in Education (AACE), Chesapeake, VA
A need for research to determine predictors of attrition from distance education is of particular importance because governmental funding to institutions of higher education is often based on attendance. Attrition rates in distance education format have been reported as high as twice that of traditional instruction. One hundred and seventy community college students were the sample for this study. Each completed two instruments: The Rotter's Internal-External Locus of Control scale and a student information sheet. Discriminant analysis was then used to determine predictors of attrition. It was determined that locus of control and source of financial assistance, in particular self-pay, were able to predict dropout with nearly 85 percent accuracy. In addition to qualitative analysis, interviews with non-completers provided insight into personal and private reasons that students had for non-completion. It was determined that lack of time management skills and ill-defined educational goals were the primary reasons given by the students. These findings were consistent with other researchers in the field of distance education. The results of this study are important for practitioners in the area of distance education as student control and time management skills are essential for students working in distance education formats.
Parker, A. (1995). Distance Education Attrition. International Journal of Educational Telecommunications, 1(4), 389-406. Charlottesville, VA: Association for the Advancement of Computing in Education (AACE).
© 1995 Association for the Advancement of Computing in Education (AACE)
ReferencesView References & Citations Map
These references have been extracted automatically and may have some errors. Signed in users can suggest corrections to these mistakes.Suggest Corrections to References
Cited ByView References & Citations Map
Simon Liu, Joel Gomez, Badrul Khan & Cherng-Jyh Yen, George Washington University, United States
International Journal on E-Learning Vol. 6, No. 4 (October 2007) pp. 519–542
Looking for a comprehensive eLearning acceptance framework. A literature review and a tentative map.
Chiara Succi & Lorenzo Cantoni, University of Lugano, Switzerland
EdMedia + Innovate Learning 2006 (June 2006) pp. 912–919
Patricia McGee, The University of Texas at San Antonio, United States
E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2002 (2002) pp. 1887–1890
These links are based on references which have been extracted automatically and may have some errors. If you see a mistake, please contact firstname.lastname@example.org.