ERIC Number: EJ1420338
Record Type: Journal
Publication Date: 2023
Pages: 19
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1537-2456
EISSN: EISSN-1943-5932
Predictors of Persistence and Success in Online Education
Sami Mejri; Steven Borawski
International Journal on E-Learning, v22 n3 p239-257 2023
This article will address predictors of success for online students. A survey questionnaire was used to gather data concerning online students' social and educational readiness levels at a four-year private university in the Midwestern United States. Of the 4,050 potential participants, 250 (6.23%) responded to the survey. Stepwise regression revealed two Models for predicting student performance on two key dependent variables in this study. The first Model sought to predict student success based on their self-reported views on whether they felt successful in their online courses. This Model revealed 11 survey questions that were significant predictors of students' self-reported success scores, b = 0.382, t (17.737) = 5.399, p < 0.001. The eleven questions in the Model also explained a significant proportion of variance in the self-reported success scores, R[superscript 2] = 0.472, F (1, 171) = 29.15, p < 0.001. The second Model focused on the dependent variable of students' self-reported grade point average (GPA). Of the questions asked in the survey, the second Model showed eight statistically significant predictors of student GPA, b = -0.397, t (110.066) = -5.767, p < 0.001. These eight survey questions explain a significant portion of the variance for students' self-reported grade point averages, R[superscript 2] = 0.359, F (1, 178) = 33.261, p < 0.001. These findings shed light on the student perspective's importance concerning persistence and success in online education. Limitations of the study and recommendations for future research were provided.
Descriptors: Academic Persistence, Success, Online Courses, Readiness, Undergraduate Students, Student Attitudes, Predictor Variables, Grade Point Average, Statistical Analysis, Models
Association for the Advancement of Computing in Education. P.O. Box 719, Waynesville, NC 28786. Tel: 828-246-9558; Fax: 828-246-9557; e-mail: info@aace.org; Web site: http://www.aace.org
Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A