Testing a path-analytic model of adult dropout in online degree programs. (January 2018)

• Record Type: Journal Article
• Authors: Choi, Hee Jun; Park, Ji-Hye
• Is Part Of: Computers & education. Volume 116(2018)
• Page Start: 130
• Page End: 138
• Publication Date: 2018-01
• Subjects: Distance education -- Online degree program -- Path-analytic model -- Adult persistence -- Adult dropout; Education -- Data processing -- Periodicals; Education -- Periodicals; Computers -- Periodicals; Computer-Assisted Instruction -- Periodicals; Éducation -- Informatique -- Périodiques; Electronic journals; 370.285
• DOI: 10.1016/j.compedu.2017.09.005
• Languages: English
• ISSNs: 0360-1315

Abstract

Abstract: Using large samples from multiple online degree programs, this study aimed to empirically identify the direct and indirect relationships between major adult dropout factors (i.e., basic scholastic aptitude, physical constraints, interaction with course content, satisfaction, and GPA) and provide educational practitioners with insights that will enable them to indirectly handle uncontrollable adult dropout factors based on the empirical evidence. To achieve these purposes, we formulated and empirically tested a hypothesized path model encompassing multiple hypotheses derived from related literature. We found that the physical constraints variable has statistically significant direct and indirect relationships through interactions with course content, satisfaction, and GPA with adult students' dropout decisions, and the basic scholastic aptitude variable has an indirect relationship with dropout decisions through interactions with course content and GPA. This paper concludes by discussing the implications of our findings for educational practitioners in online degree programs. Highlights: We present a path-analytic model of adult dropout that is statistically acceptable. Physical constraint has direct and indirect effects on dropout decision. The effect of scholastic aptitude is not as strong as that of physical constraint. The relationship between internal dropout factors is clearly identified.