Barriers to distance education: A factor‐analytic study

American Journal of Distance Education 01/2001; 15:7-22. DOI: 10.1080/08923640109527081

ABSTRACT This article reports on a large‐scale (n = 2,504), exploratory factor analysis that determined the underlying constructs that comprise barriers to distance education. The ten factors found were (1) administrative structure, (2) organizational change, (3) technical expertise, (4) social interaction and quality, (5) faculty compensation and time, (6) threat of technology, (7) legal issues, (8) evaluation/effectiveness, (9) access, and (10) student‐support services.

Download full-text


Available from: Zane Berge, Feb 06, 2014
  • Source
    • "Access to Internet is a critical and fundamental requirement for e-learning (Muilenburg & Berge, 2001; MacKeogh & Fox, 2009; Mashhour & Saleh, 2010). "
    [Show abstract] [Hide abstract]
    ABSTRACT: E-learning is used to facilitate off-campus students' learning as well as on-campus students' learning. This study focuses on the barriers to e-learning adoption and implementation for on-campus students in China's traditional higher education institutions (HEIs). An exploratory factor analysis (EFA), based on one survey on the perceptions of e-learning professionals regarding the barriers to e-learning for on-campus college students, was conducted to explore the underlying structure of e-learning barriers at the institutional level. Responses from 141 participants were analyzed through the EFA which identified 9 barrier factors. Findings indicated that weak external drivers, insufficient inner efforts and lack of incentives for teachers were likely more important barriers to e-learning adoption and implementation for on-campus students than that for off-campus students. Implications of these e-learning barriers and future research were also discussed.
    IADIS International Conference e-Learning 2012; 07/2012
  • Source
    • "Berge (1999) argues that interaction among students and between the students and the instructor is essential for success in higher education. Muilenburg and Berge (2001) claim that these types of interactions are necessary for course satisfaction; and Münzer (2003) explains that, as social beings, students need interaction with others for motivational reasons. Other researchers claim that synchronous interaction can enable more efficient and effective communication, because students are able to listen to each others' voices, conversational tones, and emotional expression (Park & Bonk, 2007a), correct misconceptions (Finkelstein, 2006; Park & Bonk, 2007b), engage spontaneously (Beuschel, Gaiser, & Draheim, 2003; Fish, Kraut, & Chalfonte, 1990), get more personal and real-time attention (Finkelstein, 2006; Münzer, 2003), share differing perspectives (Bober & Dennen, 2001; Bowden & Marton, 1998; Mason, 1994), and develop a sense of community (Duemer et al., 2002). "
    [Show abstract] [Hide abstract]
    ABSTRACT: This article reports on a two-year ethnographic study of learners participating in multi-site, graduate-level education classes. Classes sometimes met face-to-face in the same physical location; at other times part of the class met physically elsewhere. Yet all were linked through the virtual space. Ethnographic analysis of four data types explored how the instructor and students were able to interact through videoconferencing technologies. Most of the interaction occurred between the local and distance learners by way of cultural guides, local students assigned to host a distance learner through Google Video chat. The distance learners were able to receive real-time attention from the instructor and were able to share differing perspectives that contributed to increased satisfaction in the course. These interactions allowed for a dynamic collaborative effort among a diverse set of actors in the field of education.
    Distance Education 11/2011; 32(3):357-381. DOI:10.1080/01587919.2011.610289 · 0.97 Impact Factor
  • Source
    • "Institutional supports A systematic support system seemed to improve student persistence rates in online courses. In their factor analysis study of barriers to distance education, Muilenburg and Berge (2001) identified a model of ten factors that explained 52% of data variances. Five of ten factors were related to institutional supports: administrative structure , faculty compensation and time, evaluation/effectiveness, access, and student-support services. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Although online learning is expanding in availability and popularity, the high dropout rates remain a challenging problem. In this paper, we reviewed the existing empirical studies on online course dropouts in post-secondary education that were published during the last 10years. We identified 69 factors that influence students’ decisions to dropout and classified them into three main categories: (a) Student factors, (b) Course/Program factors, and (c) Environmental factors. We then examined the strategies proposed to overcome these dropout factors: (a) understanding each student’s challenges and potential, (b) providing quality course activities and well-structured supports, and (c) handling environmental issues and emotional challenges. Finally, we discussed issues regarding dropout factors and strategies for addressing these factors and offered recommendations for future research. KeywordsDropout factors–Online course–Strategies–Higher education–Future research
    Educational Technology Research and Development 10/2011; 59(5):593-618. DOI:10.1007/s11423-010-9177-y · 1.09 Impact Factor
Show more