Performance Factors of a "Full Distance Learning": The Case of Undergraduate Students in Academic Exchange

Abstract

Various e-learning systems have been developed and implemented in educational contexts. However, few studies try to go beyond the experimental level of identifying numerous factors that influence this technology and apply them to a real academic class of students. This article based on an in-depth analysis of a business school case-Montpellier Business School (France)-and survey data from 405 students assessed on their use of the e-learning platform, helps illuminate the patterns involved in e-learning performance. A literature review on e-learning performance factors is realized and a theoretical model focusing on three dimensions of e-learning performance-the learner side, the institutional environment and the e-learning system per se-is presented and tested empirically. The key findings of this paper identify motivation and selfdiscipline of students as main drivers of e-learning outcomes. Other results show that the integration of e-learning in a pedagogical program requires the analysis of its performance not only from learners and instructors point of view, but also from the underlying strategic perspective of the institution.

Influence of online learning skills in cyberspace

“…H3 and H6 thus are proven to be valid. Such a finding is in line with the work done by Meissonier et al (2006) in which they identified that motivation and self‐disciplines of students are the main drivers of e‐learning outcomes. In other words, only through proper learning behaviors, such as the intention to learn or self‐regulation to be persistent in learning, can better learning outcome be achieved.…”

“…As Chen et al (2008) pointed out, the critical incidents that affect e‐learning satisfaction are classified into four categories: administration, functionality, instruction and interaction. Past research indicates the factors influencing the outcomes of e‐learning include learner characteristics, such as proactive personality and learning goal orientation (Kickul and Kickul, 2006), learning strategy (Santhanam et al , 2008), learning motivation (Meissonier et al , 2006), effective or appropriate e‐learning environment (Gregg, 2007; Wangpipatwong and Papasratorn, 2007), technology acceptance, system quality (Chang and Tung, 2008) and so on. Moreover, within the field of learning behavior, there is considerable research concerning learners' attitudes (Sun and Willson, 2008), instructional technologies (Wang, 2008), learning resources (Ouyang and Zhu, 2008), learning environments (Leung and Fung, 2005), learning methods (Wen and Stefanou, 2007), group collaborations (Webb et al , 2006) and course content (Bird, 2007; Young and Ku, 2008), among others.…”

Computer Self‐Efficacy and Motivation to Learn in a Self‐Directed Online Course

“…The role of motivation in the learning process and outcomes has also recently been extended to the VLE context. Motivation has been linked with the satisfaction and final grades of students (Klein et al, 2006) and other e‐learning outcomes when combined with learner self discipline (Meissonier, Houze, Benbya, & Belbaly, 2006). With respect to our specific focus on self‐directed learning in VLEs, motivation has been theorized as an important element and a critical enabler (Piccoli et al, 2001).…”

Investigating the Attitude of Students Towards Online Learning

“…Furthermore Meissonier et al (2006) went on to state that not only do online learning instructors require additional training and resources but also require a technical team responsible for helping to design and post the professor's curriculum on-line. An incentive system for professors and instructors also must be put in place for those willing to tackle the challenge of distance teaching, recognizing that more work, training, and preparation is required for these types of classes (Meissonier et al, 2006).…”