Student Satisfaction Factors

Factors that contribute to the student satisfaction

Chun Kuo and friends (2013) summarized student satisfaction which is reflects how students perceive their learning experiences, is an important measure in program evaluation. Students with a higher level of satisfaction are more persistent in their learning, and research evidence suggests that providing students a satisfying experience helps to maintain and improve retention. In addition, student satisfaction contributes to academic achievement. The more students are satisfied, the more likely they are to do well in the course (Keller, 1983; Pike, 1993). Several studies investigated the factors that contribute to student satisfaction in distance learning environments (Artino, 2007; Bolliger

Unlike traditional classroom instruction, online learning is student-centered and much self-directed effort is required for success (Artino, 2007). Although most of the studies have indicated that the ability to self-monitor and self-evaluate at different learning stages is positively related to student performance or achievement, there is very limited research pertaining to the association between self-regulation and student satisfaction. For example, Artino (2007) found motivational components of self-regulation are positively related to student satisfaction from a sample of participants attending military online training in the U.S. Navy. Puzziferro (2008) studied students who took online courses from a liberal arts community college and indicated that meta-cognitive self-regulation is positively correlated with student satisfaction at a significant level. King, Harner, and Brown (2000) also hypothesized that self-regulation of learning is more important in the distance education context than the traditional context. They employed a forty-item instrument designed to measure the effect of video technology on students, distance learning-related self-regulatory behaviors, and self-efficacy. They found that of various self-regulation factors, goals and study skills were highly significant. They also found that

Grasha’s definition will be used in this paper. Moran (1991) pointed out that there are at least 21 different models of learning style, making it hard to provide an agreed-upon definition. Geisler-Brenstein et al. (1996) compared the controversy to the parable of the three blind men and the elephant, in which each man felt a different part of the elephant and came to the conclusion that it was a different animal. Geisler-Brenstein et al. lamented that “there is little cross-fertilization between disciplines that would allow us to provide a better description of the elephant”. Hichcox (1995) pointed out that “using only one measure assumes that one inventory is more correct than others. At this time that assumption cannot be made”. There is also disagreement as to whether learning styles are fixed or can be modified in response to experiences encountered within a course (Price, 2004). However, all earning style models assume that learning styles are measurable and that matching or mismatching student styles with instructional techniques has a major effect on learning. This paper examines research on learning style as predictors of student satisfaction in UUM online