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Vark Learning Styles Essay Sample

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Introduction of TOPIC

Students’ Learning StylesLearning is a complex process of acquiring knowledge or skills involving a learner’s biological characteristics/senses (physiological dimension); personality characteristics such as attention, emotion, motivation, and curiosity (affective dimension); information processing styles such as logical analysis or gut feelings (cognitive dimension); and psychological/individual differences (psychological dimension) (Dunn, Beaudry, & Klavas, 1989). Due to the multiples dimensions of differences in each learner, there have been continuing research interests in learning styles. Some 21 models of learning styles are cited in the literature (Curry, 1983) including the Kolb learning preference model (Kolb, 1984), Gardner’s theory of multiple intelligence (Gardner, 1983), and the Myers-Briggs Personality Type Indicators (Myers & Briggs, 1995).

The basic premise of learning style research is that different students learn differently and students experience higher level of satisfaction and learning outcomes when there is a fit between a learner’s learning style and a teaching style. This study uses the physiological dimension of the study of learning styles, which focus on what senses are used for learning. A popular typology for the physiological dimension of the learning styles is VARK (Visual, Aural, Read/write, and Kinesthetic) (Drago & Wagner, 2004, p. 2). 1)

Visual: visual learners like to be provided demonstrations and can learn through descriptions. They like to use lists to maintain pace and organize their thoughts. They remember faces but often forget names. They are distracted by movement or action but noise usually does not bother them. 2)

Aural: aural learners learn by listening. They like to be provided with aural instructions. They enjoy aural discussions and dialogues and prefer to work out problems by talking. They are easily distracted by noise. 3)

Read/write: read/write learners are note takers. They do best by taking notes during a lecture or reading difficult material. They often draw things to remember them. They do well with hands-on projects or tasks. 4)

Kinesthetic: kinesthetic learners learn best by doing. Their preference is for hands-on experiences. They are often high energy and like to make use of touching, moving, and interacting with thei

r environment. They prefer not to watch or listen and generally do not do well in the classroom. One

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can speculate that a different set of learning styles is served in an online course than in a face-to-face course. We assume that online learning systems may include less sound or oral components than traditional face-to-face course delivery systems and that online learning systems have more proportion of read/write assignment components, Students with visual learning styles and read/write learning styles may do better in online courses than their counterparts in face-to-face courses.

Hence, we hypothesized: H2a: Students with visual and read/write learning styles will experience a higher level of user satisfaction. H2b: Students with visual and read/write learning styles will report higher levels of agreement that the learning outcomes of online courses are equal to or better than in face-to-face courses. Instructor Knowledge and FacilitationThe Determinants of Students’ Perceived Learning Outcomes and Satisfaction in University Online Education: An Empirical Investigation† Sean B. Eom1,*,

H. Joseph Wen1,
Nicholas Ashill2
Article first published online: 12 JUL 2006
DOI: 10.1111/j.1540-4609.2006.00114.x
Decision Sciences Journal of Innovative Education

Decision Sciences Journal of Innovative EducationVolume 4, Issue 2, pages 215–235, July 2006 Students are the primary participants of e-learning systems. Web-based e-learning systems placed more responsibilities on learners than traditional face-to-face learning systems. A different learning strategy, self-regulated learning, is necessary for e-learning systems to be effective. Self-regulated learning requires changing roles of students from passive learners to active learners. Learners must self-manage the learning process. The core of self-regulated learning is self-motivation (Smith, 2001). Self-motivation is defined as the self-generated energy that gives behavior direction toward a particular goal (Zimmerman, 1985, 1994).

The strength of the learner’s self-motivation is influenced by self-regulatory attributes and self-regulatory processes. The self-regulatory attributes are the learner’s personal learning characteristics including self-efficacy, which is situation-specific self-confidence in one’s abilities (Bandura, 1977). Because self-efficacy influences choice, efforts, and volition (Schunk, 1991), a survey question (Moti1 inAppendix A) representing self-efficacy is used to measure the strength of self-motivation. The self-regulatory processes refer to the learner’s personal learning processes such as attributions, goals, and monitoring. Attributions are views in regard to the causes of an outcome (Heider, 1958). A survey question (Moti2 in Appendix A) representing a controllable attribution is used to measure the strength of self-motivation.

One of the stark contrasts between successful students is their apparent ability to motivate themselves, even when they do not have the burning desire to complete a certain task. On the other hand, less successful students tend to have difficulty in calling up self-motivation skills, like goal setting, verbal reinforcement, self-rewards, and punishment control techniques (Dembo & Eaton, 2000). The extant literature suggests that students with strong motivation will be more successful and tend to learn the most in Web-based courses than those with less motivation (e.g., Frankola, 2001; LaRose & Whitten, 2000). students’ motivation is a major factor that affects the attrition and completion rates in the Web-based course and a lack of motivation is also linked to high dropout rates (Frankola, 2001; Galusha, 1997). Thus, we hypothesized: H1a: Students with a higher level of motivation will experience a higher level of user satisfaction. H1b: Students with a higher level of motivation in online courses will report higher levels of agreement that the learning outcomes equal to or better than in face-to-face courses.

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