Learning Styles Continues While Open Admissions Education Essay

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The narrative about learning styles continues while open admissions community colleges and other post-secondary institutions of higher education admit larger and larger populations of underprepared students, so learning the best possible way students take in and process information will benefit instructional design of computer-mediated communication courses. Knowledge of learning styles help teachers examine their own instructional practices, and become sensitive to providing diverse learning experiences (Guild, 2009 p. 18). According to Felder and Sprulin (2005) there is a seriously mismatched, students are uncomfortable and students get discouraged about courses. Cano-Garcia and Hughes (2000) indicate dominant thinking styles are the results of the native personality interacting with family and social environments (pp. 413-430). According to Petrescu and Staancescu (2008) student learning styles have an impact on the quality of higher education, "which requires the necessity or organizing a stimulating learning environment where the student participates to the process of their own education" (p. 49). However, with limited or no use of learning styles in the instructional design students are not engaged in "their own education" (p.49), and are not learning the best way possible.

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This is a problem because when a mismatch exists between learning styles of most students and faculty, faculty should be concerned that the students may become bored and inattentive in class, perform poorly on tests, and get discouraged about courses, curriculum and themselves (Keef, 1979). For instance, according to The National Center for Public Policy and Higher Education (2007) reported in a survey conducted in the 4th quarter 2007, 14,500 students at fifteen colleges indicated that twenty eight percent of dropouts are for academic disqualification. This included 1,200 community colleges across the United States. Graduation rates are on the agenda of U.S. Secretary of Education, Margaret Spelling's new national commission on higher education. It is clear that student learning styles impacts the value of their education.

The topic of learning styles is worthy of investigation for three reasons. First, Sarasin (1998) indicates that the preference or predisposition of an individual to perceive and process information in a particular way or combination of ways is important for the learning process. Second, Wilson (1998) indicates that learning styles and the required skills in utilization of instructional methods for addressing student learning will give faculty a wide array of techniques to use in promoting student learning. Third, many students enter college with little awareness of learning styles, or which skills are needed to be an effective learner, so students have difficulty with active participation in the learning process (Doidge, 2007). According to Petrescu and Stancescu (2008):

"The role of the teacher [professor] remains a main one, but the teachers [professors]

have to renounce old educational practices, and only in this way, the teacher [professor]

would be an organizer of a learning environment adapted to the characteristics, needs,

and learning styles of the students, facilitating the learning process and the developing

metacognitive competencies of the students"( p. 49).

Some of the potential and current ramifications resulting from the problem are according to Tanner and Allen (2004) the use of learning styles will raise more awareness about the diversity among learners. Atkins, Moore, Sharpe and Hobbs (2001) argued that one cause of low participation rates in computer-mediated conferences may be an incompatibility between students learning styles and the style adopted by computer-mediated conferences. According to Wilson (1998), critics will be unconvinced that learning styles-based instruction can improve motivation and performance. The simplest step toward reconciling diverse learning styles and singular pedagogical styles is explicitly to acknowledge the issue and the existence of different learning styles (Tanner & Allen, 2004).

If higher education does nothing about the problem, according to Tanner and Allen (2004), higher education will lose a potential source of future creativity; higher education is constructing environments in which only a subset of learners can succeed, and understanding the variety of learning styles that students bring to the classroom will help more students learn. If we do nothing, it unintentionally causes the loss of able, interested students from post-secondary education because they learn differently and think differently than those who currently teach them. However, if we do not recognize or using learning styles it substantiate and adds to the twenty-eight percent dropout rate for poor academic performance as indicated in the National Center for Public Policy and Higher Education (2007) survey.

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If a balance in teaching and learning styles is achieved both faculty and students will teach and learn in a manner they prefer, which will lead to an increased comfort level and willingness to learn and improve grade performance. At most institutions of higher education learning styles preferences are not an integral part of instructional design, or institutional training. Hewitt, 1997; Sarasin, 1998; Wilson, 1998; and Tanner and Allen, 2004 indicate it does suggest there may be mismatches in teaching styles and student learning styles. Students are not "passive receiver(s) of information, prefabricated knowledge must be replaced with the image of an active student, motivated to practice on authentic learning, to attain specific competencies in information processing, to generate new information and knowledge, to apply these in different situations" (Petrescu & Stancescu, 2008 p. 49). According to Merrienboer, Kirschner, and Kester (unknown date) "recent instructional theories stress authentic learning task as the driving force for learning, but due to the complexity of those tasks learning may be hampered by the limited processing capacity of the human mind" (p. 2). To prevent cognitive overload, "cognitive load theory emphasizes the need to fully integrate support for novice learners" (p. 4). According to Merrienboer at el cite Chandler and Sweller, 1992; Sweller and Chandler, 1994 "learners have to mentally integrate information from the task environment with the given support" (p. 4).

When considering the efficacy for gender, academic achievement and choice of major research, the Felder & Solomon Index of Learning Style is the best choice (Williams-Fike & Rowland et al 2004). The evidence that using learning styles inventories with students and changing teaching methods based on research results have an impact on achievement and motivation (Coffield, et al, 2004 a & b). From the observation of learning style instruments, the clarity of the Felder and Solomon's (2005) Index of Learning Styles helps explain in part its popularity, and it receives 100,000 hits per year and has been translated into several languages (Zywno, 2003), and according to Litzinger, T. at el (2005) learning styles instrument has been judged reliable and has validity as a psychometric instrument.

The disadvantage of learning styles use shows that students should not draw inferences about what students are and are not capable of doing. Learning styles reflect preferences and tendencies; they are not infallible indicators of strengths or weaknesses in either the preferred or the fewer preferred categories of a dimension (Felder & Spurlin, 2005). Too much emphasis on diagnosis and matching makes it likely that students will accept labels and be reluctant to move beyond their 'comfort zone' to develop new skills or styles (Coffield, et al, 2004 a & b). Because most groups of learners present a mixture of learning styles, it is not practical to assess all the individual styles and then try to plan a program which incorporates everyone's preferred style. This approach is a good way to frustrate faculty and is likely to result in failure (MacKeracher, 2004). The theoretical and practical applications of many of the leading models are either under-researched in educational contexts or mired in controversy (Coffield, et al, 2004 a & b). Most of the research statistically demonstrates a modest gain in test scores for students using computer-mediated communication learning tools in comparison with students using traditional face-to-face instruction (Marcy, et al, Unknown date).

For instructional design faculty learning styles offer some fundamental insights into the design process itself because of the range of content and types of activity that absolutely must go on if effective student learning is to take place (Paulhazel.com, 2006). Clark (1983) contends that it is instructional design methods not delivery technology which influence student learning. This echoes the "operational principle," which "describes natural forces being deliberately guided, diverted, transferred, transformed, and otherwise directed for specific human purposes (Gibbons, 2009 p. 3). When a reliable online learning style assessment is incorporated into the beginning of an online course or in an orientation to the online courses, then faculty and course developers should create learning materials that would appeal to the strongest learning style for the course (Garland & Martin, 2005). Rowntree (1992) argues persuasively that developers need to take into account the research on learning styles, and design materials for flexibility, diversity and balance.

Instructional design decisions need to be based not only on desired learning outcomes, but also on motivational, cognitive and volitional views of learning from the students' perspective. This view of the learning process takes into account a contextual learner variable, and leads to a constructivist, learner-responsive view of materials design (Honebein, Duffy & Fishman, 1993). However, 'the instructional designer will not be conversant in all content areas, and as such they must rely on Subject Matter Experts to assist with determining the scope and accuracy of the unfamiliar content" (Keppell, 2003 p. 1).Learning styles research is of enormous significance because it shows the learner's context of application and learning, which is more suitable for instructional design practices (McLoughline, 1999). The overall differences present a profound challenge for instructional designers, as research shows the quality of learning material is enhanced if the material is designed to take into account learners' individual learning styles (Rasmussen, 1998; Riding & Griley, 1999).

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Background of the Study

To contrast the narrative debate in higher education, institutions of higher education are undergoing significant transformation (grounded to virtual), but change must be approved, accepted and ultimately put into practice by the teaching faculty (Jaffee, 1998 p. 23). Because community colleges offer a universal available and affordable opportunity for higher education, community colleges bear a special burden in these revolutionary times. A thorough understanding of learning styles becomes more critical when applied to diverse populations and their success or failure in learning environment (Sims & Sims, 1995). To meet the emerging learning challenges of the 21st century as outlined higher education has to refocus its theoretical framework, use more human performance interventions, technology interventions and assessment tools (Gibbons, 1998). Therefore, two points are essential: post-secondary education must keep pace with new innovation in technology and new practices must be developed.

The impact of doing nothing or slow movement encourages students to change courses, change curriculum, or just dropout; and confused students tend to perform poorly (Bailey, 2003). However, more things may be out of alignment than just Schein's (1998) cultural components. Schien distinguishes technology as changing the internal culture of post-secondary institutions. The consequence, according to Schein, is that the lack of alignment causes the failure of organizational learning. Bailey (2003) indicates that students who find themselves in this environment often unknowingly have been relegated to a lower status within the internal culture of the institution.

According to Guild (2001) "we also know that an individual learner's culture, family background, and socioeconomic level affects his or her learning, the context in which someone grows and develops has an important impact on learning" (p. 1).With a new shift in the learning paradigm (computer-mediated communication), the student learning modality is brought back to the forefront of institutional priorities. Bailey indicates, that "the potential effect of computer-based distance education is perhaps the greatest unknown in the competitive landscape of higher education. To the extent that distance education reduces the need for students to be at a particular place at a specific time and provides an education at a reasonable cost, then the educational market will be free-for-all (p. 1)."

Statement of the Problem

One way to curtail the mismatches (Felder & Spurlin, 2005) between learning styles of students and teaching styles of the professor to improve performance will be to achieve a balance with instructional methods so that learning styles preferences and brain physiology associations are better understood for instructional outcomes. One approach is to minimize the mismatches for students since they enter college for the most part with little awareness of learning styles, or which skills are needed to be an effective learner. This may in part be one of the driving influences to (academic disqualification) dropout because students have difficulty with active participation in the learning process (Rachal & Daigle, 2007). The study will investigate learning style preferences to determine if they are left-right dominant and if they affect grade performance. As cited earlier, the use of new noninvasive technology such as magnetic resonance imaging and electroencephalographic analysis research studies are showing evidence of neurological underpinnings related to brain functions (physiology). Cognitive neuroscientists hold that brain hemisphericity or brain dominance is the tendency of an individual to process information through the left hemisphere or the right hemisphere or in combination (Ali & Kor 2006).

A natural step to achieving that balance is a better understanding of the student's preferred way to take in and process information, which is not fully understood at present, and to coordinate better between the varying teaching methods. To meet the learning challenges of the 21st century society, higher education must address student performance to remain competitive. Evaluating and utilizing learning styles still remain a suggested solution.

Purpose of the Study

The purpose of the study is to investigate student's preferred learning styles preference in computer-mediated communication sociology 101 courses at a two-year "open admissions" post-secondary institution to determine grade performance, as well as whether left-right dominant and neurological underpinnings influence learning style preferences. The investigation will include a qualitative review of research studies using new noninvasive technology such as magnetic resonance imaging and electroencephalographic analysis to show evidence of neurological (brain physiology) underpinnings related to brain functions that are linked to further explanation of learning style preferences.

Rationale

Moore and Thompson (1990, 1997) reviewed much of the research from the 1980s and 1990s and concluded that distance education was considered effective "when effectiveness [was] measured by the achievement of learning, the attitudes of students and by return on investment" (Diaz, 2000), which the study proposes to be grade performance, learning style preferences and neurological associations. It is important to point out that both information and communication technology literacy are foundational skills, which are on par with Math and English (Valenza, 2005).

Research has provided ample evidence that students have different methods of learning, which indicates they have different preferences. For instance, Litzinger, Lee and Wise (2005) indicate that education and liberal arts students are on average visual learners while engineering students on average are sequential, sensing, and visual; the only common preference shown for all three colleges in the study is for visual over verbal. Therefore, if higher education wants to improve student learning more understanding of learning styles are required to develop better instructional strategies. Faculty must be made aware of the differences in student learning styles to alter their preparation and instructional methods.

The research study is quasi-experimental with non-equivalent control group design. The Index of Learning Styles is a psychometric instrument for assessing student learning styles. It is available for free on the Internet (Solomon & Felder, 2004). The instrument has been translated into at least six languages and its website receives about 100,000 hits every year. The instrument was created by Felder and Silverman (1988) using the model "classifies students according to where they fit on a number of scales pertaining to the ways they receive and process information" (p. 674).

Research Questions

Five natural questions (quantitatively and qualitatively) underlie the investigation. Quantitatively, they are:

What is the difference in grade performance between college students using learning style preferences and college students not using learning style preferences in computer-mediated communication courses?

What are the preferred learning styles preferences?

Will the preferences be right or left dominant?

Qualitatively, they are:

How do the respondents' learning style index (left or right dominant)

align with current trends in neurological brain functioning?

Also, the learning style ranges and preferences have been linked by Felder and Spurlin (2005) to brain functioning, and with the latest references from neuroscience (magnetic resonance imaging), and psychological studies (Begley & Schwartz, 2002); (Doidge, 2007); and (Moffett, 2006) have verified brain activity. The ongoing studies (Merzenich, 1987; Kilgard & Merzenich, 1998) in the field of neuroscience and clinical psychology are showing more evidence of such a relationship. This is applicable to instructional design, training and learning performance. The study's conclusions and recommendations section (Chapter 5) will in part discuss brain functionality and the relationship to learning and performance.

Significance of the Study

As 21st century learning and performance challenges drive higher education coupled with technology advancement, "distance education methodologies (computer-mediated communication) have come into prominence (Morrison, 2003)." Factors emerging as a part of post-secondary education in the 21st century are student-learning styles, learning performance and technology performance outcomes. It is important to clarify that learning styles are characteristically cognitive affecting and are psychological behaviors that serve relatively stable indicators of how learners perceive, interact, and respond to the learning environment (Keef, 1979). If the variable affected by treatment does change in the predicted direction, student learning preferences will improve performance (grades). If a balance is achieved in teaching and learning styles, both faculty and students will have two-way facilitation in a manner they prefer, which will lead to increased comfort levels and reengage students the freedom and willingness to learn.

Therefore, in the spirit of this context, the significance of the pending study is the influence of learning styles on grade performance, learning style preferences, and neurological underpinnings in computer-mediated communication. Since the shift in higher education supports the use of and advancements in technology, which increases the demand for computer-mediated communication, the way students take in and process information is critical to pedagogy and learning outcomes.

It may help to reduce poor academic performance leads to academic disqualification (dropout rate 58.2%) at the host institution, and thereby reduce hostile behaviors between student and teacher, cutting classes, change poor attendance and help professors understand better how to deal with teacher-student relationships in a changing learning environment. If the variable affected by treatment does change in the predicted direction, student learning preferences will improve performance (grades). If a balance is achieved in teaching and learning styles, both faculty and students will have two-way facilitation in a manner they prefer, which will lead to increased comfort levels and reengage students the freedom and willingness to learn.

Definition of Terms

There are several (11) keywords used in the study that need definition. They are but not limited to:

Index of Learning Styles (which indicates the preferred student learning style dimension and instrument categories (action-reflective, sensing-intuitive, visual-verbal, and sequential-global) on a range scale from strongly prefer, to moderately prefer to well-balanced either right or left dominant.

Learning style preference (Felder & Spurlin 2005; Keef, 1982; Ausbubel, Novak, & Hanesian, 1978; and Gergorc & Ward, 1979) the way students take in and process information.

Computer-mediated communication (Palloff & Pratt, 1999) quoted Rheingold (1992) indicating that "computer-mediated communication implies cyberspace in which conceptual space is where words and human relationships, data and wealth and power are manifested by people using computer-mediated communication; virtual communities are cultural aggregations that emerge when enough people bump into each other often enough in cyberspace" (p. 21).

Instructional design is the systematic development of instructional specifications using learning and instructional theory to ensure quality of instruction (Alessi & Trollip,1991).

Technology including computers and noninvasive magnetic imaging

Neurological connection shows the brain as the messenger to understanding; it interprets understanding while the mind (fields of force) is entirely and completely derived from the brain's matter (Schwartz & Begley, 2002).

Performance focuses on environmental supports and the students repertory of behavior, and establishes the framework for improvement outcomes (Van Tiem et al 2001, p. 3).

Assumptions and Limitations

From a review of the Internet Interdisciplinary Institute (2006), there are two assumptions based on comparative research questions: "Is distance education as good as, or better than traditional education?" Will the "fluency" with information technology require more intellectual capacities than the rote learning of software and hardware associated with "computer literacy?" The focus is still on the technology itself. For higher education, literacy augments students' competency with evaluating, managing and using information, thereby addressing 21st century learning challenges.

Several limitations exist, such as the scheduling of computer-mediated communication courses and face-to-face classes for the study, and acquiring the most appropriate technology assessment tools to measure study respondents. The learning styles assessment tool is online and approval was received from Dr. Felder (Appendix C).

Theoretical/Conceptual Framework

The theoretical framework as postulated by Ausubel, Novak and Hanesian, 1978; Keef, 1982; Sarasin, 1998; Zywno, 2003 and Litzinger, Lee and Wise, 2005 Ramirez and Castenada (1974) and Witkin, 1976 indicates that learning styles are field dependent/global or field-independent/analytic; meanwhile Georgorc, 1979 indicates they are concrete-abstract and random-sequential. Dunn and Dunn (1979) use four groups of elements, so learners have distinct preferences such as environmental (sound, light and temperature), emotional (motivation, persistence and responsibility), sociological (working along, with others and with adults) and physical (perceptual strengths, visual, auditory and kinesthetic). The history of cognitive styles research has a continuum from Jung (1923), to Allport (1937), then Messsick (1967) including Kolb (1976) to Felder and Solomon (2005). Kolb initiated the era of testing instruments, so most if not all instruments before this era had less than significant reliability and validity. One of the perplexing issues in terms of computer-mediated communication that is not mentioned as part of the instructional method is student learning styles preferences and performance. It has been noted that students have "different strengths and preferences in the way they take in and process information (Litzinger, et al 2005)." There are several theories of cognitive style, so current trends have allowed the blending between learning and thinking style definitions, and theorists were cautioned not to accept just a single definition as being the only correct choice (Sternberg, 1997 pp. 13, 15-40).

Of the several learning style models presented in the literature review, the use of the Felder-Solomon's Index of Learning Styles will allow students the ability to maximize their intellectual, physical, and emotional strengths to improve performance. Since the psychometric questionnaire is online students and faculty will receive their responses immediately, or what McKenna (1997) has called "real time," the lapse between input (use) and output (results). Finally, learning style profiles only suggest behavior tendencies rather than being a predictor of behavior (Felder & Spurlin, 2005).

In summary, the emphasis of technology implementation as described is a cognitive process in terms of computer-mediated communication (DE/e-learning) use, student performance, and that faculty teaching is changing from instructivist to constructivist (cognitive) model. The shift from face-to-face to computer-mediated communication (DE/e-learning) for faculty, students and administrators proposes that the act will cause students and faculty to recognize gaps or conflicts in their mental models. Therefore, this will create institutional opportunities for mental model revision (Holmes, 2003). Part of the mental model revision for faculty is that this makes learning very much the responsibility of the learner, who is an active, not passive partner in the learning partnership.

Organization of the Remainder of the Study

Chapter two will be a review of the research literature about learning styles performance and technology literacy assessment, which is the rationale for the research. Chapter 3 will provide a detailed description of the study methodology, as well as design for the study and will emphasize mixed-research. The last two chapters will focus on a general discussion, results, and a conclusion to complete the final two chapters (Holmes, 2003).