Does the learning style of students depend on their area of concentration in business?
Abstract:
This paper is a study of the learning styles of business students at California State University San Bernardino as they relate to the areas of concentration within the College of Business and Public Administration (CPBA). It explores and compares the differences in learning style that exists between management, marketing, accounting, finance, public administration and information decision science majors. Results indicate the largest difference is 1.58 points between accounting and marketing concentrations on the Sensory/Intuitive construct on an 11 point scale. Results do indicate a preference for interactive, sensory, visual and sequential learning experience. It is hoped that by studying the differences in learning styles that the readers may be able to adjust their teaching styles to assist students in the learning process.

Subject:
Teachers
Business schools
Students
Authors:
Luck, Gypsi
Estes, Jim
Pub Date:
07/01/2011
Publication:
Name: Review of Business Research Publisher: International Academy of Business and Economics Audience: Academic Format: Magazine/Journal Subject: Business, international Copyright: COPYRIGHT 2011 International Academy of Business and Economics ISSN: 1546-2609
Issue:
Date: July, 2011 Source Volume: 11 Source Issue: 4
Product:
Product Code: 8244000 Business & Secretarial Schools NAICS Code: 61141 Business and Secretarial Schools SIC Code: 8244 Business and secretarial schools
Organization:
Organization: California State University and College System
Geographic:
Geographic Scope: California Geographic Code: 1U9CA California
Accession Number:
272616376
Full Text:
1. LITERATURE REVIEW OF LEARNING STYLES

Students perceive and process information in different ways. How a student perceives and processes information is referred to as a student's learning style (Felder & Silverman, 1988 and 2002). How much they learn may be impacted by native ability, prior experience, and/or the compatibility of their learning style with an instructor's design and delivery of a teaching-learning experience. When a student's learning style is compatible with an instructor's teaching style (i.e., the way an instructor designs a teaching-learning experience) learning should be enhanced. Alternatively, when a student's learning style is incompatible with an instructor's teaching style, learning may be impeded (Felder & Silverman, 1988 and 2002).

Of the many learning style models developed over the years, five are described extensively in learning styles literature (i.e., Jung's Theory of Psychological Type, Kolb's Experiential Learning Theory, Felder and Silverman's Index of Learning Styles, Herrmann's Thinking Preferences, and Dunn and Dunn's Need for Individual Diagnosis and Prescription) (Felder & Brent, 2005). Of the five learning style models, this literature review focuses on the Felder and Silverman Index of Learning Styles (ILS). The ILS is a self-scoring instrument available in both traditional and online formats. The ILS assesses an individual's learning preferences on four dimensions (i.e. Sensory/Intuiting, Visual/Verbal, Active/Reflective, and Sequential/Global). Felder states that the four dimensions are neither original nor comprehensive. Rather, they build on concepts developed in the learning style models mentioned above (Felder and Silverman, 1988 and 2002).

The original ILS model included five dimensions of learning (i.e., Sensory/Intuitive--perception, Visual/Auditory--input, Inductive/Deductive--organization, Active/Reflective--processing, and Sequential/Global--understanding). In 2002, Felder revised and reissued the original 1988 paper. In the preface to the revised paper, Felder explained that he made two significant changes to the ILS model. He dropped the Inductive/Deductive dimension and changed Visual/Auditory to Visual/Verbal dimension (Felder & Silverman, 1988 and 2002). With this change, the ILS was reduced to four dimensions of learning (i.e., Active/Reflective--processing, Sensory/Intuitive--perception, Visual/Verbal--graphic presentation, and Sequential/Global--understanding).

The revised Felder and Silverman 1988 paper described four dimensions of learning. For the purposes of this paper the revised ILS will be referred to as the ILS. The ILS uses a forced choice model where participants are asked to choose between two alternatives to complete a sentence. These alternatives represent the opposite ends of the individual ILS constructs (Litzinger, Lee, Wise & Felder, 2007). The survey seeks to determine preferences for one learning style or another; therefore, it uses a dichotomous format which negates the possibility of a "no opinion" response (Converse & Presser, 1986). Following are brief descriptions of the dimensions of learning based on a working paper document prepared by Felder & Soloman available from North Carolina State University (Felder and Soloman, 1988, 2002).

Using a sample of 448 engineering students, Litzinger, Lee, Wise & Felder (2007), reported the ILS had an internal consistency reliability ranging from a low of .55 to a high of .76 across the four learning style scales. The reliability of the ILS scales for the current study can be found in Table 1.

1.1 ACTIVE/REFLECTIVE

Active learners tend to retain and understand information best by doing something active with it-discussing or applying it, explaining it to others or actively testing information in some way. Active learners do not perform well in lecture situations. Reflective learners tend to use observation, be theoreticians and prefer to work on their own (Felder & Silverman, 1988).

1.2 SENSORY/INTUITIVE

Sensory learners like learning facts through explicit data and experimentation (Felder & Silverman, 1988). They like details, are good at memorizing facts, and prefer learning through hands-on activities. They are practical and careful, and prefer learning things that connect to the real world. Intuitors, on the other hand, prefer learning by discovery. They are good at learning concepts and easily grasp abstractions and mathematical formulations. They tend to work fast and are innovative in their approach to learning processes (Felder & Silverman, 1988).

1.3 VISUAL/VERBAL

In 2002, Felder modified this construct to include both graphics and sounds. Based on previous research, he felt that to a visual learner, "a picture is truly worth a thousand words, whether they are spoken or written" (Felder & Henriques, 1995). Visual learners prefer to see pictures, diagrams, charts, and multimedia resources rather than gathering data through auditory means (Felder & Silverman, 1988). "Auditory learners remember much of what they hear and more of what they hear and then say. They get a lot out of discussion, prefer verbal explanation to visual demonstration and learn effectively by explaining things to others" (Felder & Silverman, 1988, p. 676).

1.4 SEQUENTIAL/GLOBAL

Sequential learners tend to learn in building blocks, with each block flowing logically to the next block. Sequential learners may not understand all that they learn, but they can put the pieces together. Global learners tend to learn randomly, absorb information on-the-fly, put 2+2 together to see the big picture, without necessarily understanding how they managed to put things together (Felder & Silverman, 2002).

2. STUDIES USING THE ILS

While Felder's work focused on engineering students, his ILS instrument is widely used by other disciplines. Felder and Spurlin hypothesized that students attracted to a specific field (e.g., engineering) should have different learning styles from students in much different fields (e.g., humanities) (Felder and Spurlin, 2005). Their hypothesis has been the focus of several research studies.

For example, in 2008 Thomas Sandman used the ILS to assess learning style preferences of more than 300 undergraduate business telecommunications students. While Sandman found all ILS learning style classifications within his test group, most of his business telecommunication students were highly visual learners. While his student group shared some commonality with Felder's engineering students, their overall learning styles were different (Sandman, 2008). In this paper, the authors attempt to draw a comparison between learning styles of business students and their area of concentration in business.

Felder and Spurlin (2005) suggested that the ILS has two principal uses. First, it can help instructors to understand diversity of learning styles within their classes, which in turn should help them design teaching-learning experiences that better address the needs of all their students. Second, the ILS can give students insight into their possible learning strengths and weaknesses.

Felder suggested that teachers use the ILS and other common learning styles models to help design effective instruction. Learning style models help students better understand how they prefer to learn. Learning style models help both teachers and students to realize that not everyone teaches and learns the same way (Felder, 2010).

3. METHODS

Participants included 1144 business students from all concentrations in the business school at California State University, San Bernardino were surveyed via surveymonkey.com. Data from students who claimed a single concentration as their major were used in the study. Using a participant more than one time, as with a student with a double concentration major, would have caused validity issues. Of the 1144 surveys, 770 participants remained in the subject pool. The survey included demographic information such as, "What is your age range" and "What is your income level", as well as the 44-item ILS. Participants were encouraged but were not required to participate. Informed consent forms were required of all participants before the survey was administered.

In the literature, the ILS items are scored as -1 or +1 with a range of scale scores from -11 to +11. The appropriate items are summed to achieve a scale score with a midpoint of 0. The ILS was scored differently in the current study. We chose to score each dichotomous item as 1 or 2, therefore, the minimum score would be 11 with a maximum score of 22. The midpoint of each ILS scale would be 16.5 under the rubric used in the current study. Table 2 provides descriptive statistics.

As stated earlier, the ILS uses a dichotomous forced-choice scale. Potential biases and validity concerns may arise with the use of all self-report measures of participant responses, such as systematic response distortions, and the social desirability effect (Podsakoff, MacKenzie, Paine, & Bachrach, Podsakoff, 2003). However, since the survey was anonymous it is believed that these concerns were minimized.

The author's expect there might be differences between the learning styles of Accounting majors and Finance majors. Because of this belief, all statistics were performed looking at each major as well as the combined concentration to align with the California State University, San Bernardino Business school concentrations. Therefore, in Table 2 the majors are broken out into accounting and finance as a concentration as used in the CSU, San Bernardino Business School, as well as Accounting and Finance separately as individual concentrations.

4. RESULTS:

All outcomes fell below the ILS scale mean of 16.5 except the Information Decision Sciences Active/Reflective construct which measured 16.60. See Table 3 The greatest difference between concentrations is the Sensory/Intuitive construct where the Marketing concentration is 1.58 points higher than the Accounting concentration. See Table 4. The result with the largest distance from the ILS scale mean is the Information Decision Sciences Visual/Verbal result which is 2.36 points below the scale mean. See Table 5. Findings suggest that all concentrations are very similar in their learning style preferences as illustrated in Table 7. Standard Deviations were very small also illustrating similarity of learning style preference. Overall, results indicate a slight preference for an interactive, sensory, visual and sequential learning experience, however, findings are very close to the ILS scale mean.

Notes: ACT_REF--refers to active vs. reflective, SNS_INT--refers to sensory vs. intuitive, VIS_VRB--refers to visual vs. verbal, SEQ_GLO--refers to sequential vs. global. Mgmt refers to the Management concentration. Sample sizes vary depending on the number of students who self identified as having that major. The numbers in parentheses represent the standard deviations.

Information Decision Sciences is above the ILS average with a score of 16.6. Results are not significantly different between concentrations illustrating participants have a slight preference for an Active learning style Those with an Active learning preference tend to retain and understand information best by doing something active with it including discussions and applying the information in some way such as with case studies. Active learners do not perform well in lecture situations (Felder & Silverman, 1988).

Table 4 illustrates the most significant finding. The Sensory/Intuitive construct for the Marketing concentration is 1.58 points higher than the Accounting concentration. Marketing requires the use of an intuitive process more than Accounting, therefore, this result makes sense. All other results are not significantly different between concentrations illustrating participants have a sensing learning style preference. Those with a Sensory learning preference like learning facts through explicit data and experimentation, like details, are good at memorizing facts, and prefer learning through hands-on activities. They are practical and careful, and prefer learning things that connect to the real world (Felder & Silverman, 1988).

Results are not significantly different between concentrations illustrating participants have a visual learning style preference. Those with a Visual learning preference prefer to see pictures, diagrams, charts, and multimedia resources rather than gathering data through auditory means (Felder & Silverman, 1988).

Results are not significantly different between concentrations illustrating participants have a sequential learning style preference. Those with a Sequential learning preference tend to learn in building blocks, with each block flowing logically to the next block (Felder & Silverman, 1988).

[TABLE 3 OMITTED]

[TABLE 4 OMITTED]

[TABLE 5 OMITTED]

[TABLE 6 OMITTED]

Table 7 illustrates the similarity of results across concentrations and the ILS scales.

5. DISCUSSION

By creating an awareness of the differences in learning styles by area of concentration in the business school, the authors hope to aid educators in designing effective instruction. Recognizing that not every educator teaches the same way nor does every student learn the same way is important to meet the needs of today's students. Results from this study indicate the past University paradigm is outdated and unsatisfactory for today's students in a business school. The former University paradigm was for a professor to stand in the front of the classroom and lecture while students took notes. Often a teaching assistant handled student questions. Currently, book publishers include Power Point slides, case studies, exercises and videos to support faculty classroom preparation. According to interviews with students when professors use Power Points, usually the professor flips through the slides without elaboration, or reads to students directly from the slides. Usually, case studies, classroom exercises, and videos are not used. This is a direct contradiction to the findings of this study.

Students in this study had a slight preference for an Active, Sensory, Visual and Sequential learning experience. This translates to business students having a tendency to need to participate in their education by actively manipulating the information to be learned, using discussions and case studies, experimentation with hands-on activities, using pictures, diagrams, charts and multimedia resources, and learning by building information one idea upon another (Felder & Silverman, 2002).For those who teach across disciplines in introductory courses, perhaps this increased awareness will aid in course preparation and facilitate a better understanding among students of cross disciplinary material.

There is another possible explanation for the study outcome. These results may reflect cohort differences and not be limited to business students. Most student participants were under age 30 and grew up with different expectations regarding how they learn. Therefore, continuing research is warranted to explore if these results could be explained by the age of the student participants.

REFERENCES:

Converse, J.M., & Presser, S. (1986). Survey questions: Handcrafting the standardized questionnaire. Newbury Park, Ca: Sage Publications.

Felder, R. M. (2010). Are learning styles invalid? (Hint: No). On Course Newsletter. Retrieved from http://oncourseworkshop.com/Learning046.htm

Felder, R. M., & Brent, R. (2005). Understanding Student Differences [Abstract]. Journal of Engineering Education, 94(1), 72.

Felder, R.M., & Henriques, E.R. (1995). Learning and teaching styles in foreign and second language education. Foreign Language Annals, 28(1), 31. Retrieved from http://www4.ncsu.edu/unity/lockers/users/f/felder/public/ Papers/FLAnnals.pdf

Felder, R. M., & Silverman, L. K. (1988). Learning and teaching styles in Engineering Education. Engr. Education, 78(7), 681.

Felder, R. M., & Silverman, L. K. (2002). Authors preface: Learning and teaching styles in Engineering Education. Engr. Education, 78(7), 681.

Felder, R. M., & Spurlin, J. (2005). Applications, reliability and validity of the Index of Learning Styles. Int. J. Engng Ed., 21(1), 112. Abstract retrieved from http://www4.ncsu.edu/unity/lockers/users/f/felder/ public/ILSdir/ILS_Validation(IJEE).pdf

Litzinger, T. A., Lee, S. H., Wise, J.C., & Felder, R.M. (2007). A psychometric study of the index of learning styles. Journal of Engineering Education. 96, (4), 309-319.

Podsakoff, P. M., MacKenzie, S. B., Paine, J. B. & Bachrach, D. G. (2003). Organizational citizenship behaviors: A critical review of the theoretical and empirical literature and suggestions for future research. Journal of Management. 26 (3), 513-563.

Sandman, T. (2008). Comparing learning styles of MIS students and engineering/computer science students. Journal of the Academy of Business and Economics.

Gypsi Luck, California State University San Bernardino

Jim Estes, California State University, San Bernardino

Dr. James Estes earned his PhD from California Coast University and is a 6th year tenured Associate Professor of Finance at California State University San Bernardino. In addition to his MBA, Estes also holds the CFP, CLU, CHFC and CPCU designations, and currently manages $40 million of discretionary private equity for Wedbush Securities, where he is Vice President of Securities. He retired as President/CEO of a $750 million financial services firm to teach and is also a securities arbitrator for FINRA.

Dr. Gypsi Luck has her Ph.D. in Organizational Psychology; She has six years as adjunct faculty Cal State University. She has fifteen years experience as an external consultant regarding issues of leadership, teams, coaching, motivation, rewards, organizational culture, organizational development, change management, training and adult learning.
TABLE 1
CONSISTENCY - RELIABILITY OF ILS SCALES

          Reliability

ACT_REF   .53
SNS_INT   .69
VIS_VRB   .71
SEQ_GLO   .50

TABLE 2
DESCRIPTIVE STATISTICS FOR ILS SCALE BY ACADEMIC MAJOR

ILS Scale   Accounting   Acct     Finance   Mgmt
            & Finance

ACT_REF     16.32        16.29    16.22     16.02
            {2.17}       (1.90)   (2.58)    (2.17)

SNS_INT     14.32        14.29    14.36     14.69
            (2.40)       (2.35)   (2.36)    (2.52)

VIS_VRB     14.63        14.69    14.57     14.90
            (2.59)       (2.59)   (2.53)    (2.50)

SEQ_GLO     15.28        15.39    15.21     15.38
            (2.0)        (1.98)   (2.05)    (2.06)

Sample      321          219      127       244
size

ILS Scale   Public   Marketing   Information
            Admin                Decision
                                 Sciences

ACT_REF     15.65    15.84       16.60
            (2.10)   (2.47)      (2.19)

SNS_INT     15.12    15.87       15.47
            (2.57)   (2.43)      (2.77)

VIS_VRB     14.45    14.31       14.14
            (2.45)   (2.26)      (2.42)

SEQ_GLO     15.90    15.89       16.14
            (1.63)   (2.06)      (2.41)

Sample      51       111         43
size

Notes: ACT_REF--refers to active vs. reflective, SNS_INT--refers to
sensory vs. intuitive, VIS_VRB - refers to visual vs. verbal,
SEQ_GLO--refers to sequential vs. global. Mgmt refers to the
Management concentration. Sample sizes vary depending on the number
of students who self identified as having that major. The numbers
in parentheses represent the standard deviations.
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Copyright 2011 Gale, Cengage Learning. All rights reserved.