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Differences in learning styles: implications for accounting education and practice.

Individuals have different preferences for receiving and processing information. It has been argued that when the learning style of a student and the teaching style of an instructor do not match, the student is likely to have difficulty learning, get discouraged about the course, and perform poorly. These differences in learning style have received increasing attention at all levels of education over the last several years as educators and administrators seek ways to continuously improve the preparedness of their graduates for practice. Learning styles could also have implications in the workforce--for example, when a company offers continuing professional education (CPE).

Given the diverse student body in today's classrooms and the expanded set of learning approaches that have emerged because of online education and new technology, it is particularly important for educators to better understand the learning styles of various student groups. Such information will potentially serve them well in designing courses that challenge students to move beyond their comfort level and achieve higher learning effectiveness. Similarly, in a work environment, in-house educators and supervisors must decide how they will facilitate and support current performance, while also developing employees who are ready for the next level.

This discussion focuses on four primary learning styles and examines whether students taking online and traditional accounting courses have different preferred styles of learning. It also examines whether academic major, gender, or age affect those preferences.

Learning Styles

Experiential learning focuses on learning through experience. David Kolb's model of experiential learning involves a four-stage cycle (Learning Style Inventory, version 3, the Hay Group, 1999). The process starts when a learner encounters a new experience, referred to as a "concrete experience." The next phase, "reflective observation," involves drawing upon past experiences to perceive the new experience from different perspectives. This is followed by "abstract conceptualization," in which a person generates theories and solutions to the new issues encountered. Finally, the development of concepts leads to "active experimentation," where a person tests and applies the theories and solutions previously generated. This cycle can be continuous or repeating as individuals encounter other new experiences.

These dimensions of perceiving and processing information can be linked to four styles of learning: "diverging," "assimilating," "converging," and "accommodating" (shown in Exhibit 1). Individuals can have different styles of learning in different contexts, but most tend to prefer a particular style of learning. Kolb's learning styles form a continuum that learners move through over time, and different types of learners emphasize different stages of the model. This framework has been widely adopted and researched in accounting studies, as well as in other disciplines.

Diverging. Those with this style of learning are best at combining concrete experience and reflective observation, while considering information from many different points of view. A diverger tries to process information through observation and feeling. Consider the example of depreciation of fixed assets in financial accounting. A diverger will work through a problem with varying depreciation methods and useful lives of assets (concrete experience), then will compare the resulting effects on net income of the different depreciation expense amounts (reflective observation). In auditing, divergers might be well suited to the general testing concepts of collecting and evaluating evidence (concrete experience) and drawing conclusions from that evidence (reflection).

Assimilating. People with this style of learning are best at combining reflective observation and abstract conceptualization. To understand a wide range of information, they prefer to put the information into a simple and logical form. An assimilator will prefer to work through an assignment requiring the construction of a model--for example, asking them to design a comprehensive master budget for a hypothetical service or manufacturing company (abstract conceptualization) and come up with relevant financial and operating budgets (reflective observation). An example of this style in auditing might be in developing an expectation for a revenue or expense account in performing substantive analytical procedures, using one or more of several alternative methods.

Converging. People with this learning style combine abstract conceptualization and active experimentation in order to test the theory in practice. They prefer to find practical uses for the concepts taught. Convergers are less people-oriented and more technically oriented (David Kolb, Experiential Learning: Experience as the Source of Learning and Development, Prentice Hall, 1984). They would be drawn to a lecture in the framework of the accounting equation and its relevant components (abstract conceptualization), followed by the preparation of financial statements (active experimentation). For example, convergers might thrive in applying and connecting the financial reporting conceptual framework (abstract conceptualization) to various specific financial reporting topics in courses such as intermediate accounting (active experimentation). In auditing, convergers would be comfortable using the audit risk model and the management assertions audit objectives framework (abstract conceptualization) to develop a plan of specific audit procedures to perform tests of controls and substantive tests (active experimentation).

Accommodating. People with this learning style combine concrete experience and active experimentation, learning through "hands-on" experience. Accommodators are more people-oriented than those with other style preferences and are receptive to new challenges and experiences. Working through profitability and liquidity ratios from class exercises (concrete experience), followed by analyzing a case study and making recommendations based upon these various ratios (active experimentation), is an example of a learning structure that is appealing to accommodators. In an auditing class, accommodators might thrive in relatively active learning activities, such as developing a plan of specific audit procedures (active experimentation) and then simulating actual performance of those procedures (concrete experience). In the context of an auditing practice, accommodators might be comfortable receiving constructive feedback on their work from a supervisor; learning from those interactions; and gradually being assigned more challenging auditing tasks, as a natural progression in building their confidence.

Survey Overview

The authors surveyed a cross-section of 231 students enrolled in 11 sections of undergraduate advanced-level accounting courses at a public university in the Midwest about their preferred approach to learning, using the Kolb learning inventory. These accounting classes consisted of cost accounting, intermediate I financial accounting, intermediate II financial accounting, and auditing. Student age ranged from 18 to 62, with 119 male and 112 female students. Of the total participants, 90 students were enrolled in online classes and 141 students were enrolled in traditional classes. The sample consisted of 148 students age 29 or younger and 82 students age 30 or older (plus one respondent who did not indicate). Of the 231 total students, 179 students were accounting majors; 7 did not specify a major.

Among other variables measured, 12 survey questions aimed at measuring learning preferences. For example, one of the questions began with "When I learn ..." and the answers were "I am open to new experiences," "I look at all sides of issues," "I like to analyze things, break them down into their parts," and "I like to try things out." Another item asked whether students are an observing, active, intuitive, or logical person when learning. Each participant ranked the sentence endings from 1 to 4 ("4" indicating the response that best described the participant and "1" indicating the least descriptive).

Findings on Delivery Method and Age

Some research shows that online courses attract a different demographic from traditional courses. Certainly, convenience plays a large role; however, either due to differences in maturity and experience or out of a greater necessity to self-motivate, it is likely that online students differ from traditional students in other ways. Therefore, this survey looked at whether learning styles might differ between students enrolled under the two different delivery methods. Across groupings (different ages, majors, genders, and delivery type), assimilating was the most common learning preference, followed closely by converging. Diverging was consistently the third most common learning style, and accommodating was the least common.

As shown in Exhibit 2, there was a fairly pronounced tendency for online learners to lean toward a converging style, with a secondary emphasis on assimilating. On the other hand, traditional students appeared to have a somewhat opposite tendency, favoring an assimilating style with a secondary preference for converging. The latter group also leaned somewhat more toward diverging than their online counterparts.

These delivery method and style differences might be at least partially related to age. Exhibit 3 breaks down respondents into two age groups: 29 and younger, or 30 and older. Students age 29 and younger were more inclined to enroll in traditional in-class courses. The distribution between delivery methods is somewhat more even for students 30 and older, although more than one-half were enrolled in online delivery. This is not surprising; if anything, the distribution of "older" students in online delivery is understated, partly because of the arbitrary break at 30, rather than, for example, 35. Because of the convenience of online delivery, many older students often choose this method; otherwise, they might not have been able to take classes.

As further evidence of the relationship between age and learning style, Exhibit 4 breaks down learning styles based on age group. The results are strikingly parallel to the delivery mode results in Exhibit 2. Although the greatest clusters remained in assimilating and converging, the two age groups showed somewhat opposite preferences between the two styles--specifically, the younger group favored the assimilating style by a fairly wide margin, whereas an identical percentage (43.9%) of the older group displayed a preference for converging. The above results are consistent with both online and older students tending toward the converging style, with younger and in-class students tending toward the assimilating style. The relatively greater experience of students 30 and older appears to be associated with different learning style preferences than their younger, traditional classroom counterparts.

Do Major and Gender Matter?

Many consider accounting to be a "hard" major that focuses on quantitative and technical subject matter. Studies have revealed differences in students that choose "hard majors" versus "soft majors" that tend to consist of less quantitative material. In addition, the research literature documents a long-held belief, largely outside the profession, that accounting attracts a certain type of person (e.g., a rules-based, math-focused individual who is somewhat inflexible and socially uncomfortable). Therefore, the authors considered whether learning style preferences of accounting students tended to differ from their nonaccounting counterparts. Exhibit 5 shows a breakdown based upon major. As with the delivery method, the results show the greatest cluster in assimilating and converging. Both groups slightly favored assimilating, with nonaccounting majors leaning toward this style. Nonaccounting majors also showed a somewhat greater preference for accommodating and a somewhat lesser preference for diverging.

The authors further examined the results to see whether males and females differed in their preferences as to how they learn. Using the same general model, Marge Philbin, Elizabeth Meier, Sherri Huffman, and Patricia Boverie found that male students were predominately assimilators, whereas only about one-fifth of females preferred assimilating ("A Survey of Gender and Learning Styles," Sex Roles, vol. 32, no. 7/8, 1995). It thus seems possible that differences could exist in how males and females prefer to process and learn information. Exhibit 6 presents a breakdown by gender. Again, assimilating and converging are the preferred styles. In addition, a relatively higher percentage of males than females leaned toward a diverging style; otherwise, there was no major difference between the two genders. Philbin et al. found a more pronounced difference between males and females in learning style preferences. Perhaps the preferred learning style of females interested in accounting differs from that of other females.

Analysis of Results

According to this survey, online students tend to be convergers who rely on abstract conceptualization and active experimentation to transform experience into knowledge. In contrast, traditional students tend to be assimilators who rely on reflective observation and abstract conceptualization. This result is important, given the prevalence of distance education in today's environment. This difference in learning style between students in different delivery modes is somewhat surprising, because it does not appear that traditional in-class learning environments would preclude opportunities to actively engage in experiential learning. The results suggest potential benefits to recognizing tendencies in order to proactively engage with students and newer employees who favor different styles of learning.

In the education realm, it is important for instructors to consider incorporating instructional activities that help develop students' skills of testing theories to developing solutions; thus, simulation assignments would be beneficial. For example, in a management/cost accounting class, students can work on the development of flexible budgets based upon varying production volume. In addition, common assignments in online courses, such as discussion board participation, might enhance traditional students' use of critical thinking.

This study found that both accounting and nonaccounting majors tended most toward assimilating, but the gap between assimilating and converging was much smaller for accounting majors. The largest group of nonaccounting majors in this study consisted of finance majors; thus, this result provides some evidence that, even within business majors, which emphasize quantitative or technical topics and materials, a difference exists in preferred styles of learning. This result is consistent with convergers being more technically oriented. Opportunities such as auditing or tax internships, however, might lead accounting students closer to being accommodators, because they learn from experiential application and through interacting with professional practitioners.

More generally, teaching and learning strategies that connect and apply broad concepts to specific issues have promise for teaching convergers, who are well represented in online accounting and auditing classes. This is true with respect to learning the conceptual framework in intermediate accounting, for example, and applying it to specific topics covered. Such strategies might also be effective in applying the audit risk model and the assertions/audit objectives framework to specific transaction cycles, such as sales or purchases, whether in class or on the job.

Relatively younger students preferred assimilating styles, whereas older students preferred converging styles. Today's younger students might be more used to--and more comfortable with--a variety of viewpoints. They are arguably better at memorizing and often have relatively less exposure to work situations than do older and online students. Instructors might find that these students have a strong preference for concreteness, with less focus on applying concepts to uncertain situations. On the other hand, relatively older and more experienced online students might find it more meaningful and beneficial to relate conceptual matters to something they have seen in their current job. For instance, a student who also works in a hotel might find it meaningful to think about how many rooms need to be filled to break even on an average night and what costs are relevant to that analysis. Instructors can include interactive and experiential learning tools to help transition students into the different stages of the learning cycle. For example, an exercise that involves asking students to use a classroom response clicker to respond to important conceptual and problem-solving questions would provide opportunities to develop more critical-thinking and problem-solving skills manifested in the converger style of learning.

This study found little gender difference in terms of preferred styles of learning: both groups tended to favor converger and assimilator styles. As education continues to evolve, educators might help students develop the skills necessary to become more balanced learners. Already used by many educators, case studies can develop students' ability to grasp and apply concepts through deep analysis and critical thinking and can result in the creation of solutions and recommendations. In a positive move toward creating a closer link between formal education and practice, some of the large accounting firms provide real-world cases geared toward university classes. In addition, in-class group exercises and instructional materials that require students to go through the aforementioned four cycles can enable them to explore and adopt different styles of learning that are feasible given the task content and context. This will lead to more effective learning.

Practical Implications

The learning process does not stop with formal university education. In an accounting firm, for example, managers must decide upon the appropriate way to train promising individuals for the next level. Managers are well served to understand how individuals learn and are motivated. Identifying employees' different learning style preferences can enable employers to develop more effective professional development programs and more productive employees, partly by encouraging creative thinking and challenging employees to "think outside the box" to avoid becoming stuck in one line of thought. This is true in formal CPE offered by employers or educational organizations and also in smaller-scale on-the-job training and development provided by supervisors and managers to the employees they direct.

This article is not intended to suggest that university, in-house company, or other professional educators should cater to individual preferences, that one learning style is always preferred over others, or that individuals cannot adapt to other styles. Often out of necessity, as individuals mature through experience and realize what is required for success, they develop the ability to adapt to situations that might have previously seemed beyond them. The accounting profession may very well be best served by recruiting individuals who can operate within any of these styles, depending upon what the task at hand requires. Numerous employer surveys call for accounting and finance professionals who possess strong analytical skills and are flexible and adaptable to different situations, suggesting that such individuals might be best equipped to progress further within the organization. As a result, those charged with educating, training, and developing high-performing employees are well served to understand these employees' tendencies.

This study included a large number of male and female students, a wide range of ages, and representation from two different course delivery methods; in this sense, the sample was fairly diverse. At the same time, it included students enrolled in accounting courses at a single university. As with any such survey, it is impossible to be sure about the representativeness of the sample. It is clear, however, that learning styles vary across individuals and that learning can be improved when instructors and managers are aware of these differences. ?

Clement C. Chen, PhD, CPA, is a professor of accounting at the University of Michigan-Flint. Keith T. Jones, PhD, CPA, is a professor of accounting at the University of North Alabama, Florence, Ala. Keith Moreland, PhD, CPA, is a professor of accounting, also at the University of Michigan-Flint.

Delivery Methods and Learning Styles

              Diverging   Assimilating   Converging   Accommodating

Traditional     22.0%        41.1%         28.4%          8.5%
Online          11.1%        32.2%         45.6%          11.1%

Total           17.7%        37.7%         35.1%          9.5%

Age Groupings and Delivery Methods

                 Traditional   Online

29 and younger      69.3%      30.7%
30 and older        46.4%      53.6%

Total               61.2%      38.8%

Age Groupings and Learning Styles

                 Diverging   Assimilating   Converging   Accommodating

29 and younger     17.6%        43.9%         29.7%          8.8%
30 and older       18.3%        26.8%         43.9%          11.0%

Total              17.8%        37.8%         34.8%          9.6%

Learning Styles among Accounting and Nonaccounting Majors

                Diverging   Assimilating   Converging   Accommodating

Nonaccounting     15.5%        40.0%         28.9%          15.6%
Accounting        19.0%        37.4%         35.2%          8.4%

Total             18.3%        37.9%         33.9%          9.8%

Gender and Learning Styles

         Diverging   Assimilating   Converging   Accommodating

Male       21.9%        36.1%         33.6%          8.4%
Female     13.4%        39.3%         36.6%          10.7%

Total      17.7%        37.7%         35.1%          9.5%
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Title Annotation:Responsibilities & Leadership: professional development
Author:Chen, Clement C.; Jones, Keith T.; Moreland, Keith
Publication:The CPA Journal
Geographic Code:1USA
Date:Aug 1, 2014
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