Learning Styles Models and Theory of Motivation

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Table of Contents

Learning Styles
Vroom’s Expectancy Theory
Harvard Referencing
References

Learning Styles

Introduction

Various researchers and pedagogy experts have defined learning styles in various ways depending on the intended use and the context of either the study or the discussion (Cassidy 2004, p. 421). However, there exist apparent commonalities in the understanding of what constitutes learning styles despite the various definitions, which will be outlined to give credence to the primary assumption in this essay. Also, it is crucial to note that learning styles have been used interchangeably with the phrase cognition styles. This paper will endeavor to distinguish the two phrases based on the existing research and study on the same. Of particular interest in the essay is the Honey and Mumford learning style that is the result of the work done by Peter Honey and Alan Mumford. The Honey and Mumford style is a development of Kolb’s style. However, it is more applicable in an organizational or industry management setting and hence its preference in this paper (Honey & Mumford 1986). This derivation from the purely educational or academic application into the management application is one of the distinctions that set apart Kolb’s version from Honey and Mumford’s style. However, due to the brevity of this essay’s content, the researcher will not go into a detailed comparison between Kolb’s and Honey and Mumford’s styles expect to indicate the direct similarities while delineating the causes for criticism of Honey and Mumford’s style, which is a lesser heir to Kolb (1984) strategy.

It is noteworthy that researchers and experts of the learning theory have looked into learning styles for more than four decades now. However, the motivation and content that researchers and experts look into this field have varied over time. Initially, only psychology and pedagogy-oriented experts would look into learning styles. Today, experts from all sorts of fields, including industry and management, are interested in learning styles. Each new researcher has different aims, with their different fields of study naturally indicating that they have different ways of going about their research including their selection of sources. This has ultimately led to the jumbled array of information on learning styles that can be consuming and ambiguous at a superficial level. However, to move past the ambiguities, it behooves the researcher to seek out commonalities across the various available research in the effort of coming up with a working theory.

Definitions

In this spirit of progression, this paper begins by defining primary terminologies.

A learning style is a position taken by the researcher to address a certain issue to a targeted audience. The learning style indicates the manner of featuring individuals’ preferences or inclinations when faced with a learning opportunity. It is widely accepted that this manner has a bearing on the individual’s performance and the success rate as far as the learning objectives are concerned. Felder and Spurling (2005, p. 109) define cognitive style as “an individual’s typical or habitual mode of problem-solving, thinking, perceiving, and remembering.” They go ahead to differentiate it from learning style by claiming that learning styles are “adopted to reflect concerns with the application of cognitive styles in a learning scenario” (Felder and Spurling, 2005, p. 109). This differentiation has the effect of demarcating learning styles into a sub-class of a strategy known as cognition style. However, it is also noteworthy that style and strategy have been demystified in the same manner, with the strategy being the sub-class of style that is defined as the means of bringing about style.

Definition of Honey and Mumford Style

Peter Honey and Alan Mumford came up with four different possibilities in terms of individuals’ learning preferences that closely mirror Kolb’s model. They base the categorization of learners according to their intrinsic preferences or typical reaction to a learning encounter. The categories include activists, reflectors, theorists, and pragmatists. As far as the relationship with Kolb’s model goes, it is safe to indicate that activists refer to Kolb’s active experimentation preference while reflectors match the reflective observation trait. Theorists prefer Kolb’s abstract conceptualization strategy while pragmatists reflect the traits of favoring Kolb’s Concrete Experience.

It is also noteworthy that critics have opined that Honey and Mumford’s model is replete with an internal inconsistency that does not afflict Kolb’s model. The rate of internal consistency in Honey and Mumford’s model who used a sample of 388 undergraduates is 0.52 – 0.73 for the subscales involved. Critics such as Duff and Duffy indicate that the Learning Style Questionnaire (LSQ), which is the determinant of learners’ preference that is adopted by Honey and Mumford, is not a worthy alternative to the Kolb LSI especially as far as its application in higher education is concerned (Honey & Mumford 2000). However, it is for this very reason that the Honey and Mumford model’s success in management setups is unrivaled. The very inconsistencies that render it premature for use in the higher education context make it ideal for management settings.

For measurement, the LSQ provides 80 items on the questionnaire. It is possible to cut down these 80 elements to 40 depending on the learners’ preference. The scoring on the questions leads to the categorization of activists, reflectors, theorists, or pragmatists (Huang & Busby 2007, p. 94). This model is inherently grounded on psychological elements and hence its familiar manner of measurement. It is also of note that nobody is purely an activist or pragmatist but that each individual usually displays bits of each trait as learning preferences. However, some traits are stronger while others are weaker, and hence the reason behind the scoring questionnaire. Activists are risk-takers in learning. They have an open-minded character about them that makes them ready to embrace change. However, they get easily bored with implementation. As a result, they compete for attention. They detest lengthy explanations or long lectures. This situation reveals why they have problems with the following instructions.

Reflectors are cautious learners who prefer grasping the various dimensions of the problem situation before delving into it. As such, their learning would be compromised if they happen to be thrown out without prior briefing on the facts surrounding the problem situation. They enjoy observation exercises and working within established deadlines. Moreover, their learning would be interfered with if they happen to be cast into leadership, limelight roles, or situations for which they have not been previously prepared. Theorists observe and then explain what they observe in complex but logical theories. Such learners have been accused of perfectionism and objectivity rather than subjectivity, which is commonly associated with emotiveness. They are at their optimal learning levels and/or in complex situations that require their skills and knowledge to theorize and seek links between them and superficially unrelated materials. Also, they are at their worst state when thrown into problematic situations that require much emotion than analysis. They also find it hard when they are forced to co-learn with others concerning different styles (Keefe 1979, p. 12).

Pragmatists are experimentalists who enjoy practical situations. Consequently, they dislike too much theory and are likely to ignore lessons buried in a theory, which they cannot immediately apply. They prefer problem-solving situations especially when such situations are related to their problems. More so, they enjoy the idea of an enigma that has surpassed similar challenges as the ideal teacher of how to overcome it. For this group of learners, mentoring works effectively as a teaching aid (Yancey et al. 1992, p. 281). They will be at a learning loss if they cannot see the purpose behind the lesson or reward for the task.

Vroom’s Expectancy Theory

It is vital to note that Vroom’s expectancy theory has a psychological underpinning. It is based on the beliefs held by employees, specifically on “valence, instrumentality, and expectancy” (Mastrofski et al. 1994, p. 123).

Victor Vroom did the dissertation for his Ph.D. on a personality topic. This topic gained a lot of attention in the psychological as well as the economic sector, thus culminating in the conversion of the same into a book and the winning of a Ford award. Soon afterward, Vroom decided to expand his study by focusing on the effect of moderating the two variables that formed his primary lenses into human behavior, namely authoritarianism and the need for independence. He assumed that the correct levels of each of them would result in the optimal conditions that are required for performance in the name of motivation. The basis of Vroom’s expectancy theory as indicated above hinges on employees’ beliefs. Valence refers to the height of or significance of workers’ emotional affection to an incentive for their effort (Mento et al., 1992, p. 398). Expectancy refers to the confidence in the employees’ ability to perform a given task or reach a specific objective. This aspect considers the employee’s self-confidence and self-assurance reposed by managers or supervisors. Instrumentality denotes confidence in the promised reward. It is a matter of faith or belief that the employee will be awarded as promised upon the accomplishment of a certain set feat. This strategy has a lot of bearing on motivation. Its measurement is based on past actions by those in authority or issuers of the promise based on how they have reacted when an employee rightly deserves the promise (Van Erde & Thierry 1996, p. 579).

A figurative summary of the model looks as follows:

KEY

“A” represents expectancy while “B” represents instrumentality. First-order outcomes represent those behaviors that are directly proportional to the effort deployed to achieve a certain task (Renko, Kroeck, & Bullough 2011). An example of such an outcome is a novelty. Second-order outcomes represent the respective positive or negative repercussions of the first order outcomes. An example of this variable is the wage increase.

Analysis of the Model

As noted above, this model is personality-oriented. Its success is measured based on its ability to gauge the reactions of employees and employers to engage in decision-making after the moderation of the related variables. The variables that form the bulk of this theory include authoritarianism and the need for independence. Based on Vroom’s theory, the definitions for these elements are provided hereinafter. The focus of Vroom’s research took a different approach since he opted to focus on explaining rather than controlling human behavior, as opposed to most psychological practices of the day. As psychologists have attempted to understand the VIE theory of Victor Vroom, they have come up with different derivations, for instance, the position that “performance leads to contentment.”

The expectancy theory provides insight into how individual differences interact with situational variables. In other words, it explains the reason behind how people reach decisions. For motivation to be achieved, all three aspects of the theory, namely valence, expectancy, and instrumentality (VIE), need to be reported in equal proportions. The valence variable is covered in the second-order output section where it becomes relevant to know exactly how desired the outcomes are by the employees. Outputs are best defined as the resultant variables from the performance of a task. The integration of effort and whatever else may be required such as skills and knowledge is known as input. Consequently, people in authority in organizations strive to sell outcomes so that employees may contribute the desired input as to their desire for the outcomes increases.

Short Report inclusive of the Recommendations

Vroom’s model offers useful insights into how the HR Company can improve staff motivation and performance. It is noteworthy that the theory is open-ended and may be used to improve performance and hence fulfillment or to improve impetus and hence staff members’ performance. The expectancy variable indicates the perception of the staff that there will be noteworthy performance if any effort is applied. As a result, the workers’ input will bear fruit. This variable is the first and thus the first motivational point that managers should focus on by setting SMART goals. SMART is the abbreviation for Specific, Measurable, Attainable, Realistic, and Timely goals for each member of staff. These four aspects are preferably arrived at with the employees’ buy-in from the onset of their jobs. Such goals will notify both the employee and the manager upon the achievement of a goal.

This will prove to the employee that the input being contributed to the organization is worth it because it yields positive outcomes. With the learning styles discussed in section 1, it results in a better understanding of how the employee will react to this information. As the manager needs to customize the motivational model to respective members of staff, it is prudent to identify how each employee integrates and assimilates information as another perk of using Vroom’s expectancy theory, as it provides a variable for the ‘individual explanation’ (Lincoln & Guba 1985). Consequently, the employee sees the effect of putting inputs such as skills or knowledge. With time, he or she learns how to manipulate effort and other inputs to yield maximum outcomes. This means that the next phase involves the management’s acknowledgment of the employees’ efforts by linking outcomes with rewards. This strategy will be the incentive that employees need to optimize production. However, even if the style is specific to the needs of the various individual employees because money may be an incentive to someone, it may not motivate another employee equally.

The manager should go about learning the specific inclinations of each respective employer so that he or she provides for each varied preference that the employees may have for the reward mechanism in creating a model for general motivation based on Vroom’s expectancy theory (Mento et al. 1992, p. 402). Another aspect associated with Vroom’s expectancy theory that makes it ideal for organizational motivation is the concept of high motivation, which requires that each of the three variables (valence, instrumentality, and expectancy) be high for the model to work properly. Employees need to believe that they can achieve the task for performance and motivation to be high. Consequently, it is critical for the manager to ensure a balance of these variables at the top of the scale and not forego any to avoid bringing down the balance, which in turn results in low motivation. It is plausible to assume that the company does not have a structured method of the preferred motivation of its staff and that it goes by the traditional incentives of carrot and stick. This means including promotion for performers and demotion or retrenchment for non-performers. Perhaps the first step that the manager should take is to incorporate the employees’ views on the various measurement criteria for gauging performance.

If the employees participate in the formulation of policies, they own the policy and/or strive to ensure its success, as opposed to instances where such employees are handed policies from above the ranks of management. They are practically forced to adopt the same. Much as such policies may be good, they will never be seen as part of the employees’ initiative. Hence, the optimal results achievable by the implementation of such a policy are compromised. To avoid this scenario, it is prudent to engage employees in coming up with the desired performance measurements. In any event, they are the ones who are providing the inputs for the desired outcomes. Afterward, the rewards criteria should be established by incorporating the employees’ preferred incentives. Vroom’s expectancy theory provides for this variable although the manager reserves the option of looking into the X and Y dimensions of motivational approaches as an alternative source of inspiration into the individual staff’s preferences. However, different employees may have different motivational forces. It would be foolhardy for the manager to assume that the things that stimulate him or her are motivational to all other employees or even that the ones that motivate one or many employees motivate all.

Harvard Referencing

Hyper competition can be seen as a rather controversial strategic management perspective, even though many of its principles have become popular in academic research and practice (McNamara, Vaaler, & Devers 2003). (Since the authors are in brackets, the symbol ‘&’ should be used instead of ‘and’. Also, there should be no comma between the last author’s name and the year). This matter is reflected in mixed empirical support of the hypercompetitive view. Michael (No need to use the first name) Porter (1996) and Makadok (1998) both lack empirical support for the hyper-competition. An article in the Journal of Management in 2002 (Only the author’s name should be cited in the text. Not the journal itself) found no increase of industry dynamics in a study of 88 manufacturing industries. Nevertheless, recent research shows increasing support for temporary occurring hyper-competition (Thomas 1996; McNamara et al. 2003). Other researchers consider hyper-competition to just emerge in idiosyncratic market circumstances (Nault & Vandenbosch 1996) (include page numbers for convenience purposes).

References

Cassidy, S 2004, ‘Learning Styles and Overview of Theories, Models and Measures’, Journal of Educational Psychology, vol. 24 no. 4, pp. 419 -446.

Felder, R & Spurling, J 2005, ‘Applications, Reliability, and Validity of the Index of Learning Styles’, International Journal of Engineering, vol. 21 no. 1, pp. 103 -112.

Honey, P & Mumford, A 2000, The Learning Styles Questionnaire, Maidenhead: Peter Honey Publications.

Honey, P & Mumford, A 1986, Using Your Learning Styles, Maidenhead: Peter Honey Publications.

Huang, R & Busby, G 2007, ‘Activist, Pragmatist, Reflector or Theorist? In Search of Postgraduate Learning Styles in Tourism and Hospitality Education’, Journal of Hospitality, Leisure, Sports and Tourism Education, vol. 6 no. 2, pp. 92 -100.

Keefe, J 1979, Learning Style: an overview. In NASSP, Student Learning Styles: Diagnosing and Prescribing Programs, Reston, VA: : National Association of Secondary School Principals.

Kolb, D 1984, Experiential Learning: Experience as the Source of Learning and Development, Engelwood Cliffs: Prentice-Hall.

Lincoln, S & Guba, E 1985, Naturalistic Inquiry, Beverly Hills: Sage Publications.

Mastrofski, S, Ritti, R & Snipes, J 1994, ‘Expectancy theory and police productivity in DUI enforcement’, Law & Society Review, vol. 28 no. 1, pp. 113–148.

Mento, J, Locke, A & Klein, J 1992, ‘Relationship of goal level to valence and instrumentality’, Journal of Applied Psychology, vol. 77 no. 2, pp. 395–405.

Renko, M, Kroeck, G & Bullough, A 2011, ‘Expectancy Theory and Nascent Entrepreneurship’, Journal of Small Business Economies, vol. 8 no. 7, pp. 1-18.

Van Erde, W & Thierry, H 1996, ‘Vroom’s Expectancy Models and Work-Related Criteria: A Meta-Analysis’, Journal of Applied Psychology, vol. 81 no. 5, pp. 575-586.

Yancey, G, Humphrey, E & Neal, K 1992, ‘How Perceived incentive, task confidence, and arousal influence performance’, Perceptual and Motor Skills, vol. 74 no. 9, pp. 279–285.

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