Implications Of Cognitive Learning Styles On Training Design Education Essay

Cognitive Styles are described as individual differences in modes of organizing and processing information in memory. Often, cognitive styles are described as the link between personality and cognition (Sternberg and Grigorenko, 1997) or a missing piece in understanding self (Riding and Rayner, 1998). Over thirty different style labels are classified into two style families, the Wholist-analytic (WA) and the Verbalizer-Imager (VA) dimensions. These dimensions of cognitive styles are fundamental as they develop early in life and are pervasive as they affect social behavior, decision making and learning behavior (Sadler-Smith and Riding, 2000).

The general idea while designing learning materials and trainings is that all individuals learn in a similar manner. Hence learning materials and trainings, while designing, are standardized and fail to accommodate cognitive styles and learning styles in the design process. Moreover, training design methodologies although acknowledge learning styles, but they lack the theoretical and empirical bases to accommodate the important role played by cognitive styles in determining learning performance.

The assumption that all individuals learn in a similar manner ignores individual differences in cognitive styles. Streufert and Nogami (1989), and Hayes and Allinson (1994) suggested that one of the causes for differences in performance of individuals across a variety of organizations is the effect of cognitive style.

Therefore, the research question the paper attempts to answer is:

“Cognitive styles play an important role in determining the learning performance of trainees. Hence designers of trainings and learning materials need to accommodate cognitive style in training design methodologies in order to improve the effectiveness of trainings.”

Research proves that accommodating individual differences in cognitive styles has a beneficial effect on learning performance. The research by Hayes and Allinson (1996) also argues that cognitive style may be an important factor in determining how individuals operate at each stage of the learning cycle.

Literature Review

Conventional training design methodologies fail to acknowledge the important role played by cognitive style in determining learning performance. Hence, it is necessary to consider the relationship between learning performance, learning strategies and cognitive style. It is also necessary to suggest ways in which human resource development practitioners may accommodate individual differences in style such that the effectiveness of training and development interventions may be improved (Riding and Sadler-Smith, 1997).

Kim Buch and Susan Bartley (2002) investigate the relationship between learning style and preference for training delivery mode. The study explores the topic by using the Kolb Learning Style Instrument to measure training delivery mode preference. The results showed a relationship between the two variables depicting that convergers showed a stronger preference for computer-based delivery and assimilators showed a stronger preference for print-based delivery. The results also revealed an overall preference for classroom-based delivery for adults on the study, regardless of their learning styles. The article also discusses the implications of these results for training design and delivery, thereby implicating the importance of learning styles in the design process of trainings.

The type of learning style is not significantly effective on the students’ achievement and learning performance in different learning environments (Yilmaz-Soylu and Akkoyunlu, 2002). The study investigates the effects of learning styles on students’ achievement and learning performance in different learning environments designed according to principles of Generative Theory of Multimedia Learning. The inferences were made by studying a study group in three different learning environments at different times. The research made use of two different learning instruments including a pre-post test experimental method to identify students’ achievement score and Kolb’s Learning Style Inventory to measure students’ learning styles.

The design and application of distance learning is of central concern to many educators. Research has been conducted from a variety of perspectives in this area. The paper by Yuliang Liu and Dean Ginther (1999) explores ways to adapt the design of distance education to students’ cognitive styles. The paper provides an overview of the construct of cognitive styles along with the major dimensions and characteristics of cognitive styles. The researchers also present some applications of cognitive styles to the design of distance education.

The research by Steven John Simon (2000) indicates that trainees whose learning style matches training methodology are more successful in training outcomes, have higher computing satisfaction, and have higher levels of computer use. The study examines the relationship of learning style and training method to computer satisfaction and computer use. The researcher uses structural equation modeling to examine and understand the results of a field experiment to determine the optimum method of training beginner computer users, and to assess the role of learning styles in computing system training. Trainees’ learning style was determined using Kolb’s Learning Styles Inventory.

The study by John Hayes and Christopher W. Allinson (1997) reviews the research on the interaction effect of learning style and the learning style orientation of the learning environment on learning outcomes, and discusses how the findings from educational research can improve training and development practice. The paper attempts to indicate the effect of cognitive learning styles on training and development practice and discusses the need for more research in work settings and the dearth of valid and reliable measures of cognitive learning style. The presence of a valid and reliable measure of cognitive learning style can be easily administered to employees and is considered as a factor which may have inhibited research in this area. Additionally, the advantages and disadvantages of a number of measures that could be used in work settings are also discussed in the paper.

Christopher W. Allinson and Lucinda Willis (2010) examine the range of business learning styles in a population consistency of American and international business students. The research uses the Productivity Environmental Preference Survey to determine learning styles in both working and learning environments. Research findings indicate that learning styles are uniquely related to geographic locations.

Research suggests that individuals differ in the way they process information due to their learner characteristics. It also suggests the presence of 11 dimensions of learner characteristics. Lynna J. Ausburn and Floyd B. Ausburn (1978) use a fresh approach to instructional design and emphasize the importance of cognitive style as a learner characteristic. Noting that cognitive styles are stable, resistant to change by training and bear little relation to general ability, the authors advocate assisting the learner whose information processing pattern is not compatible with the task to be learned by involving explicit alteration of the task requirement with which the learner is having difficulty. Therefore, the study proposes to design the training so as to accommodate learning styles by a three-step instructional design plan with which to move beyond individual instruction to individualized instruction. Such a plan would allow for differences in learners to not result in differences in learning.

In order to optimize individual performance, managers and human resource practitioners have a crucial role to play and a number of human resource interventions are required to facilitate a versatility of style at both the individual and the organizational levels (Sadler-Smith and Beryl Badgera, 1998). The research describes cognitive style as an important determinant of individual behavior and considers it imperative to organizational learning and the innovation process. The researchers argue that it is a fundamental determinant of individual and organizational behavior and manifests itself in individual workplace actions and in organizational systems, processes and routines. The paper presents a number of propositions which raise some implications for research into cognitive styles and its impact upon innovation and organizational learning and training.

The study by Eugene Sadler-Smith (1996) argues that learning style along with learning preferences and cognitive styles may be included under the term personal style. The paper reviews each aspect of the personal style framework and considers its relationship to learning performance at the reaction, learning, behavior and results level. It also describes the instruments which may be used for profiling personal style and suggests that personal style profiling is of value to human resource development practitioners as it may help them identify their own styles, become aware of any bias or imbalance in the training and learning methods which they employ and design and develop learning events which accommodate or acknowledge the personal styles of the learners.

Eugene Sadler-Smith (1996) explores ways in which individual differences between learners regarding their cognitive styles (Riding, 1991) and experiential learning model (Kolb, 1984 and Honey and Mumford, 1986, 1992) may be accommodated while designing self-instructional learning materials. The study provides suggestions to develop balanced instructional materials that acknowledge each stage of the learning cycle and individual differences between learners in terms of verbalizer-imager (VI) and wholist-analytical (WA) dimensions of cognitive style. It also reviews the learning cycle, the associated learning styles (Kolb, 1984; Honey and Mumford, 1986, 1992) and the verbalizer-imager/wholist-analytical model of cognitive style (Riding, 1991) to make suggestions. The research argues that the learning cycle notions suggested by Kolb and Honey and Mumford and the cognitive style model by Riding may provide useful guidelines for accommodating individual differences between learners while designing self-instructional materials which may enable; learning difficulties to be anticipated and addressed, the effectiveness and efficiency of self-instruction to be improved, learners to become aware of the learning process enabling them to be self-reliant and autonomous, and learners and designers to adopt a “whole-brain” approach.

Implications of cognitive style for management practice especially while designing and delivering trainings is studied by John Hayes and Christopher W. Allinson (1994). The paper identifies some important dimensions of cognitive style, addresses semantic issues associated with the nature of cognitive style and examines ways in which styles can be classified.

Research regarding learning styles is emerging from a variety of disciplines and is conducted in domains outside psychology from which many of the central concepts and theories originate. These domains primarily include medical and health care training, management, industry, vocational training and education. Moreover, the applications of these concepts are very broad due to the importance of learning in every field and to every aspect of life. However, the topic has become fragmented and disparate due to the varied aims of the research and the diversity of disciplines and domains in which the research is conducted. Therefore, this has rendered the topic to be complex and difficult to comprehend and assimilate. Hence, it is necessary to present an account of the central themes and issues surrounding learning styles and to consider the instruments available for the measurement of style. The paper by Simon Cassidy (2004) reviews the theories, models and measures related to learning styles. The study attempts to clarify common areas of ambiguity in particular issues surrounding measurement and appropriate instruments. It also aims to bring together necessary components of the area so as to allow for a broader appreciation of learning styles and to inform readers regarding possible tools for measurement of learning styles. The paper anticipates promoting research in the field by making it more accessible to new practitioners and researchers and by developing a greater appreciation for the area across disciplines.

The paper by Samuel Messick (1984) examines characteristic features of cognitive styles and the ways in which learning styles differ from one another. These distinctive characteristics are integrated to form a framework that serves to define cognitive styles in contrast not only to abilities but to other types of stylistic variables. The paper also discusses implications of cognitive styles in terms of improving instructional methods, enriching teacher behavior and conceptions, enhancing student learning and thinking strategies, expanding guidance and vocational decision making, broadening educational goals and outcomes and tuning the stylistic demands of educational environments. The author also addresses the reasons why cognitive styles have educational impact and why such educational benefits are difficult to realize.

The study by Eugene Sadler-Smith (2001) explores the construct validity of learning style as defined in the Learning Styles Inventory (LSI) and its relationship with cognitive styles as measured by using the Cognitive Styles Analysis (CSA) by R. Riding (1994). The study also examines the relationship between styles and learning preferences and suggests that the LSI assesses two dimensions as defined by Kolb (comprehension and transformation) and that the learning style and cognitive styles are independent and the relationship between style and preference is mediated by gender.

Adrian Furnham (1991) reports three studies concerned with personality correlates of learning styles. The Eyesenckian dimensions of Extraversion, Neuroticism, Psychoticism and Lie correlated with three different measures of learning style; the Honey and Mumford (1982) Learning Style Questionnaire (LSQ), the Whetten and Cameron (1984) Cognitive Style Instrument (CSI); and the Kolb Learning Style Inventory (LSI). Personality measures, especially extraversion and psychoticism were strongly correlated with learning/cognitive styles in each case. The study also discusses the implications for assessing learning and cognitive styles in terms of the incremental validity of using learning style instruments.

The effect of text-plus-text versus text-plus-picture computer presentation conditions and the students’ cognitive styles on the learning performance is investigated in the paper by R. Riding and G. Douglas (1993). For the study, fifty nine 15-16 year old students in a secondary school were randomly assigned within sexes to one of the conditions. In the text-plus-text condition, the learning material content described the working of car brake systems while the text-plus-picture condition consisted of text with additional pictorial information. The students were given a post-test overall learning performance along with the Cognitive Styles Analysis (CSA) (Riding, 1991) which measures an individual’s position on two cognitive style dimensions; Verbal-Imagery and Wholist-Analytic. The study concluded that the Verbal-Imagery cognitive style and presentation condition interacted in their effect on overall learning performance. In the text-plus-picture condition, Imagers were superior to Verbalizers, while in the text-plus-text condition the Verbalizers did better than Imagers. The authors also observed that Imagers used more diagrams to illustrate their answers than Verbalizers. The study also discusses the results in terms of their implications for instruction.

Elizabeth R. Peterson, Ian J. Deary and Elizabeth J. Austin (2003) assess and examine the reliability of Riding’s Cognitive Styles Analysis test (CSA) by comparing the performance on the original CSA test and a new parallel version. Both test versions were completed twice by 50 participants, however, the second time the test was completed approximately a week later. The reliability of the test was measured using parallel forms, test-re-test and split half analysis. Correlations of the Verbal-Imagery (VI) and Wholist-analytic (WA) ratios from both test versions were low. However, when the CSA and parallel form data were combined, the split-half analysis of the Wholist-Analytic (WA) style ratio was stable but the Verbal-Imagery (VI) style ratio remained unreliable.

Management education and development practitioners should recognize that individuals’ learning preferences are likely to vary as a result of cognitive style and that this diversity should be acknowledged and accommodated by practitioners through the use of a variety of instructional methods. Researchers also argue that management education and development will benefit from adopting a variety of modes of presentation which will enable individuals to process information in their habitual modes (i.e. visual or verbal) and using instructional devices (overviews, summaries and different types of advance organizers) which compensate for the weaknesses of individuals’ habitual modes of organizing and structuring information in memory. In order to encourage self-awareness and hence facilitate learning and strategy development, management education and development practitioners should use the notion of style and its assessment. Therefore, it is now imperative to fully utilize the notion of style in the education and development of managers in the 21st century. The study by Eugene Sadler-Smith and Richard Riding (2000) aims to consider the implications of the Wholist-Analytic (WA) and Verbalizer-Imager (VI) dimensions of cognitive style for management education and development. The study presents and examines that at a practical level, the style may exert an influence over learning behavior in a number of ways; by interacting with the mode or structure of the presentation of information; by influencing an individual’s propensity to engage in particular types of learning behavior (learning preferences) or through using an awareness of individual’s personal styles as a basis for meta-cognitive awareness (learning strategy development).

The paper by Eugene Sadler-Smith and Peter J. Smith (2004) presents strategies for accommodating individual’s styles and preferences in flexible learning programs. The paper argues that considerable growth and development has taken place in the use of flexible methods of delivery for workplace learning and development. However, while designing programs for flexible learning, the designers often assume that learners exhibit uniformity in their ability to process and organize information (cognitive style), in their tendency towards particular learning formats and media (instructional preferences) and the conscious actions that learners employ to deal with the demands of specific learning situations (learning strategies). Due to such assumptions, the designers of learning materials and trainings may risk ignoring important aspects of individual differences in styles, preferences and strategies. The paper aims to consider some aspects of individual difference that are significant to the delivery of flexible learning in the workplace, identify some of the challenges that may raise for instructional designers and learning facilitators based on differences in styles and preferences between individuals and suggest ways to accommodate and acknowledge individual differences in styles and preferences in the models of flexible learning design and delivery through the use of a range of instructional design, learning and support strategies.

The paper by Pat Burke Guild (2001) examines the effects of diversity, learning styles and culture on the learning performance of learners. The author argues that educators do not believe that all learners learn in the same manner, yet, educators throughout the world continue to treat all learners alike while acknowledging diversity. Educators, today, are aware that students learn in different ways. Theories and extensive research illustrate learning differences among individuals. Learners bring their own individual approach, talents and interests to the learning situation in terms of learning styles, cognitive styles or multiple intelligences. Moreover, individual learners’ culture, family background and socioeconomic level also affect the learning process. Hence, these theories and principles have an important effect on the opportunities for success for every student in schools.

The paper by Teng Pei-Shan, DengchuanCai and Yao-Jen Fan (2009) investigates the relationship between design thinking and design performance in different types of cognition. Designers have the responsibility to understand and care about users’ cognitive habit to distinguish the difference between thinking and performance in different cognitive styles. The study uses the Cognitive Style Index (CSI) and classifies it into two groups; Analysis and Intuition. The research uses experience and questionnaire methods to test two groups with different cognitive styles, to show the difference of design process performance in thinking and sketch ability while executing the same mission. The study uses 134 design major students. The primary results of the study concluded for the design process that; people in intuition group prefer image thinking and those in analysis group prefer word thinking; people in intuition group have better performance than those in an analysis group. Finally, cognitive style can be applied to design education and work such that educators respect the learning modes of different users and utilize proper ways to gain better learning performance.

The paper by James B. Wells, Benjamin H. Layne and Derek Allen (1991) examines the appropriateness and applicability of multimedia instructional strategy in the management development training. The paper also reveals significant differences in the learning styles of supervisors, middle managers and upper managers. It also provides some reasons for the existence of learning style differences and suggests training media and instructional strategies most suited for the dominant learning style of each level of management. The study presents various methodologies and media approaches that can be planned to meet the needs of the training participants.

The paper by John Hayes and Christopher W. Allinson (1998) reviews the implications of cognitive styles on the theory and practice of individual and collective learning in organizations. The study evaluates and asses aspects of two contrasting literatures from adjacent fields of individual and organizational learning. The study focuses on the extent to which the individual level construct of cognitive style can be applied covertly to aid understanding at the organizational as well as at the individual level. The paper identifies nine categories of intervention and also focuses on ways in which consideration of cognitive style can improve the effectiveness of interventions designed to improve individual and organizational performance.

The paper by David Cook (2005) studies the effects of learning and cognitive styles in web-based learning and presents application of cognitive and learning styles in web-based learning. Web-based learning can reach large, heterogeneous audiences and adaptation to cognitive and learning styles increases its effectiveness. The study uses cognitive and learning style constructs to predict relationships between cognitive and learning styles and the web-based learning. The study suggests that teachers and educators develop web-based learning activities that consider assessing and adapting to accommodate learners defined by the Wholist-Analytic (WA) and active reflective constructs.