Learning Styles and Generational Differences: Do They Matter?

Jolly Holden, Ed.D. Philip Westfall, Ph.D. Associate Professor Director, Air Technology Network American InterContinental University Air University

Learning Styles and Learning Styles and Generational Differences: Generational Differences:

Do They Matter?Do They Matter?

Evaluating the Impact and Variability of Learning/Cognitive Styles and Generational Differences

Goals

Inform--What are learning styles, cognitive styles, aptitude treatment interactions, learning modalities, and generational distinctions?

Educate--What does the research indicate?

Enlighten—So what? What can teachers do to facilitate the transfer of learning?

Caution: You are Entering the

“No Spin Zone”

Presentation Menu What are Learning/Cognitive Styles? What are Learning Modalities? What’s the Difference? What are Aptitude Treatment Interactions? Review of the Research Generational Distinctions Bottom Line: How to Improve Performance Appendix—Cognitive Learning Strategies Learning /Cognitive Style Resources

So What…

• A recent article (Dec, 2009) in the Chronicle of Higher Education entitled Matching Teaching Style to Learning Style May Not Help Students, challenged the prevailing concept of learning styles and their affect on student performance.

• The investigators found “no evidence…for validating the educational applications of learning styles into general educational practice.” and concluded “the instructional method that proves most effective for students with one learning style is not the most effective method for students with a different learning style.”

• This is not a new debate but a continuing investigation into the efficacy of learning styles that has spanned 60 years.

• To that end, there is a strong intuitive appeal to the notion there are individual preferences and styles of learning.

• That said, we’re not going to solve the problem today, but… at the end of this presentation, you will better understand:

The concept of learning styles and assess their variability and impact on learning

So What…

What are Learning Styles? Basically, learning styles refers to the concept that

individuals differ in regard to what mode of instruction or study is most effective for them.

Most often learning styles are characterized as multidimensional and usually not “either-or” extremes and categorized by how information is preferentially perceived (sensory or intuitive), organized (inductive or deductive), processed (active or reflective), and modality preference (visual, aural, or kinesthetic). • The most commonly used [and least understood] model of

learning styles are the visual, aural, and kinesthetic (VAK) models

What are Cognitive Styles? Cognitive styles are viewed as a bipolar dimension

representing a person's typical or habitual mode of problem solving, thinking, perceiving and remembering; are considered stable over time, and related to theoretical or academic research.

Cognitive styles primarily focus on cognition and how information is processed in the brain.

So…what’s the difference? A learning style or modality describes how information enters the brain: visually, aurally, or tactically, whereas cognitive style refers to how the information is processed once the information gets to the brain.

What are Learning Modalities?

Learning, or perceptual modalities, are sensory based and refer to the primary way our bodies take in information though our senses: visual (seeing), auditory (hearing), kinesthetic (moving), and tactile (touching).

Humans are multi-sensory in that the brain can perform several activities at once when processing information (e.g., tasting and smelling, hearing and seeing) .

While the brain processes wholes and part simultaneously, learning engages the whole body

What’s the Difference?• Not surprisingly, there is substantial confusion

between learning styles and learning modalities where the terms are often used interchangeably.

• One of the reasons is the complexity of how the human brain functions as it relates to one’s modalities in receiving information (visual, aural, kinesthetic) and how the brain processes that information (cognition).

• Continued research into neuroscience is discovering how the brain processes information acquired through our primary learning modalities: visual, aural, and tactile.

Note: Neuroscience has estimated 85% of the human brain is wired to process visual information, and that 90% of what the brain processes is visual information, so one’s primary learning modality is visual.

What’s the Difference?• An important finding from that research is that memory

is usually stored independent of any modality.

• You typically store memories in terms of meaning—not in terms of whether you saw (visual), heard (aural), or physically (tactile/kinesthetic) interacted with the information.

• To that end, our brain is constantly searching its memory for context based on prior knowledge/experience.• Note: In the absence of visual cues, our brains create

“mental pictures” based upon our schema to add context to what is printed/spoken. Click here for an example.

The so what: retention is improved through words and pictures (visual media) rather than through words alone.

What are Aptitude Treatment Interactions?

• Any discussion concerning individual differences in learning cannot be complete without addressing the research on aptitude treatment interaction (ATI).

• ATI is the concept that some instructional strategies (treatments) are more or less effective for particular individuals depending upon their specific abilities.

• As a theoretical framework, ATI suggests optimal learning results when the instruction is exactly matched to the aptitudes of the learner.

• The goal of ATI research is to predict educational outcomes from combinations of aptitudes and treatments.

Aptitude Treatment Interactions Conclusions

• The lack of attention to the social aspects of learning is a serious deficiency of ATI research.

• Design treatments should not focus on the individual but groups of students with particular aptitude patterns.

• An understanding of cognitive abilities alone would not be sufficient to explain individual differences in learning when incorporating aptitude treatment interactions.

• ATI critics argued that student performance was too dynamic to be supported by the permanence and pervasiveness of primarily cognitive ATI .

Click here for more on ATI

What Does the Research Indicate?• Simply stated, the research has not revealed a

compelling argument as to the impact of learning styles and their effect on predicting learning outcomes

• Postulates learning/cognitive styles have <5% effect on the variability in learning.

• The majority of research does not support a significant statistical relationship between learning/ cognitive styles and learning outcomes.

• Low validity and reliability scores of the instruments used to identify specific learning styles raise serious doubts about their psychometric properties, particularly the VAK learning style tests

Given the Research, Why all the Confusion?

• It’ s not surprising the reference to learning styles is one of the most misunderstood and overused issues confronting educational and training communities.• Part of the reason is the wide disparity in the definition of

learning styles and their relationship to cognitive styles.

• Furthermore, there is continued debate as to whether learning styles even exist, with the only current evidence of their existence being the tests used to identify them.

• Confusion is further exacerbated in that the research has identified over 71 different types of learning styles (Table 1), summarized into the 13 most influential models (Table 2), and families (Table 3)

Chronicle of Higher Education’s The Millennial Muddle, October 2009:

• “The brightest bunch of do-gooders in modern history” or “self-involved knuckleheads”?

• “To accept generational thinking, one must find a way to swallow two large assumptions. That tens of millions of people, born over about 20 years, are fundamentally different from people of other age groups—and that those tens of millions of people are similar to each other in meaningful ways.” (Palmer H Muntz director of admissions Lincoln Christian Univ.)

Generational Distinctions—What are They?

Cooperative Institutional Research Program at UCLA (annual surveys since 1966. American Freshman: Forty Years of Trends) show small, gradual changes; differences are not significant between generations but only over multiple generations.

Some disturbing trends over multiple generations: increasing sense of entitlement, decreasing literacy and general factual knowledge.


Myth: “The Digital Generation takes to e-learning like ducks to water”

Reality: Greatest disappointment of our time: Huge investments

made in technology (beginning with Telecommunications Act of 1996) in public schools with negative results. Leisure-time tech skills don’t translate to educational & training use of technology. Fast scanning doesn’t translate into academic reading. Reading proficiency dropped from 40% to 35% from 1992 to 2005. Intellectual habits such as deep reflection decrease with increase time spent on browsing, blogging, IMing, Twittering, and Facebook

Online Literacy Is a Lesser Kind, Mark Bauerlein, Chronicle of Higher Education, Sep., 2008)


“Not quite …students do want to be connected, but principally to one another; they want to be entertained, principally by games, music, and movies; and they want to present themselves and their work. E-learning at its best is seen as a convenience and at its worst as a distraction.

Thwarted Innovation What Happened to e-learning and Why, Robert Zemsky and William F. Massy, 2004 . The Learning Alliance at the University of Pennsylvania)


Familiarity with, understanding of, and dexterity with technology varies greatly within the 18-23 age group a few with amazing skills, a large number who can’t deal with computers

Playing games doesn’t translate to improving educational outcomes

Generational Myth, report of research on literacy and technology Chronicle of Higher Education, Sept., 2008)


Chronicle of Higher Education’s Generational Myth report of research on literacy and technology, Sept 2008:

• “Today’s young people—including college students—are just more complicated than any analysis of imaginary generations can ever reveal.”

• Must consider vast range of skills, knowledge & experience of many segments of society—avoid focusing more on needs of socially or financially privileged and overestimate the digital skills of young people in general

• Thinking in generations too simplistic—keeps us from examining ethnic, gender, and class distinctions too closely.

Focusing too much on the Digital

Generation

• “Once we assume that all young people love certain forms of interaction and hate others, we forge policies and design systems and devices that match those predispositions. By doing so, we either pander to some marketing cliché or force otherwise diverse group of potential users into a one size-fits-all system that might not meet their needs.”

Focusing too much on the Digital Generation

A comprehensive literature review in 2006 conducted by Professor Thomas Reeves , Univ. of Georgia: Do Generational Differences Matter in Instructional Design?

• Although generational differences are evident in workplace, not salient enough to warrant different instructional designs or learning technologies.

• Research on generational differences suffers from many same weaknesses found in learning styles research—throws grave doubt on validity of using learning styles as basis for accommodating students of any generation.

Focusing too much onthe Digital Generation

• Instead of worrying about whether Boomers, GenXers or Millennials will learn more from direct instruction or virtual reality games, instructional design should begin by identifying needs of learners, design best possible prototype learning environments in situ, then conduct evaluation to optimize solution

Focusing too much onthe Digital Generation

Bottom Line--How to Improve Performance

Cognitive science has revealed learners differ in their abilities with different modalities, but teaching to a learner’s best modality doesn't affect their educational achievement.

What does matter is whether the learner is taught in the content's best modality…people learn more when content drives the choice of modality.

Given a typical heterogeneous class that encompass a wide range of learning/cognitive styles…

what can you do about it?

Improving Performance--Adapting the Learning

Environment• Considerations when adapting learning environments to meet a diverse classroom.

Existing knowledge and skills Motivation Cognitive abilities Cognitive load (working memory capacity) Personality traits Interests Exploratory behavior Impulsivity

Note: Research has indicated prior knowledge and intrinsic motivation account for ~70% of the variability in learning.

Improving Performance--Integrating Cognitive Learning

Strategies Cognitive learning strategies are methods used to help learners link new information to prior knowledge in facilitating the transfer of learning through the systematic design of instruction•Focuses on how the learner processes the knowledge

•Provides a structure for learning when a task cannot be completed through a series of steps (scaffolding)

•Supports the learner as s/he develops internal procedures that enable him/her to perform tasks that are complex, and can increase the efficiency with which the learner approaches a learning task.

•Tailoring instruction for different levels of prior knowledge

Improving Performance—Integrating Visual Components

Since neuroscience has revealed 90% of what the brain processes is visual information, one’s primary learning modality is visual.

Therefore, compliment text-based presentations with visual components/aids.

•This adds context to the written/spoken word

•Provides a structure for learning when a task cannot be completed through a series of steps

Bottom line: Different ways of knowing and understanding demand different ways of learning

and teaching

The End

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Background: Beginning in the early 60’s, Lee Cronbach and Richard Snow searched “fruitlessly for interactions of abilities” by looking for aptitudes (characteristics that affects responses to the treatment) that explained how to instruct students one way and not another, i.e., evidence that showed regression slopes that differed from treatment to treatment. Continuing through the 70’s and mid 80’s, Cronbach and Snow continued their research by advocating a closer scrutiny of cognitive processes by focusing on Aptitude Treatment Interactions (ATIs) (Learning Orientation Research, 2004).

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Findings: Cronbach’s (1975) research emphasized the important relationship between cognitive aptitudes and treatment interactions. However, he was continually thwarted by inconsistent findings coming from roughly similar inquiries. Successive studies employing the same treatment variable found different outcome-on-aptitude slopes. Cronbach concluded the inconsistency came from unidentified interactions and that "an understanding of cognitive abilities considered alone would not be sufficient to explain learning, individual differences in learning, and aptitude treatment interactions (Learning Orientation Research, 2004).

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Findings (con’t): In the early eighties, the cognitive process analysis of aptitudes processes continued with variations focusing on individual differences in learning and cognition (Snow, 1980). Although Cronbach and Snow (1977) were looking for a "whole-person view" of learning, they believed it was primarily the cognitive processes that should be considered in the design and development of adaptive instructional systems. Eventually the new aptitudes evolved into cognitive styles to represent the predominant modes of information processing, although can very within individuals as a function of task and situation variables (Snow, 1989).

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Conclusion: ATI critics argued that student performance was too dynamic to be supported by the permanence and pervasiveness of primarily cognitive ATI and that students, e.g., without learner control, would become system dependent on prescribed solutions. However, based upon Cronbach and Snow’s pioneering research, they concluded that ultimately design treatments should not focus on the individual but groups of students with particular aptitude patterns.

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Describing and “Seeing” the Constellation Orion

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• The constellations are totally imaginary things that have been made up over the past 6,000 years . So how would you describe something imaginary to your students?

• You may begin by describing the three bright stars in a row that form Orion’s belt and the other stars that form his sword.

• But your students have trouble “visualizing” how the stars shape the figure of Orion. To assist them in creating a mental picture, you show them a star chart of Orion to help them “visualize” this imaginary figure.

• But they still can’t quite get it, so to further enhance their mental image, you show them another detailed chart depicting Orion.

• The aha moment…they got it because they now can “see” Orion, so they conclude they must be visual learners.

But…are they really visual learners or did you create the visual image for them by adding context to the description?

Orion Star Chart

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Orion Figure Outlined in a Star

Chart


The Constellation Orion



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Table 1: Types of Learning/Cognitive Styles*

convergers vs. divergers

verbalisers vs. imagers holists vs. serialists deep vs. surface

learning activists vs. reflectors pragmatists vs.

theorists adaptors vs.

innovators assimilators vs.

explorers field dependent vs.

field independent globalists vs. analysts assimilators vs.

accommodators imaginative vs.

analytic learners

intuitionists vs. analysts

extroverts vs. introverts

seeing vs. hearing sensing vs. intuition thinking vs. feeling non-committers vs.

plungers common-sense vs.

dynamic learners concrete vs. abstract

learners random vs.

sequential learners initiators vs.

reasoners judging vs.

perceiving

left brainers vs. right brainers

meaning-directed vs. undirected

theorists vs. humanitarians

activists vs. theorists pragmatists vs.

reflectors organizers vs.

innovators analytics/inductives/

successive processors vs. globals/deductivess/simultaneous processors

executive, hierarchic, conservative vs. legislative, anarchic, liberal

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* Adapted from: Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004). Should we be using learning styles: What research has to say to practice. Learning Skills and Research Centre, London. Retrieved from http://www.ttrb.ac.uk/attachments/c455e462-95c4-4b0d-8308-bbc5ed1053a7.pdf

Table 2: Most Influential Models of Learning/Cognitive

Styles*

Allinson and Hayes’ Cognitive Styles Index (CSI) Apter’s Motivational Style Profile (MSP) Dunn and Dunn model and instruments of learning

styles Entwistle’s Approaches and Study Skills Inventory

for Students (ASSIST) Gregorc’s Mind Styles Model and Style Delineator

(GSD) Herrmann’s Brain Dominance Instrument (HBDI) Honey and Mumford’s Learning Styles Questionnaire

(LSQ) Jackson’s Learning Styles Profiler (LSP) Kolb’s Learning Style Inventory (LSI) Myers-Briggs Type Indicator (MBTI) Riding’s Cognitive Styles Analysis (CSA) Sternberg’s Thinking Styles Inventory (TSI) Vermunt’s Inventory of Learning Styles (ILS)

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* Adapted from: Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004). Should we be using learning styles: What research has to say to practice. Learning Skills and Research Centre, London. Retrieved from http://www.ttrb.ac.uk/attachments/c455e462-95c4-4b0d-8308-bbc5ed1053a7.pdf

Table 3: Families of Learning/Cognitive Styles*

Learning styles are largely sensory based

Betts (1909) Betts InventoryBartlett (1932) Gordon (1949) Scale of Imagery ControlScheehan (1967) Shortened Betts InventoryPaivio (1971) Individual Difference Questionnaire (IDQ)Marks (1973) Marks Vividness of Visual Imagery QuestionnaireDunn and Dunn (1975, 1979, 1992, 2003) VAK Learning Style Theory; Learning Style Inventory(LSI); Building Excellence Survey (BES)Torrance (1990) Style of Learning and ThinkingRiding (1991) Cognitive Style Analysis (CSA)

Learning styles reflect deep-seated cognitive structure

Guilford (1950) Convergent/divergent thinkingPrettigrew (1958) Scale of Cognitive StyleGardner et al. (1959) Tolerant/ intolerantBroverman (1960)Kagen (1967) Matching Familiar Figures TestMessick (1976) Analytic / non-analytic conceptualizingHunt (1978) Paragraph Completion MethodCooper (1997) Learning Styles IDWeinstein, Zimmerman, Palmer (1988) Learning and Study Strategies Inventory

Learning styles reflect relatively stable personality type

Witkin (1962) Group Embedded Figure Test (GEFT)Myers – Briggs (1962) Myers-Briggs Type Indicator (MBTI)Apter (1998) Motivation Style Profile (MSP)Epstein-Meier (1989) Constructive Thinking Inventory (CTI)Miller (1991) Personality typology: cognitive, affective, conativeHarrison- Branson (1998) revised Inquiry Mode QuestionnaireJackson (2002) Learning Style Profiles (LSP)

Learning styles are flexibly stable learning preferences

Kolb (1976, 1985, 1999) Learning Style Inventory (LSI); Revised Learning Style Inventory (R-LSI); LSI Version 3Schmeck (1977) Inventory of Learning ProcessesHoney and Mumford (1982) Learning Style Questionnaire (LSQ)Felder and Silverman (1989) Index of Learning Styles (ILS)Kaufmann (1989) The A-E InventoryAllinson and Hayes (1996) Cognitive Style Index (CSI)Herrmann (1995) Brain Dominance Instrument (BDI)

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* Adapted from: Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004). Should we be using learning styles: What research has to say to practice. Learning Skills and Research Centre, London


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Appendix—Cognitive Learning Strategies

Table of Contents

• What is Schema?

• Types of Cognitive Learning Strategies

•Organizing Strategies

•Spatial Strategies

•Bridging Strategies

Cognitive learning strategies are mental strategies which occur in the minds of people.• Learning these strategies are aided by their

incorporation into instruction.• The utility of cognitive learning strategies can

be employed by faculty to facilitate the activation and retention of prior knowledge by integrating active and exploratory learning techniques into the design process.

What are Cognitive Learning Strategies?

The utility of cognitive learning strategies can be employed by faculty to facilitate the activation and retention of prior knowledge by focusing on knowledge construction.• Knowledge construction is a methodological approach

that assumes knowledge needs to be constructed– Involves the opportunity to critically analyze information,

dialogue with others about its meaning, reflect how the information fits within one’s belief and value systems (schema), and arrive at a meaningful understanding of that information

– In this process, information becomes transformed into knowledge

What are Cognitive Learning Strategies?

What is Schema?

• The contents of long term memory are sophisticated structures that permit us to perceive, think, and solve problems, rather than a group of rote learned facts.

• These structures are known as schemas (a mental framework for understanding and remembering information) and permit us to treat multiple elements as a single element.

• Schemas are the cognitive structures that make up our knowledge base and assist us in knowledge construction.

• Schemas can be “activated” through the use of cognitive learning strategies

What is Schema Activation?

• Schema activation refers to an array of activities designed to activate relevant knowledge in students’ memory prior to encountering new, to be learned information.

• Schema activation is the process of engaging prior knowledge, which is organized in the brain in schemata .

• Schema activation is an important scaffolding tool where learning depends upon the activation of old knowledge to provide an appropriate schema into which new knowledge can be incorporated .

Schema Activation

Prior knowledge: Schema activation engages prior knowledge

New knowledge: Schema activation links prior knowledge to new knowledge

Comprehension: Schema activation creates connections which increase comprehension

Types of Cognitive Learning Strategies

Some cognitive learning strategies can be represented based on the information presented, and are used as tools to construct knowledge in new concepts

Representative models include:

• Organizing

• Spatial

• Bridging

Organizing Strategies

Organizing strategies are not memorable strategies in that they must be supplemented by more powerful strategies, such as framing or concept mapping. However, chunking strategies are good preparation for other strategies.

Chunking

Organization of information into meaningful units Makes it easier to use, store, and recall information Multiple chunks of information can be linked together Helps in overcoming working memory limitations

CREATE

REFLECT & ORGANIZE

RESEARCH

READI need to create a project. What must I do?

Spatial Strategies

Spatial strategies are an array of information organized by location in space and time. They assist in the recall of concrete arrays of information by using visual displays (grids, matrix, framework) of substantial amounts of information, and provides a big picture by which learners can use to assimilate information.

Visual display of substantial amounts of information Framework for representing knowledge Allows text easier to understand Knowledge organized around the representation in

frames• Allows a uniform representation of knowledge • Main ideas are represented as slots of some

concept that describes properties of that concept Matrices or grids allow for organizing large numbers

of facts, concepts or ideas Driven by a general principle or statement Elicits personal knowledge from memory Relationships are recognized and understood by

logical inference

Frames

Improves comprehension Allows for deeper levels of processing Powerful beginning by providing the big picture or spatial learning

strategy Helps students infer and recall prior learning Appropriate combinations include imagery, rehearsal and

mnemonics Does not require as much supplementation as other cognitive

strategies

Frames

Concept Maps

Concept mapping is a way of graphically displaying concepts and relationships between or among concepts

Concept mapping allows a visual aid in which to view thoughts and ideas

Concept mapping can aid a student in tying ideas together or relationships between ideas.• Consists of extracting concepts and their relationships

from text or other content

Uses for Concept Maps

Develop an understanding of a body of knowledge Explore new information and relationships Access prior knowledge Gather new knowledge and information Share knowledge and information generated Design structures or processes such as written

documents, constructions, web sites, web search, multimedia presentations

Problem solve options

Click here for an example

Bridging Strategies

• Helps learners to recall what they know and to transfer knowledge to new topics. It should be brief, abstract, and introduction of the new material and a restatement of prior knowledge.

• Providing learners with a structure of new information and encourage transfer and application.

Advance Organizer

Old Knowledg

e

New Knowledge

A [bridging] strategy for metacognition in that it provides a “bridge” for students to transfer pre-existing knowledge to a new topic

• A brief, abstract prose passage• A bridge, a linking of information with something

already know• An introduction of a new lesson, unit or course• An abstract outline of new information and re-

statement of prior knowledge• A structure for students of the new information• An encouragement for students to transfer or apply

what they know

can be used as…

Advance Organizer

A figure of speech in which an expression is used to refer to something that it does not literally denote in order to suggest a similarity

Types•Comparative: An implicit statement that two apparently

dissimilar objects do have in common features• Interactive: Similarities in the mind of the student between

the vehicle and topic.•Relational: Based on abstract connections of a logical or

natural character•Attribute: Based on physical or perceptual similarities

Metaphor

Involves taking into consideration resemblances between objects, situations or ideas which are similar• Intent is to transfer prior knowledge from a familiar

situation to a new situation, per se, use of a familiar idea or concept to introduce or define a new idea or concept

Analogy

Simile

Simile is a figure of speech in which two unlike things are compared and share one common factor

This form of a cognitive strategy is essential because its ability to influence learning and memory

When using a simile the relationship is expressed using “is like” or “is similar to” or “as”

Use of the simile will allow the learner to… Use imagery as a bridge connecting the concept and

the understanding Display better memory performance Evaluate their learning preference from the different

formats the information is introduced Imagine the concept, store and recall the image, and

relate it to the subject

Human Skin is as flexible as a rubber band

For example, a student will imagine the concept and be able to store and recall the image of a rubber band and relate it to the flexibility and durability of human skin.

Metacognition

Simile

Skin can be bended and stretched like a rubber band

Imagery/memory

Examples of Concept Maps


Complexity

Instructional Strategies

Instructional Objectives

Content

Rapidity of Change

Multimedia (aural/visual)

Interactivity

Didactic Collaboration (P2P)

Asynchronous

Dialectic Collaboration (P2P)

Synchronous

Collaborative Tools

Synchronicity

Asynchronous Instructional

Media

Synchronous Instructional

Media

Symmetry

Asymmetrical Media

Symmetrical Media

Distance Learning

AsynchronousSynchronous

Traditional

Classroom

Learning Environment Component

Media Component

Instructional Component

Examples of Concept Maps


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Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004). Should we be using learning styles: What research has to say to practice. Learning Skills and Research Centre, London. Retrieved from http://www.ttrb.ac.uk/attachments/c455e462-95c4-4b0d-8308-bbc5ed1053a7.pdf

Cognitive/Learning Styles (n.d.). Theory Into Practice, Retrieved from http://tip.psychology.org/styles.html

Cronbach, L. (1975). Beyond the Two Disciplines of Scientific Psychology. "American Psychologist," 116-127.

Cronbach, L. & Snow, R. (1977). Aptitudes and Instructional Methods: A Handbook for Research on Interactions. New York: Irvington Publishers.

Curry, L. (1990). A critique of research on learning styles. Educational Leadership, 56(2), 50-56.

DeTure, M. (2004). Cognitive Style and Self-Efficacy: Predicting Success in Online Education. The American Journal of Distance Education, 18(1), 21-38

Resources

Dumbo, Myron H., & Howard, K. (2007). Advice about the Use of Learning Styles: A Major Myth in Education. Journal of College Reading and Learning, v37 n2 p101-109 Spr 2007. Retrieved from: http://www.eric.ed.gov/ERICWebPortal/search/detailmini.jsp?_nfpb=true&_&ERICExtSearch_SearchValue_0=EJ767768&ERICExtSearch_SearchType_0=no&accno=EJ767768

Howles, S. (n.d.). Learning styles: What the Research Says and How to Apply it to Designing E-Learning. Session TH101, University of Wisconsin-Madison. Retrieved from http://isg.urv.es/library/papers/learning%20styles_overview.pdf

Learning Orientation Research: Individual Differences in Learning (2004). Retrieved from http://www.trainingplace.com/source/research/cronbach.htm

Learning styles and pedagogy in post-16 learning: A systematic and critical review. (2008). Learning and Skills Research Centre, Department for Education and Skills, UK (2004). Retrieved from http://www.hull.ac.uk/php/edskas/learning%20styles.pdf

Resources

Mayer R.E. & Moreno R. (2003) Nine ways to reduce cognitive load in multimedia learning. In Web-Based Learning: What Do We Know? Where Do We Go? (eds R. Bruning, C.A. Horn & L.M. PytlikZillig), pp. 23–44. Information Age Publishing, Greenwich, CT.

Matching Teaching Style to Learning Style May Not Help Student. (Dec 15, 2009). Chronicle of Higher Education. Retrieved from http://chronicle.com/article/Matching-Teaching-Style-to/49497/

Multimodal Learning Through Media:What the Research Says. (2008). Metiri Group--Commissioned by Cisco. Retrieved from http://www.cisco.com/web/strategy/docs/education/Multimodal-Learning-Through-Media.pdf

Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning Styles: Concepts and Evidence, Psychological Science in the Public Interest, Retrieved from http://www.psychologicalscience.org/journals/pspi/PSPI_9_3.pdf

Resources

Sharp, J. G., Byrne, J., & Bowker, R. (2008). The Trouble with VAK. Educational Futures Vol.1(1) August 2008. Retrieved from http://www.educationstudies.org.uk/materials/sharp_et_al_2.pdf

Snow, R. (1980). Aptitude Processes .In R. Snow, P. Frederico, & W.Montague (eds.), Aptitude, Learning and Instruction, Conative and Affective Process Analyses (Vol. 1, pp. 27-60). Hillsdale, NJ: Erlbaum Associates.

Snow, R. (1989). Aptitude-Treatment Interaction as a framework on individual differences in learning. In P. Ackermann, R.J. Sternberg, & R. Glaser (eds.), Learning and Individual Differences. New York: W.H. Freeman.

Stahl, Steven A. (1999). Different Strokes for Different Folks: A Critique of Learning Styles. The American Educator, Fall, 1999.

Willingham, D. (2005). Do Visual, Auditory, and Kinesthetic Learners Need Visual, Auditory, and Kinesthetic Instruction? American Educator, Summer 2005

Resources

Learning Styles and Generational Differences: Do They Matter?

Documents

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