Do Learning Styles Really Matter?

Do Learning Styles Really Matter?
Jolly Holden, Ed.D. Associate Professor, School of Education American InterContinental

Why Are You Here? Opinion: The concept of learning styles in predicting learning outcomes is probably the most misunderstood and misapplied instructional concept confronting educators and trainers today. Fact: Research has revealed that learning styles have little, if any, effect on learning outcomes. Result: So why is there so much discussion on them and why are they still widely perceived as having an affect?

Goals of This Presentation
Inform--What are learning styles, cognitive styles, and learning modalities? Educate--What does the research indicate? Enlighten—So what? Why so much confusion? What can instructors/trainers/instructional designers do to facilitate the transfer of learning?

Presentation Menu The “So What” The Debate
What are Learning/Cognitive Styles? What are Learning Modalities? What’s the Difference? Review of the Research What Does it All Mean & What Can I Do? Learning /Cognitive Style Resources

State of Confusion: Do You Know Your Learning Style?
Are you a… Converger; diverger; assimilator; accommodator (Kolb’s learning styles inventory) Concrete sequential; abstract random; abstract sequential; concrete random (Gregorc’s learning style topography) Sensory/intuitive; visual/verbal; active/reflective; sequential/global (Felder & Silverman four-dimension model) Activists; reflectors; pragmatists; theorists (Honey and Mumford's learning styles) Messick: Analytic/non-analytic; conceptualizing Convergent/divergent thinking (Guilford’s model of intellect) Field dependent/field independent (Witkin’s cognitive styles) Visual, aural, reading, kinesthetic (Dunn & Dunn VARK learning styles)

Insight [and research] into Learning Styles
A recent study published in the Psychological Science in the Public Interest challenged the prevailing concept of learning styles and their affect on student performance. The investigators (four prominent cognitive psychologists) found “no evidence…for validating the educational applications of learning styles into general educational practice.” To that end, in a 2010 article appearing in the Australian Journal of Educational Research stated “research conducted over the last 40 years has failed to show that individual attributes can be used to guide effective teaching practice”.

So What? The concept of learning/cognitive styles;
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 answer the questions or resolve the issues surrounding learning styles in today’s presentation, but… at its end, you will better understand: The concept of learning/cognitive styles; their variability; and impact [or lack thereof] on learning and instructional design

The Essence of the Debate [and the Disagreement]
Learning styles theorists look at how students learn, not what they learned. By emphasizing the how of instruction, learning styles practitioners lose sight of the what of instruction and tend to “profile” learners based upon perception. Research does not support designing instruction to match learning styles. No current holistic [overall] theory of learning preferences. The point being that what is commonly referred to as learning styles, others have labeled as cognitive styles, learning preferences, learning capabilities, cognitive control, multiple intelligences, etc.

Learning Styles: A Perpetuated Myth?
Over time, learning styles have been perceived to account for the variability in learning, much the same way that Edgar Dale’s Cone of Experience has been erroneously used to predict retention. The commonality is that both have been used to make a prediction not based upon evidence…in essence, instructional malpractice. Dale’s Cone of Experience is essentially a “visual metaphor” depicting types of learning, from the concrete to the abstract. Dale did not intend to place value on one modality over another:“The shape of the cone is not related to retention, but rather to the degree of abstraction.” So it went from this metaphor, to this perceived fact (perpetual myth—next page)

Cone of Learning: Points to Ponder
How do you compare "reading" and "seeing” (don't you have to "see" to "read")? What does "collaboration" mean? If two people talking about the information they were learning, weren't they "hearing" it? What does "doing" mean…how much were they "doing" and were they "doing" it correctly? Do you believe people learn more "hearing" a lecture than "reading" the same material? Do people who "read" have an advantage in being able to pace themselves and revisit material they don't understand?

And Morphed Into This Fact: These percentages have been passed around in our field from reputable person to reputable person, but there is no credible data or research to support them.

The Essence of the Debate: What Do the Experts Say?
Foremost ISD text: The Systematic Design of Instruction (Walter Dick, Lou Carey, & James Carey, 2009) Learning styles are personal “preferences” rather than “psychological traits” and cannot predict “how a student will learn best.” Popular ISD text: Instructional Design (Smith & Ragan, 2005) “View learning styles with extreme caution…not sufficiently prescriptive to aid instructional designers in making design decisions.” Foremost e-Learning text: e-Learning and the Science of Instruction (Ruth Clark & Richard Mayer, 2008) Major criticism is that learning styles “makes unwarranted assumptions about how people learn.”

The Essence of the Debate: What Do the Experts Say?
Leading learning theory text: Psychology of Learning for Instruction (Marcy Driscoll, 2005) Doesn’t even address learning styles Popular learning theory text: Cognitive Psychology and Instruction (Bruning, Shaw, Norby, Ronning, 2004) Des not mention learning styles Leading text on cognitive science: Learning Theories (Dale Schunk, 2004) Differentiates between learning styles and learning modalities, where [VAK] learning styles are essentially “modalities”

The World According to Google: Pervasiveness of Learning Styles
Let’s explore some Google results. First, it is important to distinguish between learning styles and cognitive styles…they are not the same (we’ll discuss the “what” later). “learning styles” “cognitive styles” AND NOT Search terms Results learning styles >14,000,000 “learning styles” 5,050,000 “cognitive styles” 399,000 “learning styles” NOT “cognitive styles” 62,100 “learning styles” NOT “cognitive styles” (.com) 22,200 “learning styles” NOT “cognitive styles” (.org) 10,900 “learning styles” NOT “cognitive styles” (.edu) 3,750 Note: Google can only search the WWW…it cannot search the deep web. The majority of research data is only available on the deep web.

What Google Doesn’t Know and Can’t Find: The Deep Web
Now, let’s see what a comprehensive, university library database reveals when searching the Deep Web. Note: Google currently indexes ~23.5 billion out of the 300+ billion pages out there...less than 8% of all available internet content. The other 92% is located in the deep web. Search terms Results learning styles 5,608 cognitive styles 950 This university library has the capability to search thousands of databases comprising over 18,000 peer reviewed (refereed) journals that encompasses ~1,464,000 annual journal articles in specific disciplines, from The total articles searched exceeds 28,000,000. Click the icon to find out about the Deep Web

What are Learning Styles?
Basically, learning styles refers to the concept that individuals differ in regard as to what specific mode in acquiring information is most effective for them. However, learning style definitions are characterized by considerable conceptual confusion and the lack of any generally accepted definition. Many educational/cognitive psychologists believe learning styles are a myth…that while individual differences in learning exists, they are a result of acquired/innate preferences but do not affect learning anymore than the truck delivering groceries to your local store affects your dietary habits.

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.

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 performs several activities at once when processing information (e.g., tasting and smelling, hearing and seeing), but are processed through different channels in our brain. While the brain processes wholes and part simultaneously, learning engages the whole body. Note: Multi-sensory processing is not the same as multi-tasking (partial tasking) in that the brain is not very good at multi-tasking, per se, attempting to perform multiple tasks simultaneously.

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 retention is generally independent of the modality used to acquire whatever is learned. In fact, retention can be reinforced when learning occurs through a combination of text and images rather than through text alone 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.

What Does the Research Reveal About Learning Styles?
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. Based on several decades of empirical evidence, matching learning activities/ strategies with specific learning styles does not often result in improved learning. Dr. Allan Jeong, Associate Professor, Dept. of Educational Psychology and Learning Systems, Florida State University

Small sample sizes, flawed sampling methodology, and non- experimental research designs casts doubt on the results of VAK learning style research. Low validity and reliability scores of the VAK instruments used to identify specific learning styles raise serious doubts about their psychometric properties. In other words, if the tests used to identify learning styles are not reliable or valid, then any conclusions or results based upon them are suspect. Note: While the most common learning style test is the 16 question VARK questionnaire, it states “no reliability studies have been conducted” and that “the VARK questionnaire is difficult to use with current statistical methods of validation because of its structure”. The results of the VARK questionnaire indicate 2/3 of the respondents have “multimodal” preferences (

These tests are not controlled in their distribution and/or reproduction, or administered under controlled conditions. Scores on the VAK learning style tests vary greatly among same individual. VAK test questions focus on out-of-context preferences which allows for wide range of interpretations. Learning style instruments tend to be self-assessments that rely on students to answer honestly and to have enough self-awareness to answer accurately. Intervening variables confound the results. Research reveals that most learning style instruments have such serious weaknesses (e.g. low reliability & poor validity) it is recommend their use in research and practice should be discontinued. Investigations of the properties of a variety of scales have revealed that even the most widely used are inadequate in this regard. Australian Journal of Education, Vol. 54, No. I, 2010, 5-17

What Does the Research Reveal About Cognitive Styles?
The research pertaining to cognitive styles is quite different than learning styles in that the reliability and the validity of the instruments used to identify them are much more robust. The most researched cognitive style is Herman Witkin’s Field Dependence/Field Independence (more on FD/FI here). The test used to identify Field Dependence (FD) and Field Independence (FI) is the Embedded Figures Test Highly reliable and valid (Cronbach Alpha >80%) However, research on cognitive styles has declined in recent years due to the fuzziness between cognitive styles and abilities, assumption that cognitive styles are innate while abilities are acquired. Click here for a example.

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 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).

So What Does it all Mean? Do learning styles exist…are they a myth? Read the research and decide for yourself. Do learning styles affect performance and/or learning outcomes? Overwhelming body of research does not support this premise. Numerous uncontrolled variables affect performance. Intervening /confounding variables that cannot be identified Attempting to isolate variables requires a robust multivariate experimental design. Content and expected outcomes of learning must decide what strategies should be used to deliver instruction, rather than matching instruction to individual learning styles. Dr. David Merrill, esteemed educational psychologist

Cut to the Chase—What Can I Do?
Cognitive science has revealed learners differ in their abilities with different modalities, but teaching to a learner’s best modality doesn't affect learning outcomes. 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 Integrate cognitive learning strategies into the design of instructional to facilitate transfer of knowledge (click here for more) Review the Cognitive Information Processing model (click here for more).

Avoid cognitive overload in multimedia design . Cognitive Overload Theory focuses on the role of working memory in instructional design. Meaningful learning depends on active cognitive processing in learner’s working memory. If learners encounter too many elements in the presentation of multimedia information (animation, graphics, sound, text), working memory can be overwhelmed Result is excessive cognitive load that impedes learning. Note: Since neuroscience has revealed 90% of what the brain processes is visual information, one’s primary learning modality is visual. However, most learners are multi-modal and multi-sensory and adapt their strategies accordingly.

Integrate Cognitive Flexibility Theory in design of instruction (facilitates the acquisition of knowledge). Accomplished by revisiting the same material, at different times, in rearranged contexts, and from different conceptual perspectives. Employ dual-coding theory: When content is presented through two different channels (visual and auditory),working memory can be increased (click here for more on dual-coding theory). Adds context to the written/spoken word. Retention is improved through words and pictures (visual media) rather than through words alone.

Conclusion Learning styles provide no indication of what the students are capable of, nor are they legitimate excuses for poor academic performance. Assume all students have an intrinsic motivation to learn. Recognize the complexity in learning and that individuals do learn differently. Don’t constrain learning by “profiling” (aka categorizing/ labeling) students based on learning styles.

Conclusion Integrate cognitive and instructional learning strategies into the curriculum/course. Focus on developing learners schemas rather than simply displaying content. “learning styles‘ theory appeals to the underlying culture's model of the person ensures the theory's continued survival, despite the evidence against its utility. Rather than being a harmless fad, learning styles theory perpetuates the very stereotyping and harmful teaching practices it is said to combat.” Australian Journal of Education, Vol. 54, No. I, 2010, 5-17

Final Note The research on how we learn has generally ignored the agility of humans in being able to adapt to different learning environments. The research has grossly understated the internal fortitude of humans to employ multiple learning “preferences” in their endeavor to learn. As educators and trainers, we must never underestimate the ultimate trump card that represents the single most important variability in learning…the will to learn. Research has indicated prior knowledge and intrinsic motivation account for ~70% of the variability in learning.

The End: Questions? “A man only needs two tools in life: WD-40 to make things go, and duct tape to make them stop.” G. M. Weilacher, American humorist “and a hammer to pound things in and a screw driver to pry them out.” my wife Prior Return slide to Menu

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Describing and “Seeing” the Constellation Orion
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. Return to main presentation But…are they really visual learners or did you create the visual image for them by adding context to the description?

Orion Star Chart Return to prior slide

Orion Figure Outlined in a Star Chart
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The Constellation Orion
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Return to main presentation
Example Given the depiction of a power line in the map to the left, identify the power line in the right hand image. Return to main presentation

Example If you cannot find the power line, it may be due to your prior knowledge (schema) of what power lines should look like, such as the ones depicted below. Since there are no other visual cues to add context to your prior “visual images”, and due to lack of past experiences, you may not be able to locate the power line. Return to main presentation

Example So lets add some context (meaning). Don’t look for the actual power line structure…instead look where the power line might be. It’s not a matter of “seeing” the actual power lines or visual acuity…it’s a matter of context. Return to main presentation

Example Still can’t locate it? Here’s another image – look for the path of the power line instead of the actual structures. Result: Given a different context, you identify the power line path not from your prior knowledge but instead based upon an entirely different context. You have now added a new concept to your schema, which could also be applied to similar situations. Return to main presentation Click for final image/click again to turn off

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 Return to main presentation * 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

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) Herman Witkin’s Field Dependent (FD) & Field Independent (FI) Riding’s Cognitive Styles Analysis (CSA) Sternberg’s Thinking Styles Inventory (TSI) Vermunt’s Inventory of Learning Styles (ILS) Return to main presentation * 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

Table 3: Families of Learning/Cognitive Styles*
Learning styles are largely sensory based Betts (1909) Betts Inventory Bartlett (1932) Gordon (1949) Scale of Imagery Control Scheehan (1967) Shortened Betts Inventory Paivio (1971) Individual Difference Questionnaire (IDQ) Marks (1973) Marks Vividness of Visual Imagery Questionnaire Dunn and Dunn (1975, 1979, 1992, 2003) VAK Learning Style Learning Theory Torrance (1990) Style of Learning and Thinking Riding (1991) Cognitive Style Analysis (CSA) Learning styles reflect deep-seated cognitive structure Guilford (1950) Convergent/divergent thinking Prettigrew (1958) Scale of Cognitive Style Gardner et al. (1959) Tolerant/ intolerant Broverman (1960) Kagen (1967) Matching Familiar Figures Test Messick (1976) Analytic / non-analytic conceptualizing Hunt (1978) Paragraph Completion Method Cooper (1997) Learning Styles ID Weinstein, Zimmerman, Palmer (1988) Learning and Study Strategies Inventory Learning styles reflect relatively stable personality type Witkin (1962) Field Dependent (FD/Field Independent (FI); Group Embedded Figure Test (GEFT) Apter (1998) Motivation Style Profile (MSP) Epstein-Meier (1989) Constructive Thinking Inventory (CTI) Miller (1991) Personality typology: cognitive, affective Harrison- Branson (1998) revised Inquiry Mode Questionnaire Jackson (2002) Learning Style Profiles (LSP) Learning styles are flexibly stable learning preferences Kolb (1976, 1985, 1999) Learning Style Inventory (LSI) Schmeck (1977) Inventory of Learning Processes Honey and Mumford (1982) Learning Style Questionnaire (LSQ) Felder and Silverman (1989) Index of Learning Styles (ILS) Kaufmann (1989) The A-E Inventory Allinson and Hayes (1996) Cognitive Style Index (CSI) Herrmann (1995) Brain Dominance Instrument (BDI) Return to main presentation * 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

Resources 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 bbc5ed1053a7.pdf Clemons, Stephanie (2005). Brain-Based Learning: Possible Implications for Online Instruction. International Journal of Instructional Technology and Distance Learning, September 2005, Vol. 2. No. 9. Retrieved from Cognitive/Learning Styles (n.d.). Theory Into Practice, Retrieved from Curry, L. (1990). A critique of research on learning styles. Educational Leadership, 56(2), Retrieved from DeTure, M. (2004). Cognitive Style and Self-Efficacy: Predicting Success in Online Education. The American Journal of Distance Education, 18(1), Retrieved from 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 Return Next to Menu slide

Resources Learning Orientation Research: Individual Differences in Learning (2004). Retrieved from 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 Liu, Y.& Ginther, & Ginther, D. (1999). Cognitive Styles and Distance Education. Online Journal of Distance Learning Administration, Volume II, Number III, Fall Retrieved from Matching Teaching Style to Learning Style May Not Help Student. (Dec 15, 2009). Chronicle of Higher Education. Retrieved from Teaching-Style-to/49497/ Merrill, David M. (2000). Instructional Strategies and Learning Styles: Which takes Precedence? Retrieved from %2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D %2 6rep%3Drep1%26type%3Dpdf&rct=j&q=Instructional%20Strategies%20and%20Learni ng%20Styles%3A%20Which%20takes%20Precedence&ei=czy4TaTaOsmDtgfHnczeBA &usg=AFQjCNFRR9qlyzSSM3L_YzhcksffPlkmGg Prior Return Next slide to Menu slide

Resources Multimodal Learning Through Media:What the Research Says. (2008). Metiri Group-- Commissioned by Cisco. Retrieved from Media.pdf Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning Styles: Concepts and Evidence, Psychological Science in the Public Interest, Retrieved from Reeves, T. (2006), Do Generational Differences Matter in Instructional Design? Retrieved from Scott, Catherine (2010) "The enduring appeal of ‘learning styles’," Australian Journal of Education: Vol. 54: Iss. 1, Article 1. Available at: Sharp, J. G., Byrne, J., & Bowker, R. (2008). The Trouble with VAK. Educational Futures Vol.1(1) August Retrieved from Stahl, Steven A. (1999). Different Strokes for Different Folks: A Critique of Learning Styles. The American Educator, Fall, Retrieved from Prior Return Next slide to Menu slide

Resources Willingham, D. (2005). Do Visual, Auditory, and Kinesthetic Learners Need Visual, Auditory, and Kinesthetic Instruction? American Educator, Summer Retrieved from Willems, Julie. (2011). Using learning styles data to inform e-learning design: A study comparing undergraduates, postgraduates and e-educators. Australasian Journal of Educational Technology, 27(6), Retrieved from Prior Return slide to Menu

What are 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

What are Cognitive Learning Strategies?
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 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 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

Spatial Contiguity Principle

Spatial Contiguity Principle
Blended Learning Model Complexity Instructional Strategies Instructional Objectives Content Rapidity of Change Multimedia (aural/visual) Interactivity Didactic Collaboration (P2P) Asynchronous Dialectic Synchronous Collaborative Tools Synchronicity Asynchronous Instructional Media Synchronous Instructional Media Symmetry Asymmetrical Media Symmetrical Media Distance Learning Traditional Classroom Learning Environment Component Media Component Instructional Component Depicted in this concept map is the blended learning model three main components and subcomponents. The degree of integration of each of the subcomponents is based upon evaluating specific attributes of each component, resulting in the most appropriate blend to ensure attainment of the instructional goal.

Temporal Contiguity Principle

What is the Deep Web? The “Deep Web” is a reservoir of Internet content 1,000 times larger than the surface web, aka World Wide Web. It is sometimes referred to as the “Invisible Web" because database content is "invisible" to search engine spiders, such as Google, Bing, Yahoo, etc. The Deep Web contains billions of high-quality documents in over 350,000 specialty databases hidden from standard search engines! In 2000, the Univ. of California estimated the Deep Web contained 19,000 terabytes of information, compared to 167 terabytes of information for the surface web (1 terabyte = ~7,330,000 documents) The Deep Web contains nearly 140 trillion individual documents compared to12 billion on the surface Web.

Characteristics of Field Dependent and Field Independent Learns
Field dependent learner… Processes information globally Holistic approach to problem solving Views the perceptual field as a whole Socially oriented Uses spectator approach for concept attainment Relies on external cues to guide their behavior Field independent learner… Highly analytical Relies on internal cues (gravity and vestibular) to guide their behavior Breaks the field down into its component parts Not influenced by the existing structure Impersonal orientation Uses hypothesis-testing approach to attain concepts

What Does the Research Reveal About Cognitive Styles?
Results of Field Independent (FI) and Field Dependent (FD) cognitive styles reveal: FI attracted to engineering, hard sciences, mathematics, computer sciences/engineering FI able to extrapolate detailed information from complex figures FI correlated in predicting success in engineering courses FI less influenced by visual effects in media No difference in learning outcomes based on instructional media

Group Embedded Figures Test Example (GEFT)

What is the Cognitive Information Processing Model?
Cognitive Information Processing (CIP) model views learning when information is received from the environment via the senses (modalities), processed and stored into memory, and then output in some form of learned capability. The flow of information is generally conceived to occur in three basic stages: sensory memory, short-term memory, and long-term memory. Sensory Input (seeing, hearing, touching, etc.) Sensory Memory (visual, aural, kinesthetic) Short-term Memory (cognitive learning strategies) Rehearsal Chunking Spatial Long-term Memory attention pattern recognition encoding retrieval Memory Storage context meaning

What is the Cognitive Information Processing Model?
The first stage of information processing, sensory memory, is associated with the senses (seeing, hearing, touching, etc.) where information is stored briefly for processing. Working memory, also referred to as short-term memory, is the stage where further consciousness processing occurs, per se, actively thinking about what has occurred. While working memory holds limited information for a limited amount of time, by employing cognitive learning strategies (rehearsal, chunking, spatial, etc.) the transfer of information from working memory to long term memory can be facilitated.

Dual Encoding Theory Applied to Multimedia Design
Modality Principle – People learn more deeply from multimedia lessons when graphics are explained by audio narration than onscreen text. Spatial Contiguity Principle - People learn better when corresponding words and pictures are presented near rather than far from each other on the page or screen (click here for an example) Temporal Contiguity Principle - People learn better when corresponding words and pictures are presented simultaneously rather than successively (click here for an example)

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