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Dual-coding theory is a theory of cognition introduced by Allan Paivio from the University of Western Ontario that posits the existence of two functionally independent stores of mental representation (codes).[1][2] One system is specialized for dealing specifically with verbal/linguistic input, while the other processes only nonverbal/visuo-spatial input. Functional independence implies that each system can operate without the other one being active. Despite being independent, the two systems interact through diverse connections. Dual-coding theory has often being confused with simply distinguishing between verbal and visual encoding systems but, rather, the theory distinguishes between the verbal and nonverbal systems, which can include any of the sensorimotor systems.[3] What began as a departure from current theories on cognition, dual-coding theory has contributed much to the field of imagery and how pictures and words are represented in memory.[4] In essence, both the verbal and nonverbal (usual visual) systems are used to represent memory.[5] [6]

Development of Dual-Coding Theory[edit]

Dual-coding theory (DCT) emerged out of research on associative learning and the role that imagery played in recall performance. Popular theories prior to DCT revolved around verbal learing, and so DCT was a departure from the norm. Early research on DCT engendered interest because they were the first thorough analyses on the role of imagery in memory and learning. Imagery was still of interest prior to DCT, but mainly in the form of speculations about its role. Psychology was initially dominated by verbal representations for learning, memory and thought and was often studied using nonsense variables. Dual-coding theory transformed the field by showing the contribution of imagery, or nonverbal representations to memory, learning and thought. To substantiate the claims of DCT, Paivio objectively measured imagery by relating it to performance in memory and other tasks in postexperimental questionnares, which asked participants to state the type of representation that they untilized.[3] He also measured individual differences in imagery abilities, how imagery can be encouraged or interferred, and type of stimuli that naturally evoke imagery. Despite rigorous experimentation, imagery in cognition still undergoes critism. One roadblock to the proliferation of DCT has been proponents of the classic view of internal representations who claim that information is encoded unimodally (E.g., in a single anatomical location) in abstract forms, such as interalized words or phrases. [3]

The Conceptual-peg hypothesis was an important contributor to the development of Paivo's research. This hypothesis refers to a type of rhyming mnemonic technique and implicates the use of two forms of encoding to remember a list of paired words, called associative learning. The conceptual-peg hypothesis discovered that concrete-concrete noun pairings were more easily remembered than abstract-abstract noun pairings because they were thought to evoke images the easiest.[3][7] This phenomenon, referred to as the concreteness effect was studied to verify the processing locus, or more specifically, if imagery could account for the effect. Paivo found evidence for imagery as the mediator in the concreteness effect from utilizing postexperimental questionnares, paired-associates studies, and convergent studies by manipulating learning strategies.

Principles of DCT[edit]

Modality specificity is a concept that refers to the idea that something belongs to a certain group, or more specifically that particular perceptions or inputs are specific to certain anatomical regions in the brain. Modality specificity is an important concept in DCT referring to the two representational systems (verbal and nonverbal) creating representations that correspond to different sensorimotor systems. Environmental stimuli enter cognition first through our sensorimotor systems (visual, olfactory, auditory, haptic & gustatory systems), which then sends inputs to the either, or both of the representational systems.[4] Encodings into the nonverbal system are generally referred to as imagens, while encodings into the verbal system are called logogens. [3] Logogens arise from regions in the brain specific to language, areas for speaking, hearing, writing and feelings (E.g., Braille), whereas imagens are specific to areas that represent emotions, sounds, tasts, smells and vision. [1][8]

Functional independence refers to the capacity of the two systems to operate independently of each other so that one can be active independent of the other's activation. Functional independence also indicates that both systems can be activated together in a parallel process. Processing or encoding the same information in both systems has important benefits such that both systems can have additive effects and enhances recall in attempting to memorize the the information. Different forms of input have variable levels of ability to be stored in both systems. For instance, concrete words have the capacity to be stored more easily in both visual and verbal forms compared to abstract words.[3] The additive effects of the two systems help to explain the concreteness effect.

There are vast connections between elements within each representational systems that allow for the ability to associate similar items. In addition, the verbal and nonverbal representational systems are also share connections. These interunit connections allow for imagens to have names and logogens to evoke images. For instance, hearing the word dog will evoke an image of a particular dog or a prototypical dog in memory, whereas seeing a picture of a dog will elicit a linguistic response such as saying or thinking dog or a particular breed.[3] The connections within each system and across each system leads to three levels of processing upon which imagens and logogens can be activated. The first level is representational processing and is a fairly direct activation of logogens and imagens via linguistic and nonverbal stimuli respectively. Activation across systems such as imagens activating logogens, or visa versa, represents the second level called referential processing. The third level of processing takes place within each representationl system by association to similar items and is called associative processing.[3] All cognitive tasks irrespective of their level of complexity require the use of representational processing because it corresponds to the most fundamental level upon which representations are formed.

A key difference between the two represenational systems is reflected in how they are organized because the verbal and nonverbal systems organize and transform information differently. The verbal system is organized sequentially by words, phrases, or sentences and can only be transformed according to this form (E.g., elements can only be rearranged or substituted). In contrast, the nonverbal system is characterized by synchronous and spatial organization so that transformations can occur in any spatial dimension, such as rotating or flipping images. Synchronous organization is a term similar to parallel processing but adds complexity such that information can be integrated or unitized. Processing of stimuli can occur rapidly through parellel processing, but sometimes successive processing can give more elaborate details. For instance, a visual scene is available in its entirety, but scanning of individual components will enable more elaborate processing. Even successive processing in the nonverbal system is not restricted to sequential processing because it can proceed in any order. Synchronous organization at first glance appears superior to sequential organization, however, the latter form in the verbal system is more efficient for tasks that are amenable to sequential processing.[3]

Evidence[edit]

ERP Studies[edit]

To verify the existence of two forms of representational systems, ERP studies have been conducted that examined the concreteness effects. One study examined the N400 waveform in the context of concrete and abstract word forms to infer the effects upon the verbal and nonverbal representational systems.[9] The N400 waveform seems to be increased more by concrete items than abstract ones.[10] Tasks in one experiment were contrasted by either requiring image generation or word association and it was proposed that concreteness differences would appear later for tasks requiring image generation than word association. Results indicated that using imagery produces different concreteness effects than using word association implying that the verbal and nonverbal systems process information on a different time scale. This also supports the general claim for the existence of two representational systems.[9] Other studies have examined the N400 waveform in relation to differential effects between the verbal and nonverbal system with concrete and abstract words. The different pattern in ERP wave forms that concrete and abstract words elicit supports dual-coding theory. [9][11]

Applications[edit]

Bilingualism[edit]

Dual-coding theory was extended to show how bilinguals can learn and associate words in both languages. Concrete and abstract word pairings have been tested for free recall ability in bilinguals and have discovered that verbal-imagery referential conncetions enable enhanced learning for concrete words. [12] Concreteness is relevant to the development of referential connections because of the links across the two representational systems. Bilinguals have each language represented in two subsets of the verbal representational system and a separate nonverbal system. [12] Seeing or hearing a word and being able to translate it into another languae is due in part to associative connections between the two verbal subset systems. Bilinguals that learn word lists can benefit from associative connections by translating each to-be-remembered word into the other language. This form of memory technique was shown to be even more effective than associating each word with synonyms because there is less uncertainty with between-language connections. [12][13]

Associative Learning and Semantic Memory[edit]

When trying to remember word listings or lists of any sorts, numerous techniques have been suggested that span from rote repetition to chunking into meaningful bits. Dual-coding theory offers another approach that has proven effective, particularly for items that have implicit concreteness. If given a list of words to remember, items that already have a concrete value to it, such as dog, or chair are easily coded into both the verbal and nonverbal systems.[14][15][16] When trying to learn these words, it is beneficial to purposefully imagine each word with its visual counterpart.[17] Abstract items can also taken advantage of both representational systems, but more effort must be taken to encode abstract items into the nonverbal system. Abstract do not carry an easily identifiable image because they are often concepts or constructs such as justice or love.[16] To enable the nonverbal system to encode abstract words, effort has to be taken to create mediators. For instance, given two words such as wind and patriot, effort can be made to visualize the image of a flag because a flag can be representative of both words, since patriots are loyal to a country, and hence a flag, and flags blow in the wind.[7]

Education[edit]

DCT has implications for education in that multipedia presentations have been shown to be an effect medium for learning because they allow for information to be encoded into both the verbal and nonverbal system.[18] In a learning context, separating visual information from auditory information appears to be less effective than if the information is combined and contiguous. This can be explained by dual-coding theory such that combining the two forms of information enables broader referential connections as well as associative connections.[18] People with higher spatial ability might have an added advantage for multimedia learning because they can encode the visual information more effectively into the nonverbal system, whereas people with low spatial ability require more effort to integrate the two forms of information.[18]

Criticisms and Alternative Theories[edit]

Dual-coding theory, while vast in experimental literature, is not accepted by all researchers. Proponents of a theory called the conceptual-propositional hypothesis assert that all knowledge is encode and stored in the form of abstract propositions. These propositions reflect the characteristics of environmental stimuli and associations between them. The theory attempts to account for the concreteness effect by positing that concrete items are more lexically complex and provide a broad set of possible associations for binding together concrete pairs.[19] Proponents of this theory further state that dual-coding theory would have to account for the extensive storing and retrieving capabilities needed to store texture details of entire scenes.

References[edit]

  1. ^ a b Marsh, Elizabeth J.; Multhaup, Kristi S. (1 January 2007). "Dual coding theory: It's not just for cognitive psychologists anymore". PsycCRITIQUES. 52 (31). doi:10.1037/a0008572.{{cite journal}}: CS1 maint: date and year (link)
  2. ^ Lockhart, Robert S. (1 January 1987). "Code duelling". Canadian Journal of Psychology Revue Canadienne de Psychologie. 41 (3): 387–389. doi:10.1037/h0084355.
  3. ^ a b c d e f g h i Paivio, Allan (1 January 1991). "Dual coding theory: Retrospect and current status". Canadian Journal of Psychology/Revue Canadienne de Psychologie. 45 (3): 255–287. doi:10.1037/h0084295.
  4. ^ a b MacLeod, Colin M. (1 January 1984). "Imagery and dual coding theory: The first decade". Canadian Journal of Psychology/Revue Canadienne de Psychologie. 38 (3): 519–522. doi:10.1037/h0080882.
  5. ^ Mio, Robert J. Sternberg ; with contributions of the Investigating Cognitive Psychology boxes by Jeff (2006). Cognitive psychology (4th ed.). Belmont California: Wadsworth. pp. 234–236. ISBN 0534514219.{{cite book}}: CS1 maint: multiple names: authors list (link)
  6. ^ Sternberg, Robert, J (2003). Cognitive theory (3rd ed.). Thomson Wadsworth.{{cite book}}: CS1 maint: multiple names: authors list (link)
  7. ^ a b Paivio, Allan (1971). Imagery and verbal processes. New York: Holt, Rinehart & Winston. ISBN 0-03-085173-4.
  8. ^ Carr, Thomas H. (1 January 1987). "Is Dual Coding Theory Better the Second Time Around?". PsycCRITIQUES. 32 (7): 649–650. doi:10.1037/027324.{{cite journal}}: CS1 maint: date and year (link)
  9. ^ a b c Welcome, Suzanne E.; Paivio, Allan; McRae, Ken; Joanisse, Marc F. (NaN undefined NaN). "An electrophysiological study of task demands on concreteness effects: evidence for dual coding theory". Experimental Brain Research. 212 (3): 347–358. doi:10.1007/s00221-011-2734-8. PMID 21656220. {{cite journal}}: Check date values in: |date= (help)
  10. ^ Nittono, Hiroshi; Suehiro, Maki; Hori, Tadao (2002). "Word imageability and N400 in an incidental memory paradigm". International Journal of Psychophysiology. 44 (3): 219–229. doi:10.1016/S0167-8760(02)00002-8. PMID 12031296.{{cite journal}}: CS1 maint: date and year (link)
  11. ^ Kounios, John; Holcomb, Phillip J. (1 January 1994). "Concreteness effects in semantic processing: ERP evidence supporting dual-coding theory". Journal of Experimental Psychology: Learning, Memory, and Cognition. 20 (4): 804–823. doi:10.1037/0278-7393.20.4.804. PMID 8064248.
  12. ^ a b c Paivio, Allan; Clark, James M.; Lambert, Wallace E. (1 January 1988). "Bilingual dual-coding theory and semantic repetition effects on recall". Journal of Experimental Psychology: Learning, Memory, and Cognition. 14 (1): 163–172. doi:10.1037/0278-7393.14.1.163.{{cite journal}}: CS1 maint: date and year (link)
  13. ^ Arnedt, C. Suzanne; Gentile, J. Ronald (1 January 1986). "A test of dual coding theory for bilingual memory". Canadian Journal of Psychology/Revue Canadienne de Psychologie. 40 (3): 290–299. doi:10.1037/h0080100.
  14. ^ Clark, James M. (1 January 1984). "Concreteness and semantic repetition effects in free recall: Evidence for dual-coding theory". Canadian Journal of Psychology/Revue Canadienne de Psychologie. 38 (4): 591–598. doi:10.1037/h0080869.
  15. ^ Sadoski, Mark; Goetz, Ernest T.; Fritz, Joyce B. (1 January 1993). "Impact of concreteness on comprehensibility, interest, and memory for text: Implications for dual coding theory and text design". Journal of Educational Psychology. 85 (2): 291–304. doi:10.1037/0022-0663.85.2.291.{{cite journal}}: CS1 maint: date and year (link)
  16. ^ a b Paivio, Allan (May 1969). "Mental imagery in associative learning and memory". Psychological Review. 76 (3): 241–263. doi:10.1037/h0027272.{{cite journal}}: CS1 maint: date and year (link)
  17. ^ Reed, S. K. (2010). Cognition: Theories and application (8th ed.). Wadsworth Cengage Learning.
  18. ^ a b c Mayer, Richard E.; Sims, Valerie K. (1 January 1994). "For whom is a picture worth a thousand words? Extensions of a dual-coding theory of multimedia learning". Journal of Educational Psychology. 86 (3): 389–401. doi:10.1037/0022-0663.86.3.389.
  19. ^ Anderson, John R. (1979). Human associative memory (3rd rev. ed.). Hillsdale, N.J.: Lawrence Erlbaum. ISBN 0470028920. {{cite book}}: Unknown parameter |coauthors= ignored (|author= suggested) (help)