James M. Clark

Dual coding theory and education.

Dual coding theory (DCT) explains human behavior and experience in terms of dynamic associative processes that operate on a rich network of modality-specific verbal and nonverbal (or imagery) representations. We first describe the underlying premises of the theory and then show how the basic DCT mechanisms can be used to model diverse educational phenomena. The research demonstrates that concreteness, imagery, and verbal associative processes play major roles in various educational domains: the representation and comprehension of knowledge, learning and memory of school material, effective instruction, individual differences, achievement motivation and test anxiety, and the learning of motor skills. DCT also has important implications for the science and practice of educational psychology — specifically, for educational research and teacher education. We show not only that DCT provides a unified explanation for diverse topics in education, but also that its mechanistic framework accommodates theories cast in terms of strategies and other high-level psychological processes. Although much additional research needs to be done, the concrete models that DCT offers for the behavior and experience of students, teachers, and educational psychologists further our understanding of educational phenomena and strengthen related pedagogical practices.

COGNITIVE COMPONENTS OF PICTURE NAMING

A substantial research literature documents the effects of diverse item attributes, task conditions, and participant characteristics on the case of picture naming. The authors review what the research has revealed about 3 generally accepted stages of naming a pictured object: object identification, name activation, and response generation. They also show that dual coding theory gives a coherent and plausible account of these findings without positing amodal conceptual representations, and they identify issues and methods that may further advance the understanding of picture naming and related cognitive tasks.

Integrated versus modular theories of number skills and acalculia.

This paper contrasts two views of the cognitive architecture underlying numerical skills and acalculia. According to the abstract-modular theory (e.g., McCloskey, Caramazza, & Basili, 1985), number processing is comprised of independent comprehension, calculation, and production subsystems that communicate via a single type of abstract quantity code. The alternative, specific-integrated theory (e.g., Campbell & Clark, 1988), proposes that visuospatial, verbal, and other modality-specific number codes are associatively connected as an encoding complex and that different facets of number processing generally involve common, rather than independent, processes. The hypothesis of specific number codes is supported by conceptual inadequacies of abstract codes, format-specific phenomena in calculation, the diversity of acalculias and individual differences in number processing, lateralization issues, and the role of format-specific codes in working memory. The integrated, associative view of number processing is supported by the dependence of modular views on abstract codes and other conceptual inadequacies, evidence for integrated associative networks in calculation tasks, acalculia phenomena, shortcomings in modular architectures for number-processing dissociations, close ties between semantic and verbal aspects of numbers, and continuities between number and nonnumber processing. These numerous logical and empirical considerations challenge the abstract-modular theory and support the encoding-complex view that number processing is effected by integrated associative networks of modality-specific number codes.

Extensions of the Paivio, Yuille, and Madigan (1968) norms

The Paivio, Yuille, and Madigan (1968) norms for 925 nouns were extended in two ways. The first extension involved the collecting of a much more extensive and diverse set of properties from original ratings and other sources. Factor analysis of 32 properties identified 9 orthogonal factors and demonstrated both the redundancy among various measures and the tendency for some attributes (e.g., age of acquisition) to load on multiple factors. The second extension collected basic ratings of imagery, familiarity, and a new age of acquisition measure for a larger pool of 2,311 words, including parts of speech other than nouns. The analysis of these ratings and supplementary statistics computed for the words (e.g., number of syllables, Kucera-Francis frequency) demonstrated again the relative independence of various measures and the importance of obtaining diverse properties for such norms. Implications and directions for future research are considered. The full set of new norms may be downloaded fromwww.psychonomic.org/archive/.

Referential processing: Reciprocity and correlates of naming and imaging

To shed light on the referential processes that underlie mental translation between representations of objects and words, we studied the reciprocity and determinants of naming and imaging reaction times CRT). Ninety-six subjects pressed a key when they had covertly named 248 pictures or imaged to their names. Mean naming and imagery RTs for each item were correlated with one another, and with properties of names, images, and their interconnections suggested by prior research and dual coding theory. Imagery RTs correlated .56 (df = 246) with manual naming RTs and .58 with voicekey naming RTs from prior studies. A factor analysis of the RTs and of 31 item characteristics revealed 7 dimensions. Imagery and naming RTs loaded on a common referential factor that included variables related to both directions of processing (e.g., missing names and missing images). Naming RTs also loaded on a nonverbal-to-verbal factor that included such variables as number of different names, whereas imagery RTs loaded on a verbalto-nonverbal factor that included such variables as rated consistency of imagery. The other factors were verbal familiarity, verbal complexity, nonverbal familiarity, and nonverbal complexity. The findings confirm the reciprocity of imaging and naming, and their relation to constructs associated with distinct phases of referential processing.

Chapter 12 Cognitive Number Processing: An Encoding-Complex Perspective

Summary According to the encoding-complex approach (Campbell & Clark, 1988; Clark & Campbell, 1991), numerical skills are based on a variety of modality-specific representations (e.g., visuo-spatial and verbal-auditory codes), and diverse number-processing tasks (e.g., numerical comparisons, calculation, reading numbers, etc.) generally involve common, rather than independent, cognitive mechanisms. In contrast, the abstract-modular theory (e.g., McCloskey, Caramazza, & Basili, 1985) assumes that number processing is comprised of separate comprehension, calculation, and production subsystems that communicate via a single type of abstract quantity code. We review evidence supporting the specific-integrated (encoding-complex) view of number processing over the abstract-modular view, and report new experimental evidence that one aspect of number processing, retrieval of simple multiplication facts, involves non-abstract, format-specific representations and processes. We also consider implications of the encoding-complex hypothesis for the modularity of number skills.

Implicit learning of first-, second-, and third-order transition probabilities.

Most sequence-learning studies have confounded different types of information, making it difficult to know precisely what is learned. Addressing many of the confounds, the current study shows that people can learn 1st-, 2nd-, and 3rd-order transition probabilities. Measures directly assessing awareness of the probabilities show that the knowledge is implicit early in training and becomes explicit with extended training.

Effects of concreteness and semantic relatedness on composite imagery ratings and cued recall

Day and Bellezza (1983) rejected a dual coding imagery explanation for the superior recall of concrete words because unrelated concrete pairs were rated lower in composite imagery but were still remembered better than related abstract pairs. We show that dual coding theory explains their results and our new findings using the same paradigm. In Experiment 1, 120 subjects rated imagery or relatedness for 108 pairs that varied in concreteness, pair relatedness, and associative strength. Incidental cued recall followed. Relatedness and strength affected imagery ratings, as did concreteness, and very low relatedness partly accounted for the low composite imagery ratings for unrelated concrete pairs. Concreteness and relatedness also affected recall, and suporior recall for unrelated concrete pairs occurred consistently under imagery but not under relatedness instructions. In Experiment 2, 40 subjects rated imagery value and recalled 24 pairs. Subsequent questioning indicated that composite images were retrieved better given stimuli from unrelated concrete than from related abstract pairs. These findings and Day and Bellezza’s original results are explained in terms of (1) imaginal and verbal associative processes, which jointly influence composite imagery ratings and recall, and (2) the critical role of stimulus concreteness during image retrieval and recall (i.e., the conceptual peg hypothesis).

Static Versus Dynamic Imagery

The distinction between static and dynamic imagery is familiar to us all at the commonsense level in so far as we are able to imagine not only stationary objects but also action scenes in which objects are in motion or in the process of being rotated or otherwise transformed. This chapter examines the distinction and its implications at several levels. First, we review the general contrast between static and dynamic representations and processes, including imagery. Then we consider individual differences, including sex differences, on that dimension. Finally, we discuss possible mechanisms and causal factors that could explain the phenomena associated with the distinction.

A Dual Coding Perspective on Encoding Processes

Dual coding theory emerged several decades ago when a systematic research program was undertaken to examine the role of imagery in human cognition and, if warranted, to restore imagery to its “rightful place” alongside the language processes that then dominated the interests of cognitive psychologists. Early research efforts at the University of Western Ontario demonstrated the contribution of nonverbal processes to human cognitive behavior, even when that behavior involved language (e.g., Paivio, 1963, 1965, 1966; Paivio & Yarmey, 1965; Paivio & Yuille, 1966). We still find useful this work and that of other early investigators, summarized in Paivio (1971/1979), despite the considerable developments that have occurred in the intervening years as more and more scholars have applied their scientific skills to the study of imagery. Paivio (1986) provides a dual coding perspective on some of this recent work. These earlier sources give a more complete description of dual coding theory, which provides for us a useful organization of many cognitive phenomena.