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Technical Report 648

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Verbal Information Processing Paradigms:

A Review of Theory and Methods

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Karen J. Mitchell

Selection and Classification Technical Area

Manpower and Personnel Research Laboratory

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U. S. Army

Research Institute for the Behavioral and Social Sciences

September -!984

Approved for public release; distribution unlimited.

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U. S. ARMY RESEARCH INSTITUTE

FOR THE BEHAVIORAL AND SOCIAL SCIENCES

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Deputy Chief of Staff for Personnel

EDGAR M. JOHNSON

Technical Director

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Commander

Technical review by:

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Report 648

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VERBAL INFORMATION PROCESSING PARADIGMS:

A REVIEW OF THEORY AND METHODS

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Karen J. Mitchell '

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-Information processing^

Cognitive psychologyVerbal processing , ^

20. ABSTRACT fCootCou« an revere* etme) H naceeefy and Identity by block numbet)

"*> The theory and research methods of selected verbal information processing

paradigms are reviewed. Work in factor analytic, information processing,

Chronometrie analysis, componential analysis, and cognitive correlates psychology is discuss2d. The definition and measurement of cognitive processing

operations, stores, and strategies involved in performance on verhaltest

items and test-like tasks is documented. Portions of the reviewed verbal

processing paradigms are synthesized and a general model of text. (Continued)

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ARI Technical Report 648

20. (Continued)

, processing is presented. The model was used as a conceptual framework for

subsequent analyses of the construct and predictive validity of the verbal

subtests of the Armed Services Vocational Aptitude Batteryt (-ASVAB) 8/9/10.

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Technical Report 648

C!

Verbal Information Processing Paradigms:

A Review of Theory and Methods

Karen J. Mitchell

Submitted by

Newell K. Eaton, Chief

Selection and Classification Technical Area

i> Approved as technically adequate

and submitted frr publication by

Joyce L. Shields, Director

Manpower and Personnel

Research Laboratory

P

U.S. ARMY RESEARCH INSTITUTE FOR THE BEHAVIORAL AND SOCIAL SCIENCES

5001 Eisenhower Avenue, Alexandria, Virginia 22333-5600

Office, Deputy Chief of Staff for Personnel

Department of the Army

September 1984

Armv Project Number

2Q162722A791

Manpower, Personnel, and Training

Approved for public «He««; distribution unlimited.

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ARI Research Reports and Technical Reports ore intended for sponsors of

R&D tasks and for ether research and military agencies. Any findings ready

for implementation at the time of publication are presented in the last part

of the Brief. Upon completion of a major phase of the task, formal recommendations for official action normally are conveyed to appropriate military

agencies by briefing or Disposition Form.

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FOREWORD

The Selection and Classification Technical Area of the Array Research Institute for the Behavioral and Social Sciences (ARI) is concerned with developing effective procedures for the selection of applicants into military

service and for the classification of accessions into Army occupational

specialties. The purpose of this research was to develop a model of verbal

information processing for use in subsequent analyses of the construct and

predictive validity of the current Department of Defense military selection

and classification battery, the Armed Services Vocational Aptitude Battery

(ASVA3) 8/9/10.

EDGAR M. JOHNSON

Technical Director
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'•"V '.V. VERBAL INFORMATION PROCESSING PARADIGMS:

A REVIEW OF THEORY AND METHODS

EXECUTIVE SUMMARY

Requirement:

To develop a model of verbal, information processing for use in subsequent analyses of the construct and predictive validity of the Armed Services

Vocational Aptitude Battery (ASVAB) 8/9/10.

Procedure:

The theory and methods of selected verbal information processing paradigms were reviewed. Work in factor f .alytic, information processing,

Chronometrie analyses, componential analyses, and cognitive correlates psychology was discussed.

Findings:

The definition and measurement of cognitive processing operations,

stores, and strategies involved in performance on verbal test items and

test-like tasks were documented. Portions of reviewed verbal processing

paradigms were synthesized and a general model of text processing was

presented.

Utilization of Findings:

The verbal processing model served as a conceptual framework for the

subsequent identification and assessment of cognitive processing contributions to performance on the verbal subtests of ASVAB 8/9/10. These results

were also used in a series of analyses on the predictive validity of assessed

constructs to successful performance in Army jobs.

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VERBAL INFORMATION PROCESSING PARADIGMS:

A REVIEW OF THEORY AND METHODS

CONTENTS

Page

INTRODUCTION 1

THE FACTOR ANALYTIC APPROACH TO THE EXAMINATION OF VERBAL

PERFORMANCE 2

THE RATIONAL ANALYSIS APPROACH TO THE EXAMINATION OF VERBAL

PERFORMANCE 3

THE INFORMATION PROCESSING APPROACH TO THE EXAMINATION OF

VERBAL PERFORMANCE 6

THE COGNITIVE CORRELATES APPROACH TO THE EXAMINATION OF

VERBAL PERFORMANCE 7

THE COMPONENTIAL ANALYSIS APPROACH TO THE EXAMINATION OF

VERBAL PERFORMANCE 10

THE COGNITIVE PROCESS OUTCOME MODELING APPROACH TO THE

EXAMINATION OF VERBAL PERFORMANCE , 11

THE CHRONOMETRIC ANALYSIS APPROACH TO THE EXAMINATION OF

TEST ITEM PERFORMANCE 14

THE KINTSCH & VAN DIJK PROSE PROCESSING APPROACH TO THE

EXAMINATION OF VERBAL PERFORMANCE 16

A MODEL OF VERBAL PERFORMANCE 18

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Figure 1. Model of verbal performance 19

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VERBAL INFORMATION PROCESSING PARADIGMS:

A REVIEW OF THEORY AND METHODS

INTRODUCTION

Recent advances In cognitive psychology have resulted in methods for

identifying the cognitive processing operations, memory stores, and strategies

involved in performance on test items and test-like tasks. The cognitive

processing operations, stores, and strategies that cognitive psychologists

examine represent psychological constructs which may contribute to both item

and subject differences in observed performance.

Current attempts at applying theories of human cognition to analyses of

performance on cognitive tasks range from broad analyses of a number of tasks

to specific and detailed models for performance on a single task type. The

methods for analysis, similarly, range from intuitive analyses of performance

to computer simulation of human protocols and mathematical modeling of

response tiue and response accuracy. Investigations of the algorithms and

heuristics people use in processing information have focused on very simple

cognitive tasks such as, deciding whether or not two visually presented

Letters are the same or different, to complex cognitive activities like

reading text and solving algebra word problems. The ability components

employed by these models, likewise, span a wide range.

Recent attempts at applying theories of human cognition to analyses of

performance differences on test items suggest general dimensions along which

differences are manifested. Investigations of cognitive ability components

relevant to performance on test items and test-like tasks have focused on

verbal and imaginal encoding; retrieval; code access; categorization; executive control; rule induction; inference; semantic, procedural and strategic

knowledge; memory span; spatial visualization; etc. Various test-like tasks

have been examined; these include tasks involving verbal analogy processing

(Sternbarg, 1977a, 1977b, 1980; Gentile et al., 1977: Pellegrino & Glaser,

1979, 1980; Barnes & Whitely, in press; Whitely & Barnes, 1979; Whitely &

Schneider, 1980), geometric analogy processing (Mullholland, Pellegrino, &

Glaser, 1980), syllogistic reasoning and transitive inference (Falmagne, 1975;

Sternberg, 1979, 1980; Sternberg et al., 1980; Sternberg & Weil, 1980),

spatial rotation and visual comparison (Egan, 1979; Cooper, 1980), block

design problems (Royer, 1977), matrix pattern abstraction (Hunt, 1974), and

comprehension of text (Frederiksen, 1978, 1980).

A brief summary of the theory and methods of cognitive processing

paradigms relevant to the analysis of performance on verbal tasks follows.

Processing operations, strategies and structures with a history of empirical

and theoretical support are presented. Relevant measurement methodologies and

analytic techniques are discussed.

—a -
THE FACTOR ANALYTIC APPROACH TO THE EXAMINATION OF VERBAL PERFORMANCE

The structure of cognitive ability as It relates to performance on tests

and test-like tasks has traditionally been examined using factor analytic and

related methodologies. The research pioneers of the factor analytic

movement—Spearman, Thomson, Thurstone—have paved the way for the use of

solid, empirically based analyses in aptitude test construction and validation. Factorial methods have been developed, according to Thurstone (1947, p.

55), for the purpose of "...identifying the principal dimensions or categories

of mentality". Guilford (1967, p. Al) describes the goal of factor analysis

as the identification of "...an underlying latent variable along which

individuals differ".

Factor analytic methods can be employed at the stages of both hypothesis

formulation and hypothesis testing. In the first instance, factor analysis

serves as a useful exploratory technique. It allows analysts to derive a "...

crude first map of a new domain" (Thurstone, 1947, p. 56). Exploratory factor

analytic examinations of items, subtests or intact tests then allow one to

proceed beyond initial staged to more direct forms of psychological experimentation in the laboratory. In the second instance, factor analysis can be

employed as a "... method of comparing, confirming, or refuting alternative

hypotheses initially suggested by nonstatistical arguments or evidence" (Burt,

1970, p. 17).

Factor analysis begins with a matrix of intercorrelations among items,

subtests, or tests and distributes variance within variables and between

factors in such a way that a set of underlying hypothetical performance

constructs are suggested. The output from the factor analysis is a factor

structure or factor pattern matrix of correlation coefficients between each

variable, item or test, and each underlying factor. The factor matrix for a

given factor analysis is typically rotated to some mathematically permissable

coordinate reference system to facilitate interpretation.

The factor analytic definition and measurement of verbal ability is well

documented. Verbal comprehension, defined as "...the ability to understand

the English language," is referenced in at least 125 published studies

(Ekstrom, French & Uarman, 1976, p. 163). Tests of vocabulary, similarities,

opposites, verbal analogies, proverbs, quotations, grammar, spelling, and

paragraph and reading comprehension have loaded highly on the verbal factor in

a number of studies. Verbal factors have been variously titled word

knowledge, word fluency, verbal reasoning, cognition of semantic units, and

cognition of semantic relations or systems. The basic distinctions between

factor types may be summarized as follows: word fluency is typically characterized by tests dealing with single and isolated words; facility with

grapheme or phoneme relations rather than semantic knowledge is tapped. The

word knowledge factor taps semantic knowledge; it seems to reflect experience

with and knowledge of the English language. The verbal reasoning factor may

be seen as reasoning in reading or the ability to see relationships among

ideas, to draw inferences from a paragraph or derive the principal thought or

idea from a passage.

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For the purposes of studying cognitive ability component differences

relevant to performance on standardized tasks, factor analytic methods can

play a promising role In theory-oriented research. Factor analyses of Item or

subtest data can be used to confirm or refute theory-oriented characterizations or processing requirements for items and tests. Alternatively, theoryoriented characterisations of cognitive processing operations, stores, and

strategies underlying test Item performance can be detailed and "...the role

of various processes in a total matrix of cognitive operations," can be

identified (Carroll, 1976, p. 41). An example of the application of factor

analytic methods to the examination of human Information processing is seen in

the work of John Carroll; a description of his work is included below.

THE RATIONAL ANALYSIS APPROACH TO THE EXAMINATION OF VERBAL PERFORMANCE

Using Hunt's Distributive Memory Model (discussed more fully in a later

section), Carroll has attempted a rational and empirical analysis of the

necessary and sufficient cognitive processing operations, stores and

strategies underlying performance on the 74 psychometric tests of the French,

Ekstrom and Price (1973) Kit of Reference Tests for Cognitive Factors.

Research suggests that the French Kit contains good marker tests for 24

different cognitive ability factors.

The memory model employed by Carroll depicts the processing of language

messages in stages. The first stage is a decoding stage, in which arbitrary

physical patterns are recognized as representations of language concepts. The

second stage is an active memory stage, in which the recognized lexical items

are rearranged in memory until they form a coherent linguistic structure. The

third stage is a sentence producing stage, in which the semantic meaning of

the linguistic structure is extracted and incorporated into our knowledge of

the current situation. In the fourth stage, the current situation itself is

analyzed with respect to information held in long term memory, and if appropriate, a response is chosen and emitted. A control or executive system

directs the flow of information in the processing system and has access to the

various levels of memory storage (Hunt, 1971, 1973, 1980).

Carroll has developed a uniform system for classifying the characteristics of the tasks represented by the items of each test in the French Kit. The

classificatory scheme addresses the types of stimuli presented, the kinds of

overt responses that are required to demonstrate performance, the sequencing

of subtasks within the tasks, the cognitive processing operations, stores, and

strategies that Carroll, conceiving himself as a subject, would employ in

performing the test tasks, and the probable ranges of relevant temporal

parameters. The scheme considers the term and contents of memory that would

probably be addressed in storage, search, and retrieval operations.

The cognitive processing operations and strategies outlined by the system

(Carroll, 1976) are processes that are explicitly specified or implied in task

instructions and that are necessary to successful completion of the task.

These operations and strategies are of three types: attentional, memorial,

and executive. The latter two are further subdivided as follows—there are

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three kinds of memorial operations—storing, searching, retrieving. Executive

strategies are exemplif ed by such things as simple judgements of stimulus

attributes such as to reveal identity, similarity, or comparison betwee. two

stimuli; manipulations of memorial contents, such as 'mentally rotating' a

vlsiospatial configuration; and information transformations that produce new

elements from combinations, reductions, etc. of old elements. In all, twenty

different operations and strategies are outlined; they are:

1. Identify, recognize, interpret stimulus

2. Educe identities or similarities between two or more stimuli

3. Retrieve name, description, or instance from memory

4. Store itsm in memory

5. Retrieve associations, or general information, from memory

6. Retrieve or construct hypotheses

7. Examine different portions of memory

8. Perform serial operations with data from memory

9. Record intermediate result

10. Conduct visual inspection of stimulus

11. Reinterpret possible ambiguous item

12. Image, imagine or form abstract representation of stimulus

13. Mentally rotate spatial configuration

14. Comprehend and analyze language stimulus

15. Judge stimulus with respect to a specified characteristic

16. Ignore irrelevant stimuli

17. Use a special mnemonic aid

18. Rehearse associations

19. Develop a special search strategy

20. Chunk or group stimuli or data from memory (Carroll, 1976, p. 39).

Carroll has used his classification scheme as a basis for specifying the

potential sources of individual differences underlying each of the 24 French

Kit cognitive ability factors. He postulates that individual differences

might arise through: (1) differences in the composition and ordering of

processing operations and execution rules Incorporated in the system; (2)

differences in the temporal parameters associated with those execution rules;

(3) differences in the processing capacity of the executive and its associated

memory stores; and (4) differences in the contents of long term or permanent

memory stores.

Carroll has found that nearly all pairs of tests from the same factor

have one or more classification codes In common and that the patterns of the

codes are generally distinct from factor to factor. The cognitive processing

operations, stores, and strategies identified as being characteristic of the

24 factors and the tests that represent them are quite diverse with respect to

type of operation and memory store involved, temporal parameters and other

details. A description of the factors defined by verbal tasks and the

cognitive processing operations, stores, and strategies characterizing these

factors includes:
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1. Factor FW (Word Fluency) Is the facility to produce words that fit one or

more structural, phonetic or orthographic restrictions unrelated to the

meaning of words. The cognitive processing operation involved in word fluency

is a search of a "lexiographemic" portion of long term memory for Instances

fitting the orthographic requirements« Strategies may include the use of an

alphabetic mnemonic to search the memory systematically. French Kit tests

loading on this factor are: (a) Word Endings tests, where the task is to

write as many words as possible ending with certain given letters, (b) Word

Beginnings test, where the task is to write as many words as possible beginning with given certain letters and (c) Word Beginnings and Endings test,

where the task is to write as many words as possible beginning with one given

letter and ending with another.

2. Factor FA (Associational Fluency) is the ability to produce rapidly words

which share a given area of meaning or some other commmon semantic property.

Associational fluency entails a search of a major portion of a long term

lexlcosemantic store, with special attention to semantic or associational

aspects. Strategies may involve searching long term memory for different

meanings of the stimulus word. Tests loading on this factor are: (a)

Controlled Associations tests, where the task is to write as many synonymns as

possible for each of four words, (b) Opposites test, where the subject is

asked to write up to six antonyms for each of four words, and (c) Figures of

Speech, where the subject is asked to provide up to three words or phrases to

complete each of five figures of speech.

3. Factor FE (Fluency of Expression) is the ability to think rapidly of word

groups or phrases. Like associational fluency, expressional fluency Involves

a search of lexiosemantic memory but with special attention to grammatical

features of lexical items and different syntactical patterns of phrases and

sentences. Cognitive processing strategies may involve the use of grammatical

mnenomics such as considering grammatical classification in the search for

words. Tests loading on this factor are: (a) Making Sentences, where the

subject is asked to make sentences of a specified length when the initial

letter of some of the words is provided, (b) Arranging Words, where the

subject is asked to write up to twenty different sentences using the same four

words, and (c) Rewriting, where the subject is asked to rewrite each of three

sentences in two different ways.

A. Factor V (Verbal Comprehension) is the ability to understand English

words. This factor is almost exclusively dependent on the contents of

lexlcosemantic long term memory store, i.e., upon the probability that the

subject can retrieve the correct meaning of a word. Tests loading on this

factor are: (a) Vocabulary I, a four choice synonym test, (b) Vocabulary II,

a five choice synonym test, (c) Extended Range Vocabulary test, a five choice

synonym test having items ranging from very easy to very difficult, (d)

Advanced Vocabulary 1, a five choice synonym test consisting mainly of

difficult items, and (e) Advanced Vocabulary II, a four choice vocabulary test

consisting mainly of difficult items. Carroll states that a more diversified

set of tests of this factor would probably call on other aspects of the

lexiosemantic store, particularly on the grammatical feature portions.
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THE INFORMATION PROCESSING APPROACH TO THE EXAMINATION OF VERBAL PERFORMANCE

Although each of the paradigms discussed here may be thought of as

information processing paradigms, a more general discussion of verbal information processing may be informative. The information processing viewpoint

holds that performance on cognitive tasks may be described by the operation of

Integrated programs for the processing of Information available from sensory

channels and memory stores. The paradigm pos-i that the presentation of

stimuli Initiates a sequence of processing stages. Each stage operates on the

Information available to it. The operations transform the information in some

manner; furthermore, these operations take a measurable amount of time. The

output of each processing stage is in the form of transformed information, end

this new information is the input to the succeeding stage.

The operations, stores, and strategies of the human information processing system are usually described as analogues to computer system structures.

The cognitive ability components are used to formulate information processing

models of tasks. The major concern of information processing research is to

Identify cognitive processing operations, stores, and strategies and to

determine how they operate.

Most general models of the human Information processing system include a

short term sensory storage or buffer component, a memory component consisting

of two or three subsystems distinguished by relative time duration of information storage—short term, intermediate term or working memory and long term

storage; a response selection or generation component; and a central or

executive processor. There is much less unanimity in the literature with

respect to the cognitive processing operations and strategies.

Rose (1980) describes a number of cognitive processing operations which

have a history of empirical and theoretical support. His compendium includes:

1. Encoding, the operation by which information is input into the processing

system, including the initial set of operations that converts the physical

stimulus to a form that is appropriate for the task. Different task demands

may require different levels of analysis of the stimulus. Posner (1969) has

called this dimension "abstraction," the operation by which differnt types of

Information about the stimulus are extracted.

2. Constructing, the operation by which new information structures are

generated from information already in the processing system. This is what

Neisser (1967) and others have called "synthesis."

3. Transforming, the operation by which a given Information structure is

converted into an equivalent structure necessary for task performance. In

contrast to constructing, transformations do not involve any new information

abstraction; rather, this operation requires the application of some stored

rules to the information structures already present.

4. Storing, the operation by which new information is incorporated into

existing information structures while its entire content is retained.

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*. Retrieving, the operation by which previously stored information is made

available to the processing system.

6. Searching, the operation by which an information structure Is examined for

the presence or absence of one or more properties. The information structure

examined may be one already in the processing system or one external to it.

7. Comparing, the operation by which two information structures, either

internal or external to the processing system, are judged to be the same or

different. The structures need not both be physical entitles, for example, a

physical entity may be compared to a stored representation or description in

order to determine identity.

8. Responding, the operation by which the appropriate motor action is

selected and executed.

Newell and Simon (1972) and Simon (1976) have shown that systems of

cognitive ability components can be depicted by computer simulations of

complex problem solving activities, such as the solving of chess or symbolic

logic problems. They have determined the cognitive processing operations,

stores, and strategies necessary for a computer program to extrapolate

sequential material such as number or letter sequences, to translate and solve

algebra word problems, the Tower of Hanoi puzzle, perception in chess, to

understand task instructions, and to spell English words. A running program

serves as a built-in empirical test via computer modeling.

THE COGNITIVE CORRELATES APPROACH TO THE EXAMINATION OF VERBAL PERFORMANCE

What Pellegrlno and Glaser (1979) have referred to as the Cognitive

Correlates approach to individual differences can be traced back to the work

of Hunt, Frost and Lunneborg (1973). This line of research has been continued

by Hunt and his associates throughout the decade (Hunt, 1974; Hunt, Lunneborg

& Lewis, 1975; Hunt & Lansman, 1975; Hunt, 1976, 1978). The basic premise

behind their work is that examinee performance on relatively simple laboratory

tasks can be used to identify cognitive ability components underlying performance on complex cognitive tasks Hunt and his colleagues examine tasks that

are theoretically related to performance on verbal information processing

problems in order to determine how behavior on these tasks is related to

performance on verbal aptitude tests. The goal of this approach is to specify

the cognitive ability components that are differentially related to high and

low levels of verbal competence.

Hunt and tds colleagues posit that there are two types of cognitive

ability components underlying verbal performance. The first set of components

is based on semantic knowledge, on the ability to deal with words and the

concepts they represent. The second set of components is based on strategic

knowledge, on the exercise of information-free, mechanistic operations. These

operations dictate the transformation of both the internal and external

physical representation of a symbol; these strategic knowledge operations do

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not depend on information associated with the symbol. They are the means by

which information structures are transformed into equivalent structures

necessary for task performance« Hunt and his colleagues propose that effectiveness in verbal Information processing depends on the relation of the

stimulus information to the information structures stored in semantic memory,

on the way the information is organized, and on the manipulative efficiency of

the mechanistic processes.

As is typical of most modern theories of cognition, the model employed by

Hunt and his colleagues draws a distinction between two types of memory. The

first is a relatively small active memory and the second is a theoretically

infinite long-term memory. Long term memory may be thought of as a collection

of basic memory units or engrams in conjunction with the associations that

define them. The engrams, collectively, represent the semantic knowledge

information structures and the mechanistic, information-free structures.

Verbal information processing takes place when active memory images, aroused

partly by the recognition of current input and partly by the recognition of

the previous state of active memory, are supplemented by semantic knowledge

information structures and transformed by processes controlled both by sensory

input and by the arousal of strategic knowledge-based structure rules stored

in long-term memory. This model is Hunt's Distributive Memory Model discussed

above.

With this model as a frame of reference, Hunt and his colleagues ask

questions about differences between examinees representing a wide range of

verbal competence. Tests of verbal ability, composites that test knowledge

about syntax, spelling, vocabulary, and the ability to comprehend brief

statements, are administered to subjects and the data are used to identify

ability subgroups. Subgroup performance is then compared on laboratory tasks

which have cognitive ability component characteristics defined by prior

investigations.

Hunt and his colleagues have conducted laboratory experiments to examine

individual cognitive ability component differences in (1) lexical recognition,

arousal speed; (2) speed of information manipulation in short term memory; (3)

storage differences in si ort and intermediate term memory; (4) speed of

information transmission from place to place in the total system; (5) programming which shifts the burden of information processing from one component of

the memory system to another; and (6) attention allocation (Hunt, 1976, 1980).

Hunt and his colleagues have observed indivloual differences in these

processes within the population represented by university students and within

a population of somewhat lower than average ability. These differences appear

to account for a moderate portion of individual variation in verbal competence.

In their examination of the decoding operation, for example, they have

found evidence for a clear association between verbal competence and the

simple act of identifying highly overlearned symbols. Their research in this

area has relied primarily on the letter identification task developed by

Posner and Mitchell (1967). In the Fosner task, two letters are presented

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i^^L.^i.y''\_VA-s''ij'- _*w".\ *.-».i"*->L"* 'S<mf.»: « > *~**j*>'.-.'..• i'..1 . .i., ;_.> _, i,__i . v .;.-._:'>'.' ,". *.",-' *'.'»*\
simultaneously on a visual display screen and the subject's task is to indicate whether the letters are the same or different. Under physical identity (PI) instructions, letter pairs are to be identified as 'same' only if

the letters are exact duplicates of each other, as in the pair (AA). Under

name identity (NI) instruction», letter pairs are to be called 'same' if they

are different visual codes for the same letter, as in the pair (Aa). The

difference between reaction time to classify an item as same under name

identity instructions and the time to classify an Item as same under physical

identity instructions is assumed to reflect the extra processing operations

required to carry the analysis to the same level. Hunt cites moderate

negativ? correlations for the difference measure and verbal aptitude. Low

verbal subjects are seen to have high difference scores and high verbal

subjects are seen to have low difference Indices.

Hunt, Lurmeborg and Lewis (1975) have examined the active memory capacities of high verbal and low verbal college students using a version of the

Brown-Peterson short term memory paradigm. In this procedure the subject is

shown four letters, asked to tepeat a string ox digits presented visually, and

finally to recall the four letters. A positive correlation is observed

between examinee behavior on the task and verbal aptitude test performance.

High verbal students are seen to code items more rapidly than low verbal

students and high verbals have a lower relative error frequency. Hunt and his

colleagues postulate that the observed differences are associated with

language competence. Greater short term memory capacity, they say, may

indicate an increase in the strategies that a high verbal Individual can use

in verbal problem solving.

Hunt (1978) has also examined the relationship between sentence verification reaction time and measures of verbal aptitude. The task, developed by

Clark and Chase, is designed to assess how subjects compare information from

various sources in order to verify sentences. Subjects are presented with a

display containing a sentence and a picture. The subject is asked to determine whether the sentence is an accurate or inaccurate representation of the

picture. The display sentences are of the form:

'Star (plus) is (is not) above (below) plus (star).'

Sentences can be either positively or negatively worded. They can be either

true or false representations of the displays:

+ *

* +

There are four possible sentence combinations: A true affirmative description, a true negative description, a false affirmative description, and a

false negative description. The dependent variable is the latency of the

subject's judgements.

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'-r*v7w-vTv »i 'T^^T'T^v'vwTnTTTi^rrrvTvvrTTTrrpriTiTrT-rrT» "j i "TV 7V";1 w.;11 urj *"

It is hypothesized that subjects will first encode the sentence and

picture, then perform transformations based on the modifiers in the presented

sentences, e.g., transform 'below' to 'not above,' and finally compare the

sentence and picture. The differences in processing time for the four

conditions are assumed to reflect the number of transformations that must be

executed to process the sentence as well as the complexity of the comparison

of the verbal and pictorial representations. Findings are seen to be consistent with this hypothesis. A negative correlation is evidenced for response

latency and verbal competence.

THE COMPONENTIAL ANALYSIS APPROACH TO THE EXAMINATION OF VERBAL PERFORMANCE

Sternberg says that his (1977a, 1977b, 1979) componential theory of

cognitive performance is directed at the analysis of performance differences

in the elementary operations involved in task performance, in the strategies

of task performance into which processes combine, and in the representations

of information upon which the operations and strategies act. A component is

defined as an elementary information process that operates upon internal

representations of objects or symbols (Newell & Simon, 1972). A component may

translate sensory input into a conceptual representation, transform one

conceptual representation into another, or translate a conceptual representation into motor input. Components are classified by level of generality

and function.

Sternberg describes general components, for example, encoding and

response components, as prerequisite to successful performance of all tasks of

a global task *ype, e.g., reasoning tasks. Class componenents, such as

inference, mapping relations, or applying relations, are components common to

a particular class of tasks, for example, inductive reasoning tasks. Specific

components are required for performance of single tasks within a task

universe.

Components perform five different kinds of functions. Metacomponents are

higher-order control processes used for planning how a problem should be

solved, for making decisions regarding alternate courses of action during

problem solving, and for monitoring solution processes. These are analogous

to the executive or control subsystems discussed above. Performance components are processes that are used in the execution of a problem solving

strategy. Acquisition components are processes used in learning new information. Retention components are processes used in retrieving previously stored

knowledge. Transfer components are used in carrying knowledge over from one

task or task context to another.

Componential analysis defines information processing models of performance that specify: (1) the nature and order of component process execution,

and (2) the mode of component execution, that lu, whether components are

executed serially or in parallel, as self terminating or exhaustive processes,

holistically or particularistica'' Cognitive tasks may be decomposed using

the methods of partial tasks, s . «lifting, systematically varied booklets,

and the method of complete tasVt. The method of stem splitting is discussed

for Illustrative purposes.

10

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•, »%' '/"S3 \-'u ' . » f» "g 1? p

'*"'V1"."-' -*' -* — *"j»- .--»;p~<;*—g-—«' ; v.* ',' i

The method of stem splitting Involves items requiring the ssme number and

type of information processing components, but with different numbers of

executions of the various components. The method of stem splitting applied to

a verbal analogy task, for example, might take the following form:

1. red : blood :: white : (a) color

(b) snow

2. red : blood :: (a) white : snow

(b) brown : color

3. red : (a) blood :: white : snow

(b) brick :: brown : color

The first item involves the encoding of five terms—red, blood, white,

color, and snow; the inference of one relation, the color/substance relation;

the mapping of one relation, the color/substance relation onto white and its

alternatives; the application of two relations, the color/substance relation

onto color and snow; and one response, b. The second item requires the

encoding of six terms—red, blood, white, snow, brown, and color; the inference of one relation, again, the color/substance relation; the mapping of

two relations, the color/substance relations onto white and brown; the

application of two relations, the color/substance relations onto whits/snow

and brown/color; and one response, a. The third item requires encoding of

seven terms, inference of two relations, mapping of two relations, application

of two relations, and one response. The primary dependent variable for the

analogy task might be solution latency or response choice. Controls are

introduced for requirement differences in the encoding process. The cognitive

processing contributions of the Inference, mapping, and application of

relation components may then be individually examined. Experimental results

suggest the psychological reality of each of the three components in verbal

analogy processing. Solution latency increases with additional executions of

the various components; response accuracy also decreases for the more complex

items.

Sternberg has examined such task types as linear categorical and

conditional syllogisms, and verbal and schematic-picture analogies. Componential models accounting for as much as 96Z of the variance in solution latency

and response choice data have been constructed.

THE COGNITIVE PROCESS OUTCOME MODELING APPROACH TO THE EXAMINATION OF VERBAL

PERFORMANCE

Also working in the area of componential analysis is Whitely (1980, 1981;

Barnes & Whitely, in press; Whitely & Barnes, 1979; Whitely & Schneider, 1980,

1981) and h«?r colleagues at the University of Kansas. These researchers have

also examined cognitive processing operations, stores, and strategies in terms

of performance on test items and test-like tasks. These researchers charge

11
test developers to begin the test construction process by elaborating theories

of Item tasks. The theories can then be used as item specifications in test

development. Cognitive process outcome models can be used to factor Item and

examinee response variance in accordance with eompoüential theories of task

performance. Multlcomponent latent trait and linear logistic latent models

can be employed to relate cognitive ability component performance to ability

test outcomes.

These latent trait models assume that aptitude test items can be decomposed into subtasks that reflect an exhaustive set of cognitive processing

components. Cognitive ability components are defined by item subtasks and/or

stimulus information measures, that is, by records of the cognitive processing

operations, stores, and strategies purportedly involved In performance on a

test item. The models specify both a mathematical model of Item performance

and a latent trait model for cognitive ability components. The latent trait

models express the probability of success on each subtask as a logistic

function of item difficulty and person ability on the underlying cognitive

ability component. The mathematical model expresses the probability of

success on the total item as the joint probability of passing the subtasks for

each cognitive ability component. Models have been developed to estimate

joint, conditional and marginal maximum likelihoods for the multlcomponent and

linear logistic latent trait models.

The linear logistic latent trait model will be discussed for the purposes

of illustration. This technique models item difficulty from stimulus information. Maximum likelihood estimates of person ability and cognitive ability

component contributions to item difficulty are generated. The linear logistic

latent trait model is similar to the Rasch model in that only item difficulty

is examined; no discrimination or guessing parameters are postulated. The

following equation is the Rasch model for the probability that person J_passes

item i:

exp( t

*

p

<*ii-»""""

u. nl

exp( Sj - o^)

where £ j «the ability level for person j, and

a

l »the difficulty for item i.

The linear logistic latent trait model factors item difficulty Into a subset

of stimulus complexity components according to the following linear model.

12

«kl^-^^wj ...!-i.-JLiL^4 '«1» -,»'i *- A * '" - " 1 "~ ,

-l'- '* -1 ~
I *" ' '-fl'^"-* T«^,- B „,- . g^v^VTrg^t^-^-rv^r^-T-VTl, 1%' t »V \%l^rmTl ^H ^^ 1^

2. °'i "^imV +a

where ^lm "the number of executions of component m that are

involved in solving item j.,

m

»the difficulty of processing component m, and

X "a normalization constant.

The complete linear logistic »odel, then, it given:

3 '(, .1) ' "

P(tlJ-1f

lm"m +'»

Maximum likelihood estimates are computed for the parameters; an estimate

for the difficulty of each cognitive ability component Is obtained along with

standard errors and error correlations. Examinee item and component

likelihoods are computed.

Cognitive process outcome analyses involve: (1) testing alternative

component models of response accuracy, (2) decomposing Item difficulty into

cognitive ability component contributions, and (3) assessing the cognitive

processing operation, store, and strategy person parameters as individual

difference measures. Whitely and her colleagues have examined verbal and

geometric&l analogy tasks.

Performance on verbal analogy and verbal classification test items has

been modeled by Whitely and her collegaues in terms of such cognitive

processing operations as image construction and response evaluation. The

image construction operation involves defining the attributes of the ideal

solution of an item; response evaluation involves selecting the response

alternative that best fulfills a given set of ideal solution attributes.

Image construction is probably best regarded as an inductive reasoning

operation since it involves constructing a general rule from particular

stimuli. Response evaluation, on the other hand, involves deductive

reasoning, since it depends on the evaluation of specifics according to a

general rule.

13
. .„,».- » . r i. * ■■ »\i-*—- , » f »« I ', i

In cognitive process outcome analyses, subjects might be given a verbal

analogy item such as:

STEM tree : sap :: man :

ALTERNATIVES 1. ax«

2. woman

3. maple

4. blood

5. arm

For the image construction subtask the subject Is asked to specify the rule or

set of attributes for the ideal completion of the analogy item. For the

response evaluation subtask, the subject is given an analogy 'image' and asked

to select the response alternative chat best fulfills the image. Verbal

classification subtasks might be constructed in the same way as the analopy

sub tasks for the various cognitive ability components. Whltely's data support

the feasibility of modeling response accuracy on verbal aptitude items from

image construction and response evaluation operations. The inclusion of these

subtasks account for from 70 to 83 percent of the variance in item performance.

THE CHRONOMETRIC ANALYSIS APPROACH TO THE EXAMINATION OF TEST ITEM PERFORMANCE

Frederiksen (1980) and his colleagues have sought to develop a series of

cognitive ability component measures that are representative of the verbal

information processing components involved in reading text. Their measures

are designed :.o assess skills involved in the translation of letter patterns

into sound patterns, in the recognition and encoding of patterns, in the

retrieval of semantic information, and la the formulation of representations

of text. The theoretical model that guides the selection of cognitive ability

component measures for Frederiksen and his colleagues 1« defined by four

levels of verbal information processing: P) visual feature extraction, (2)

perceptual encoding, (3) decoding and (<•) lexical analysis. Visual feature

extraction is the operation by which different type«? of Information about the

stimulus display are extracted. Perceptual encoding ie the operation by which

information is input Into the system, and decoding is the cyeration by which

arbitrary physical patterns are recognized as representations of grapheme and

phoneme concepts .in the lexicon.

In lexical analysis an attempt is made to match letter strings input in

the preceding stages to appropriate semantic referents. For phrase and

sentence units, analysis is also directed at organizing these meaning elements

into coherent text representations. Lexical, semantic, and syntactic

knowledge is called upon in the identification of lexical items and in phrase

and sentential analysis. The lexical analysis process may be either data

driven or hypothesis driven. When lexical analysis is data driven, grapheme

and phoneme data alone drive the analysis process. When lexical analysis is

hypothesis driven, information available from *:he analysis of previous text

14

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: - • 1 •-' ' *-• " *- - » - * '- * - - ' " r ' * *

', If- , V - . < • <• - 1 ■■■'-'-r L i
-rnrBTCggypnfCT^T^jr^r ».' ' 'vi».' %' vI\Tyi\Tt.Ti:'^'^^ ^'i_» u j ^ « t j

supplements the data driven analysis process. Contextual Information is

encoded by the reader and serves to generate hypotheses about subsequent text.

The reader may engage in an Iterative process of discourse representation and

revision.

Frederiksen and his colleagues propose that skilled readers are better

able to execute cognitive processing operations, gain access to and search

memory stores, and define processing strategies at all levels. An advantage

in visual feature extraction, perceptual encoding, decoding and data driven

lexical access is hypothesized for skilled readers. It is hypothesized that

skilled readers are better able to integrate information from perceptual and

contextual sources in generating hypotheses about text and in gaining access

to memory stores.

The Chronometrie analysis approach to the assessment of cognitive

processing operations, stores, and strategies Ik.Ids that the monitoring or

processing time provides an important tool for the measurement of cognitive

cbility components. Chronometrie analysis looks at reaction time differences

for experimental conditions that vary the processing load placed on a single

cognitive ability subsystem. The reaction time contrasts provide a measure of

relative processing difficulty under the contrasted conditions.

Frederiksen and his coworkers have examined verbal performance using such

tasks as the 'pseudoword decoding' task and the 'reading in context' task. In

Frederiksen's Kseudoword decoding task, subjects are asked to pronounce letter

strings bearing a close resemblance to English forms. The letter strings

represent a number of different variations, including variations in length,

number of syllables, and type of vowel. The subject's reaction time from the

presentation of the display to the onset of vocalization is the dependent

variable. Increases in reaction time have been observed for each added letter

in a letter string, for each added syllable, and for letter strings containing

digraph rather than single vowels. The reaction time differences are assumed

to be indicative of the additional processing time required to handle the more

complex letter string forms.

The reading in context task centers on the use a subject makes of prior

context in generating perceptual hypotheses in reading. The task presents the

subject with a series of displays in three frames. The first frame contains

an Incomplete paragraph. The second frame is blank, and the third frame

presents the final phrase of the passage. Subjects are presented with the

context paragraph, they are instructed to read it at their own pace and press

a response button when they have finished. The blank frame is then presented

for 200 msc. The final passage phrase frame follows and is projected for 200

msc The dependent variable is the number of words or word fragments reported

correctly for the third frame. Subjects are presented with all three frames

in one condition. In a second condition, subjects are presented only the

second and third frames. Experimenters are able to assess the subject's use

of context in generating and testing hypothesized word sequences by looking at

15

.\:~
'.»'.V;T;':>VVIM,\ V^IVI^'W\ TWWT1 J

."• '." '."*<'

visual span measurements, defined as the number of letter spaces from the

leftmost correct reported letter to the rightmost correct letter* Increases

In visual span have been observed for the condition where frame one provides

prior context. The increase in visual span is assumed to be Indicative of the

use of information structures provided by prior context to construct

hypotheses about subsequent text.

THE KINTSCH AND VAN DIJK PROSE PROCESSING APPROACH TO THE EXAMINATION OF

VERBAL PERFORMANCE

The Kintsch and van Dijk (1978) prose processing model attempts to

describe the system of mental operations that underlie text comprehension.

The model is based on the premise that the comprehension act can be decomposed

into component processes. The Kintsch and van Dijk prose processing model has

its roots in the propoBitlonal theory outlined by Kintsch in The Representation of Meaning in Memory (1974). The scheme is further explained by

Turner and Greene (1978); these authors also provide a step-by-step guide to

propositionallzing text.

The Kintsch and van Dijk prose processing model is concerned primarily

with semantic structures. A full grammar, necessary for both the interpretation and production of text, is not specified. The model operates at the

level of assumed underlying semantic structures. The theory posits that

comprehension involves knowledge use and inference construction. The model

does not, however, specify the knowledge bases necessary for comprehension,

nor does it disucss the process involved in inference construction.

The Kintsch and van Dijk prose processing model represents textual

information in terms of a text base. A text base is an ordered set of

interrelated propositions depicting the underlying meaning of prose. Propositions are idea units; each proposition represents a single idea. A proposition consists of a relation (previously called a predicate) and one or more

arguments. The relation connects sets of arguments to form an idea unit. The

arguments are either concepts or propositions themselves. A concept is

realized in language by a word or phrase. The words themselves are inconsequential. It is the abstract concepts they represent that are of interest.

Kintsch and van Dijk have adopted the convention of writing a proposition as

follows:

(TRACK, ROCKET, RADAR)

The relation is TRACK. The first argument is ROCKET which functions in the

semantic role of an object; and the second argument is RADAR which serves the

semantic role of instrument of the action defined by the relation. The actual

English text for this proposition might be expressed as : "The radar tracked

the rocket", or "The rocket was tracked by radar".

16

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r

• 8 '
ijiiB<i v«t rjf i w «^^;

Propositions can be classified Into three classes: Prediction, Modification, and Connection. These classes are defined by the types of relations

propositions contain. Relation types impose constraints on the classes of

arguments that can be taken.

Predicate propositions express ideas of action or being. The relations

are usually verbs. Arguments serve such semantic roles as agent, experlencer,

instrument, object, source, or goal of the stated action. Nominal propositions, expressing set membership, and references may also be predicate

propositions. A referential proposition is one which states that the

referent of one argument is the same as that of a second argument. Propositions of reference are frequently implied.

_ Modifier propositions change a concept by restricting or limiting it by

means of another concept. Four different types of modifiers are discussed:

Qualifiers, Quantifiers, Partitives and Negations. These classes indicate the

specific type of modification that is Involved. Qualifier propositions limit

or restrict the scope of an argument or proposition by expressing a quality or

attribute of it. Quantifier propositions express definite or indefinite

quantities. Partitive propositions indicate a part of a collective whole.

Propositions of negation express the complement of a proposition.

Connective propositions relate text facts or propositions to each other.

Connective propositions may be expressed in the text or they may be Inferred.

Thay are important to providing text cohesion. The arguments of connective

propositions are often propositions themselves. Eight categories of connec1 tives are specified.

] 1. Conjunction, expressing union, association, or combination.

2. Disjunction, expressing opposition or alternatives.

3. Causality, expressing cause-and-effect or correlated events.

4. Purpose, expressing reason, purpose or intent.

| 5. Concession, expressing admission of a point or yielding.

6. Contrast, expressing divergence or comparison.

7. Condition, expressing prerequisite states, restriction,

([ or qualification.

i 8. Circumstance, expressing time, location or mode of action.

A text base, then, is a cohesive, Interrelated set of predicate,

modifier, and connective propositions. These propositions represent the

meaning of text. The target text may be coherent, connected discourse united

by a common theme or topic or it may be incomplete and characterized by

missing logical links, facts, references, etc. The propositions suggested by

the text itself may not be sufficient to form a connected and coherent text

i base. The reader may be called upon to supply prerequisite general or

' contextual knowledge or to make inferences about possible, likely or necessary

/ bridging propositions in order to establish semantic coherence. The incidence

cf Inference construction is recognized by the Kintsch and van Dijk prose

- ; processing model; the model does not address itself to the nature of process-

'2 ing inherent in inference construction.

17
uiuwipaiia uuBU*iMiuwi£w jrju'^'M-i w .'i. a i«j'n:i »^ v^M •' ,"nvv VV \'vj nw VHH^H II'T'1

".' ' 'i.'\ '" !": »' ',".

Turner and Greene (1978) state that the Kintsch and van Dijk model of

prose processing can be used as a tool for research Into the cognitive

processes involved in the comprehension of text. Kintsch and van Dijk have

examined the relationship between meaning as represented using propositional

analysis and behavioral Indices of processing difficulty.

They have demonstrated a relation between number of propositions expressed in a text base and processing difficulty. Kintsch and Keenan (1973)

systematically varied the number of propositions in a text base while holding

constant the number of words in the selection. They observed that reading

time increased and recall decreased as a function of number of propositions

expressed. Kintsch, Kozminsky, Streby, McKoon, & Keenan (1975) looked at

processing difficulty as a function of the number of different arguments used

in a text base. Short texts controlled for number of words and propositions

and differing In number of different arguments were read and recalled by

groups of subjects. Reading times were longer and recall poorer for texts

with many different arguments. Texts with fewer arguments had shorter reading

times and higher levels of recall. Kintsch and van Dijk conclude that

comprehension difficulty is positively related to the number of propositions

that must be processed and the number of different arguments that need be

encoded.

Miller and Kintsch (1980) propose that, in addition to propositional

density and number of different arguments, comprehension difficulty is related

to the incidence of Inference construction. Using a computer program written

in two parts, a chunking program to perform thf initial segmentation of text

and a coherence program to simulate processes i. solved in maintaining semantic

coherence, Miller and Kintsch examined processing difficulty and inference

construction. Miller and Kinstr.h modeled twenty texts of varying readability

and used these data to pred-trt. empirically generated recall and readability

statistics. They found significant relations between number of connecting or

bridging inferences necessary to connect segments of text and reading time and

recall data. They summarize that the processing necessary to generate

inferences implied by or implying stated propositions and necessary to

semantic coherence is psychologically relevant and related to comprehension

difficulty

A MODEL OF VERBAL PERFORMANCE

The theory and methods of factor analytic, information processing,

Chronometrie analysis, cognitive correlates a

r.d componential analysis approaches to the study of individual differenr.es are summarized abov'e. This

review of the definition and measurement of cognitive processing operations,

stores, and strategies involved in performance on verbal tas.es provides a

framework for the following general model of rerbal performance.

18

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7*J,"?>"".i

".I".» "> "_«"> ".'<" > V'"'V"A'*',."""J*lr

,

'l3,,t',tt"

tf'E.*,

'w"v|

The model of verbal performance outlined in Figure 1 brings together

portions of the paradigms outlined by Frede-iksen, Hunt, Carroll, Pellegrino,

Kintsch, and others. The model describes verbal performance in terms of the

subset of processing skills associated w'th text analysis.

The model depict

structures. The firs

sor, the second as an

of lexical access and

based information and

a response processor,

not strictly serially

within the system is

the model follows .

s verbal performance by five processing or storage

t structure might be thought of as a perceptual procesexecutive or control processor, the third as the locus

semantic-syntactic analysis, the fourth as knowledgemechanistic information-free storage, and the fifth ^s

Each structure is discussed below. The structures are

or hierarchically ordered. THe flow of information

not necessarily sequential or parallel. A schematic of

VISUM. DISPLAY

Perceptual Processor

A. Visual Feature Extraction

B. Perceptual Encoding

C. Decoding

Executive or

Control Processor

Stört lern Storage

A. Lexical Access

B. Semantic-Syntactic

Analysis

Long Term Storage

A. Knowledge-Based

Information

Structures.

B. .Controlled,

Mechanistic,

Informat ion-Free

Functions

Response

Figure 1. Model of verbal performance.

19

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The PERCEPTUAL PROCESSOR is the structure that inputs stimulus information to the processing system. It Includes the set of operations that

converts the physical stimulus to a form that is appropriate for the task; it

includes the operations that match stimuli to appropriate grapheme and phoneme

representations. The perceptual processor is characterized by three operations described by Frederiksen as: visual feature extraction, perceptual

encoding, and decoding. Visual feature extraction is the operation by which

different types of Information about the stimulus display are extracted.

Perceptual encoding is the operation by which information is input into the

system, and decoding is the operation by which arbitrary physical patterns are

recognized as representations of grapheme and phoneme concepts in the lexicon.

These operations may be thought of as automated, mechanistic processes for the

samples of examinees considered here. The processor may be thought of as a

short term sensory storage or buffer component.

The EXECUTIVE OR CONTROL PROCESSOR is the structure that controls the

flow of information in the system and has access to the various levels of

memory storage. This structure determines the nature of a problem, selects

processes for solving a problem, decides on a strategy for combining these

processes, decides how to allocate processing resources, decides how to

represent the information upon which processes act, and monitors solution

processes. This structure is analogous to Sternberg's metacomponent and to

the executive processor described by Snow, Whitely, and others.

The LEXICAL ACCESS/SEMANTIC-SYOTACTIC ANALYSIS STRUCTURE is a short term

storage or working memory structure. In lexical access/semantic-syntactic

analysis, an attempt is made to match letter strings input at the perceptual

processing stage to appropriate semantic referents. Analysis is directed at

attaching meaning to perceptual patterns. For phrase and sentence units,

analysis is also directed at organizing these meaning elements into coherent

text representations. Lexical, semantic, and syntactic knowledge is called

upon in the identification of words and in phrase and sentential analysis.

Lexical Access is defined as the retrieval of information about

individual words from long term memory. In lexical access, grapheme and

phoneme data drive the retrieval of semantic information.

Semantic-syntactic analysis takes place in short term memory; it is

defined by the retrieval of knowledge-based structures and Information-free

functions. These structures are discussed by Hunt (1978). In

semantic-syntactic analysis, the knowledge-based and information-free long

term memory structures are accessed and, in the case of the information-free

functions, executed in short term memory to form a semantically coherent

representation of prose. Information about Individual words stored in long

term memory is retrieved and arranged to form a semantically coherent

structure. Kintsch and van Dijk (1978) have developed a prose processing

model which references the types of knowledge-based structures and information-free functions involved in semantic-syntactic analysis.

The fourth structure is a long term storage structure. This structure is

the locus of KNOWLEDGE-BASED INFORMATION STRUCTURES and CONTROLLED, MECHANISTIC INFORMATION-FREE FUNCTIONS. The knowledge-based information structures

20

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represent semantic and syntactic knowledge. These structures represent the

ability to deal with words and the concepts they represent. They reflect

experience with and cognizance of the English language. The knowledge-based

information structures are also associated with knowledge of the world and

world events. These knowledge structures are mediated by verbal knowledge but

represent information about the world ancillary to mastery of the English

language.

The controlled, mechanistic, information-free functions are the operations by which information structures are transformed to equivalent structures necessary for task performance. No semantic or syntactic information is

associated with these strategic knowledge structures. These operators are

defined by learned, stored transformation rules. Examples of controlled,

mechanistic information-free operators are the processes of comparing and

inferring. These operators perform such functions as judging the equivalence

of two information structures or generating missing bridging information to

establish semantic coherence for a text.

The comparison operator, for example, is the structure by which two or

more information structures are examined and judged to be the same or different. The inferencing operator is a structure used to establish links

between propositions when semantic coherence for a text is not maintained via

shared arguments.

Inferencing strategies generate the missing or non-derivable connecting

or bridging information necessary to maintain semantic coherence. Inference

processes may be used to determine reference or define enabling conditions.

They may also be used to specify resultant events, that is, events not

entailed by stated conditions, but bearing a high probability of occurrence

given stated conditions.

The final structure is the RESPONSE OPERATOR. This is the structure

through which appropriate motor actions are selected and executed. The

response operator is the structure by which the examinee makes an observable

response, such as selecting one response from a set of multiple alternatives.

The verbal comprehension or verbal information processing model characterizes performance with respect to the subset of processes which underlie

text comprehension. The model synthesizes portions of processing paradigms

described by Frederiksen, Hunt, Carroll, Pellegrino, Kintsch, and others. It

provides a useful conceptual framework for the examination of cognitive

processing operations, stores, and strategies involved in performance on

verbal tasks.

21
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