DOCUMENT RESUME

En 205 571 TM 010 456

AUTHOR Yalow, ElRnnnTITLE Individual Differences in Learning from Verbal and

Figural Mater?als. Technical Report No. 12: AptitudeResearch Protect.

INSTITUTION Stanford Univ., Calif. School of Education.SPONS AGENCY Advanced Research Projects Agency (DOD), Washington,

D.C.: Office of Naval Research, Arlington, Va.Personnel and Training Research Programs Office.

PUB DATE Sep BOCONTRACT N00014-75-C-OB92NOTE 90p.

'EDRS PRICEDFSCRIPTORS

MF01/PC04 Plus Postaae.*Academic Ability: Aptitude Tests: *AptitudeTreatment Interaction: *Educational Strategies: HighSchools: Individual Differences: *InstructionalMaterials: Pretests Posttests: *Remedial Instruction:Social Studies: *Time Factors (Learning)

ABSTRACTOf primary interest in this study was the effect of

general ability on learning. It was hypothesized that students higherin general ability would obtain higher posttest scores on theaveragethan lower ability students, and 'that verbal and figural explanatorysupplements to minimal instructional materials would reduce theregression of general ability on outcome. It was expected thatstudents with higher aptitude scores would obtain higher posttestscores. The effects of a more task-specific aptitude, graphprocessing, were explored, and involved both, immediate and delayedlearning outcome measures. A course in Economics was presented tohigh-school students using one of three sets of instructionalmaterials. Before the course, participants took a three-hour aptitudebattery and were randomly-assigned to treatment. Posttests wereadministered at the end of the course and two weeks later.Generalized regression analysiS was used to assess the effects ofaptitudes, treatments, and interactions. This study provided evidencethat neither aptitude nor instructional treatment alone can fullydescribe learning outcomes. Further, instructional supplements, canbe effective in filling in for student weaknesses and reducingdifferences between high and low ability students. (Author/GK)

**********************************************************************Reproductions supplied by EDRS are the best that can be made

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INDIVIDUAL DIFFERENCES IN LEARNINGFROM VERBAL AND FIGURAL MATERIALS

ELANNA YALOW

TECHNICAL REPORT NO. 12APTITUDE RESEARCH PROJECT

SCHOOL OF EDUCATIONSTANFORD UNIVERSITY

Sponsored by

Personnel and Training Research ProgramsPsychological Sciences Division

Office of Naval Research

and

Advanced Research Projects Agency

under

Contract No. N0001,1-75-C-0882

Approved for public release; distribution unlimited.Reproduction in whole or in part is permitted for

any purpose of the United States Government.

SEPTEMBER 1980

DEPARTNIENT OP EDUCATIONNATIONAL INSTITUTE OF EDUCATION

IDUCATIONAL IILfi0lII10E8 INFODMATIONIEHICI

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"PERMISSION TO REPRODUCE THISMATERIAL HAS BEEN GRANTED DY

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TO THE EDUCATIONAL RESOURCESINFORMATION CENTER (ERIC)."

INDIVIDUAL DIFFERENCES IN FEARING

FROM VERBAL AND FIGURAL MATERIALS

ELanna Yalow

TECHNICAL REPORT No. 12

APTITUDE RESEARCH PROJECT

SCHOOL OF EDUCATION

STANFORD UNIVERSITY

Sponsored by

Personnel and Training Research ProgramsPsychological Sciences Division

Office of Naval Research

and

Advanced Research Projects Agency

under

Contract No. N00014-75-C-0882

The views and conclusions contained in this document arethose of the author and should not be interpreted asnecessarily representing the official policies, eitherexpressed or implied, of the Office of Naval Research,the Advanced Research Projects Office, or the U.S. Government.

Approved for public release; distribution unlimited.Reproduction in whole or in part is permitted for anypurpose of the United States Government.

September 1980

UNCIASSITIFD- ,

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977r irt' 0141.11N G ONG/kW/ A TION 11 AMC AND Aluu4rSe11001 Of EdllealiOnStanford UniversityStanford, California 94305

II. CONTROLLING OFFICE NAME ANN ADDRESS

Personnel kind Training ResearchPsychological Sciences Division,

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ProgramONR, 458

12. REPORT DATESeptember 1980

IL NUMBER OF PAGES44

14. MON I TUNING AGENCY NAME A ADDRESS(If ,Iillernt h011) Controlling Office) IS. SECURITY CLASS. (of this report)

UNCLASSIFIED

IS& DECLASSIFICATION/DOWNGRADINGSCHEDULE

16. DISTRIBUTION STATEMENT (of this Report)

UNLIMITED

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UNLIMITED.

lb. SUPPLEMENTARY NOTES

This research was jointly sponsored by the Office of Naval Research andthe Defense Advanced Research Projects Agency.

19. KEY WORDS (Continue on revora aide II ncrerriery and Identify by block number)

Aptitudes, aptitude-instructional treatment interaction, cognitiveabilities,learning, verbal vs. figural materials in instruction,elaboration of instruction.

20. ABSTRACT (Continue on reverse aide If necessary and Identify by block number)

The effects of supplementary verbal and figural instructional materialson students of different abilities are not fully understood. Findings inthis area have been inconclusive and inconsistent. Rarely have treatment oraptitude specifications been sufficiently precise to relate outcome to partic-ular instructional components. The present study attempted to improve onsome of these shortcomings.

Of primary interest in this study was the effect of general ability onlearning. It was hypothesized that students higher in general ability would

DD 1 JAN k73 EDITION OF I NOV 65 IS OBSOLETE.

N 0107. LF 014- 6601UNCLASSIFIED

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ino:lto!:1 rutihointoro, i f wiei hypetheHi thAt t:c and I;lv might

moderato the relAllow; between instiihilon And outieme different ly.

Ih,ll emeil 1,eci i I too.1 111 1 11 at tntont 1 llrld

I It I:c; .,11 to !own I offiont wo o;tpoct 1,1 I o part It 0,1 11':o n oilool ii

ow Intko explored the ellecui of a more f;ed:-.spiiellie aptitude, wrap',

precelng, en outcome, And Involved both immedi ito 11111 delayed learning out

come 1111',1!:11 I'1':;

A i.otirse 111 Fconowits wa!; piesented to high !whool students using

line oe sets III i 11:;1 luI ;mid I mat er ta lie fore t he course part tolpont::

took o 1-hoor .Aptilnko holtorV and wro tondomly 4o;ot,t;ned to troatmOnt. POnt-

r,,t, wore administered ;It the end of the course and two weeks later.

The Inpitc trootwont covered the theory of MaYkot prio,O, Treatments varied

in the ixplAnAtory di,iplays 'and the difficulty of the processing demands, duo

treAtment (M1N)presented the information with little redundancy, feo examples,

and limited explanations. Another (VF) covered the same material 1 MIN, cd.th

additional verbal expansion materia i. A third (EN) covered the material of

MIN, with additional graphs and diagrams as figural expansion.Ceneralied regression analysis was used to assess the effects of aptitudes,

treatments, and their interitions (ATI). On the immediate posttest, students

in VF and FE did better than Htudents in MIN, suggesting that the elaboration

provided in these conditions helped students learn. Significant ATIs suggest-

ed that the elaboration was particularly useful to low ability students. High

ability students did as well or better in MIN. Thus, the regression of

achievement on general ability was steepest in MIN and reduced in VE and FE.

Partitioning the total test score by posttest item type indicated that VE

was particularly helpful on verbal items and FE was particularly helpful on

figural items. Again, significant ATI indicated that these treatments were

particularly helpful to loan ability students. Hence, the regression of ver-

bal items on general ability was least steep in VE; the regression of figural

items on general ability was least steep in FE.

Examination of learning outcomes on retention, however, led to strikingly

different conclusions. While students In MIN were worse on average achieve-

ment on the immediate posttest, they performed the best on retnetion. Losses

iron) Immediate to delayed posttest were greatest when the 'assistance was most

direct. That is, losses on verbal items were greatest in VE; losses on fig-

ural items were greatest in FF. No significant main effects or ATI were

associated with the differential between Cc and Cfv on either posttest.

in summary, this study provided evidence that neither aptitude nor instruc-

tional treatment alone can fully describe learning outcomes. Interactions

between them exist and were demonstrated. Further, instructional supplements,

whether verbot or figural, can be effective in filling-in for student weak-

nesses and reducing differences between high and low ability students.

Such supplements, however, lint he used with caution. Reducing the diffi-

culty of instructional materials may, indeed, enhance immediate learning, but

these advantages mav short-lived.

S N 0102- 41. 01,1.660)UNCLASSIFIED

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PltriAil

Tho Inve:ltlp,Atton 101101.14.d heroin ptil ail on onv.olt

ronmarch rolect almod at tuolortandfur lite nature and

importance of Individual diffecoocen in apflundo for

learning. Requent!i tor infotmation Ink proloct

and for copion of thin or cohou technical icportn

be addre.lann to:

Profeanor Richard E. Snow, Principal invontigator

Aptitude itencarch Project.

School of Education

Stanford University

Stanford, California 94105

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Descriptive Statistic:: 1.5

Aptitude Measures .15

Outcome Measureq 17

Correlations Between Aptitude and Outcome 19

:Tression Analyses on Outcome 21

T3tal Score Ana_jses 22

Part Score Analyses 24

Verbal Items 24

Figural Items 27

Problems 31

Summary of ReE,rerion Analyses 31

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.1 I the most important aptitude for learning from instruction. Mossuros

oi general ability also seem to show the strongest mid most consistent

Al I.. This is, then, the logical place for now AI research to start.

[lie bulk of prior evidence is consistent with the following hypo-

thesis: When instruction places heavy information processing burdens on

learners, the regression of learning outcomes onto general ability differ-

ences is relatively steep; able students do well and less able students

do poorly. In contrast, when an instructional treatment is designed to

relieve some of the information processing burdens on learners by simpli-

fying, structuring, or elaborating the learning task, the regression of

outcome on general ability is relatively shallow; less able students

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Aocond, difforooflAI, hvpotho IhAf thc

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relative strength And woaknwoi of 61v And t;,. In loAlno411 141111111.1 lit' hono

ticIAI, and Isolated at based on this hypothesis have lopotIod ATI.

lint two different and opposing, 1cind:1 ot marching are possible, and both

have been found; matching to the lolunc.r'q !iirength mkbt be honvlicial

in some ways, but matching to the learner's weakness might have compensa-

tory benefits. In one typical study, for example, Peterson and Hancock

(1974) taught students the mathematics of network tracing using either

verbal, symbolic, or figural materials. Aptitude measures were selected

from Guilford's (1967) system to represent these three content areas.

Posttests were administered immediately after instruction, and again

after one and five weeks. The regression on verbal ability was shallower

In the verbal treatment than in the figural or symbolic treatments al:

all three testings, suggesting that low verbal students were compensated

by a verbal treatment. The regressions of outcome on figural and symbolic

ability were shallower when aptitude matched the instructional condition

only on the immediate posttest. On both retention measures, regressions

were steepest for figural and symbolic ability in the figural and symbolic

treatments, suggesting that one should match to strengths.

The results of other studies investigating relations between verbal

and spatial ability in instruction have also been inconsistent. Allison

(1960) provided instruction on concept attainment tasks using either

verbal stimuli and semantic solution rules or geometric stimuli and

classification solution rules. Verbal and spatial aptitude measures

were used. Those higher in verbal ability did better with verbal con-

tent; there was no effect for spatial ability. Bracht (1970) taught

addition of signed numbers using figural or verbal programmed texts.

Numerical, verbal and spatial aptitudes were measured. There were no

significant ATI. Markle (1969) taught crystallography using programmed

texts composed either entirely of words or emphasizing diagrams. The

pattern of correlations of outcome with verbal and spatial measures was

similar in both treatments. In a series of studies by Carry (1967),

Webb (1971), and Eastmaa (1972), students were taught quadratic inequali-

ties using materials designed to capitalize on spatial-visualization.

After reviewing this series, Cronbach and Snow (1977) concluded, "The

three studies together provide only negative evidence on the possible

relevance of vusualization to a piesentation that uses graphs",(p.285).

3

On the tasis of these and other mixed results, Cronbach and Snow

(1977) rejected "the conclusion that spatial treatments demand spatial

ability and that differentiated Guilford abilities will interact with

treatments of the same name" (p. 293). They did not rule out the possi-

bility of positive findings in the future, however, given more powerful

and penetrating analyses.

Gustafsson (1974; 1976) also obtained conflicting results in a

series of studies exploring the verbal vs. figural contrast. Two of

these studies used a text on polar lights as a verbal treatment; the

pictorial, treatment was a slightly reduced text supplemented with illus-

trations. Aptitude measures included a vocabulary test, a reasoning

test, and a spatial-visualization test. Learning was measured by a short

answer test and an essay test. Results on the essay test were not con-

sistent across the two studies. On the short-answer tests in both

studies, the slope of the regression on verbal ability was steeper in

the verbal treatment than in the pictorial treatment; students low in

Gc did best with pictures, especially if they were also high on Gv.

Students in the third study were taught about the heart and the blood

circulation system using either illustrated or unillustrated materials.

Immediate and delayed outcome measures included items assessing verbal,

pictorial, and spatial criteria. Aptitude measures represented Gc and

Gv. There were no substantial ATI for the verbal or spatial criteria.

Although the pictorial treatment was best for everyone, an ordinal inter-

action indicated that this treatment was least advantageous for students

high on Gc and low on Gv.

More-recent research has not changed the picture appreciably. James

and Knief (1978), for example, taught students to determine tie number of

4

I

subsets in a set of elements using a treatment designeu to capitalize

on either Gf or Cc. A sum of Cc and Gf scores represented general

ability, and the difference between the two scores represented the dif-

ferential hypothesis. A pretest and posttest wee administered. There

were significant main effects and ATI with the sum, but neither the

difference score nor any of its interactions were significant. Although

high ability students, on average, outperformed low ability students,

the treatment designed to capitalize on Gc reduced their advantage.

The consistent results for the general-ability hypothesis, and the

inconsistent results for the differential ability hypothesis, are both

understandable in hindsight. The wide variety of instructional treat-

ment contrasts that yield ATI with general ability can be summarized in

terms of variation in amount of information processing demand, but this

is only a crude summary, at best. The demand characteristics of differ-

ent kinds of instruction are not understood in detail, nor is a process

theory of ability for analyzing task demands in relation to individual

differences available. Treatments are usually poorly specified, and

this hampers our pursuit of both the general and the differential-ability

hypothesis. An enormous range of instructional materials have been

labeled "spatial" or "verbal" with little thought about their processing

demands. The presence of figures or pictures does not indicate that a

treatment requires spatial ability. Diagrams can tax ability but they

can also compensate for weakness. Similarly, it is insufficient to

attach global labels to categories of ability. A "spatial" ability test

does not necessarily measure spatial ability (Lohman, 1979a; 1979b).

Aptitude measures should be understood in terms of amount and kind of

processing demand.

There is not likely to be a simple match of aptitudes and treatments

(Cronbach and Snow, 1977; Salomon, 1972). Some kinds of instruction

build upon the learner's capacities or preferences, requiring students

to bring possessed abilities to bear in learning. Alternatively, in-

structional materials may do for learners what they cannot do for them-

selves, and so may reduce ability-outcome correlations. Less able

students might profit from such assistance, whereas able students might

be turned away by it. Further, learners may substitute abilities they

possess for those they lack. Thus, graphic problems might be solved by

either verbal processing strategies or by direct manipulation of lines

and curves.

Thus, the inconsistency and complexity of earlier ATI results seem

due, in part, to the failure to specify requisite abilities for carefully

delineated treatments, or to provide a common process ription for

aptitude and learning tasks. There has also been inadequate considera-

tion given to the multiple ways in which, aptitudes and treatments might

be matched. The notion that students of high spatial ability necessarily-

do better in spatial treatments ignores the complexities of both ability

and instructional material.

The Present Study

The primary hypothesis investigated here related general ability to

learning. First, students higher in general ability were expected to

obtain higher posttest scores on the average than lower ability studOts.s,

Further, both verbal and figural supplements were expected to reduce the .

slope of the regression of outcome on general ability. The effect/of

verbal supplements was expected to be greatest on verbal outcome measures;

the effect of figural supplements was expected to be greatest on figural

outcome measures.6

1 1-.!-.0

The present study also explored the differential impact of Gc and

Gfv on learning. It was hypothesized that students high in either Gc

or Gfv would learn more than lower ability students. It was further

hypothesized that Gc and Gfv would moderate the relations between instruc-

tion and outcome differently. Verbal supplements were expected to be

particularly useful to students low in Gc; figural supplements were

expected to be particularly useful to students low in Gfv.

Finally, the study was planned to examine long-term as well as

immediate learning. A reduction in average scores from immediate to

delayed posttest was expected. The greatest drop in performance was

expected when instructional supplements were used. By reducing process-

ing demands, supplements might enhance short-term learning while reducing

long-term learning. This effect would be particularly evident where

instructional content and outcome were matched. That is, losses on

verbal outcome measures would be greater when verbal supplements were

used than when figural supplements were used; losses on figural outcome

measures would be greater with figural supplements.

To summarize, this study assessed the relations among aptitudes,

instructional supplements, and learning outcomes. Gc and Gfv were the

aptitudes of particular interest, although more specific aptitudes were

also included. Instructional materials differed in the use of verbal

and figural supplements. Outcome measures distinguished verbal from

figural responses. In general, this study was intended to illuminate

the relations between aptitude and instructional treatment.

7

.A."1

CHAPTER 2

METHOD

A 2-week course in Economics was presented to high school students

using one of three sets of instructional materials. Beforehand, partici-

pants completed a 3-hour aptitude test battery and were randomly assigned

to treatment. One posttest was administered at the end of the course;

another was given two weeks later.

Sample

Participants were recruited from three Palo Alto, California, high

schools. Tenth- and eleventh-grade students responded to an advertise-

ment in\a kcal newspaper and were paid an hourly fee for their partici-

pation. The initial 3-hour aptitude session included a 10-item screening

test to eliminate those already familiar with the instructional content.

Of the 146 students who initially responded, 132 were retained and

completed the experiment. The final sample included 86 females and 46

males; 44 participants were assigned to each of the three conditions.

Treatments

The basic instruction covered the theory of supply and demand,

determination of market price, elasticity of supply and demand, and the

application of these principles to price floors and ceilings, taxation,

and agricultural problems. Materials were adapted from introductory

college economics textbooks (Lipsey and Steiner, 1969; Samuelson, 1976;

Spencer, 1977; Sutton, 1976), but presented at a level appropriate for

high school.

The same material was covered in each treatment condition. Treat-

ments varied, however, in the explanatory displays and the difficulty of

the processing demands. The three instructional conditions were Minimal

8

1 n

(MIN), Verbal Elaboration (VE), and Figural Elaboration (FE).

Information in MIN was presented with little redundancy, few

examples, and limited explanations. Participants were encouraged to

solve problems on their own and to generate their own explanations for

facts and principles. Principles were presented with limited verbal

explanations and figural displays.

VE covered the same basic information as MIN, but with additional

verbal material. Examples were given, verbal explanations were presented,

and basic concepts were redefined as learners encountered new material.

Figural content was identical to that of MIN.

FE also covered the same basic MIN material, but with additional

graphs and diagrams. Examples and exercises using graphs in problem

solving were added. Additional verbiage was used only to help students

understand and manipulate diagrams. The differences among treatments are

summarized in Table 1.

Each treatment consisted of eight 50-minute instructional sessions.

Participants were limited to one instructional session per day.

Materials

Aptitude Measures

Four tests were selected tgmeasure\Gfv: The Advanced Progressive

Matrices Test (Raven, 1962), Paper Foldin Test (French; Ekstrom, and

Price, 1963), Copying Test (French et al., 1963), and Memory for Designs

'(Graham and Kendall, 1960). Measures of Gc included the Terman Concept

Mastery Test. (Terman, 1956), Advanced Vocabulary Test V-4 (French et al.,

1963),.and a fill-in vocabulary test adapted from the Wechsler AdultN

Intelligence Scale (Wechsler, 1955). The latter consisted of 20 words

9

TABLE 1

Summary of Treatment Specifications

Treatment

Component of Instruction MIN VE

General information

Basic,statement of economic principles

Verbal

Figural

Explanation of principles

Verbal

Figural

Examples

Practice problems

Solutions,tu practice problems

Explanations of solutions for practice problems

Verbal

Figural

Redundancy

Verbal

Figural\

Underlining

N

Note. "+" indicates -a component present in the treatment

"-" indicates a component not present or used minimally

10

from the WAIS vocabulary sectior, representing the full rang of item

difficulty. Items were scored using the guidelines presented in the

test manual.

A test of graph processing (GRAPH) was designed and administered to

supplement the broader ability tests. This test measured the ability to

read graphs and to interpret data presented figurally. Items required

either translating verbal information to graphs or giving verbal des-

criptions to interpret graphs.

Another instrument designed specifically for this study was the

Cognitive Preference Questionnaire. This questionnaire asked students

if they preferred learning from verbal material or by reasoning about

diagrams and figures. Attitudes toward selected instructional features

and learning strategies were also solicited.

Instructional Materials'

Three workbooks, corresponding to MIN, VE, and FE, were developed.

Each workbook was composed of eight 10-20 page packets and introduced

approximately three new topf.cs. Students worked through the workbook

in a prescribed manner, answering questions and solving problems in the

packet.

Each packet began with a Summary Sheet listing the major topics

covered in previous sections. In VE and FE, major points were summarized

in the appropriate mode. Participants in MIN were cued to generate the

summary for themselves.,

The last pages in each packet contained problems relevant to the

material covered during the instructional session. These Problem Sets

were included'to encourage students who completed the material before

11

the end of the session to review it, thereby equalizing students' working

times.

Outcome Measures

An immediate and a delayed posttest were administered after the comple-

tion of each instructional unit. The two posttests were similar in format

and content. Each test consisted of 40 items and covered most of the material

presented during the instructional period. On each test, 15 items re-

quired students to answer verbal questions, 15 required students to deal

with figural information, and 10 questions required both verbal and

figural explanations. For these 10 items, the student was asked to indi-

cate the explanation given first. Within each of these categories,' items

required either the application of principles to solve a problem, or

simple recall or recognition of information specifically discussed during

instruction. Response formats included multiple-choice, fill in, and

short problems. Approximately one hour was alloted to complete each

posttest. Table 2 lists the parts of each posttest, including item type

(figural vs. verbal), response format, and the number of items.1

Procedure

Instruction began approximately one week after aptitude testing.

Participants attended one 50 minute session for each of four days during

the first week of instruction, and for each of five days during the

second week of instruction. Students completed one packet of material

during each session. Sessions were held hourly between 3 p.m. and 11 p.m.

on weekdays, and between 9 a.m. and 5 p.m. during the weekend. Students

12I' .e)titi

Table 2

Summary of Outcome Measures

ouLcome Measure Description Maximum # of Points

Total Posttest

Verbal Total

Part 1Part 2

Figural Total

Part 1Part 2Part 3

ProblemsVerbal correctFigural correctVerbal firstaFigural firsta

Total number of correct items

Total number of correct verbal items

Fill-in verbal itemsMultiple-choice verbal items

Total number of correct figural items

Fill-in figural items ; draw figure

Fill-in figural items; interpret figureMultiple-choice figural items

Total number of correct problemsNumber of correct verbal explanations on problemsNumber of correct figural explanations on problemsNumber of correct verbal explanations given firstNumber of correct figural explanations given first

40

15

10

5

15

5

5

5

10

10

10

10

10

Note. Format of Immediate and delayed posttest was identical

Numbers of verbal first and figural first apply only to correct explanations on the problems.

were allowed to schedule themselves freely except that no more than 30

students could be accomodated in a single session.

Upon arrival, students would take a folder bearing their name, and

remove the appropriate packet. At the end of the session, students

returned the packet to the investigator, who checked that the student

had worked on the proper materials. It was not necessary to schedule

participants in the same treatment for the same hours as all students

worked individually.

The immediate posttest was administered to each student after all

instructional materials were completed. All participants took the immediate

posttest on the Friday of the second week of instruction. Most partici-

pants returned for the delayed posttest two weeks later; those who could

not were scheduled individually for their delayed posttest. All partici-

pants completed the delayed posttest within 11 to 17 days after the

immediate posttest.

r-

14

0 k-1

CHAPTER 3

RESULTS

Descriptive Statistics

Aptitude Measures

Means, standard deviations, reliabilities, and courelaticns dmon

aptitude measures for the entire sample are presented in Table

Similar tables for the separate samples in MIN, VE, and FE are presented

in Appendix A.

Scores from the two vocabulary tests and the Terman Concept Mastery

Test were standardized in the total sample and combined to form a com-

posite labeled Gc. The Gfv composite included standardized scores for

Copying, Memory for Designs, Paper Folding, and the Advanced Progressive

Matrices Test. Although GRAPH showed high correlations with both com-

posites it was left as a separate third aptitude since it was thought to

be specifically relevant to this instructional setting. About 42% Of

its variance was estimated to be specific.

Tests included in the Gc composite showed higher correlations with

each other than with measures of Gfv. Copying and Memory for Designs

had higher correlations with other measures of Gfv than with indicators

of Gc. As expected, however, Paper Folding and the Advanced Progressive

Matrices Test, both complex measures of Gfv, showed higher correlations

with Gc than did Memory for Designs and Copying.

The Gc and Gfv composites were combined to form two orthogonal

indices to investigate their combined and differential importance: SUM,

the sum of the Gc and Gfv composites represented general ability, and

DIFF, Gc minus Gfv represented the ability profile difference. Positive

values on DIFF thus indicate students higher in Gc than Gfv, and negative

15

Table 3

Means, Standard Deviations, and Correlaticns ofAptitude Measures for Total Sample (N - 146)

Variable Mean S.D. (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

b(1) Vocabulary Multiple Choice 15.11 4.58 80 68 67 26 11 33 38 36 88 36 71 55

(2) Vocabulary Fill In 26.62 5.76 78a

71 30 27 49 54 53 90 52 81 39

(3) Terman Concept Mastery 30.10 5.10 78a

36 32 49 54 56 89 56 83 34

(4) Copying 32.06 9.41 88b 37 49 53 40 35 79 65 -46

(5) Memory for Designs 17.00 2.09 60a

31 37 38 26 68 53 -43

(6) Paper Folding 13.45 3.50 80b

53 50 49 77 71 -29

(7) Advanced Progressive Matrices 23.64 5.47 83a 62 54 80 77 -27

(8) GRAPH 22'.64 5.50 86a 54 62 66 -08

(9) Gc .00 1.00 91 54 88 48

(10) Cf./ .00 1.00 93c

88 -48

(11) SUM .00 1.76 95c 00

(12) DIFF .00 .96 83c

Note. Decimals omitted from correlations.Reliabilities appear in the main diagonal.

aReliability estimate coefficient a.

bSplit-half reliability estimate.

cReliability estimated as composite.

values indicate an advantage in Gfv. This procedure has advantages over

using Cc and Gfv directly in the analysis (Cronbach and Snow, 1977). First,

hypotheses can he ordered so that the general-ability hypothesis can be

tested independently from the more exploratory differential-ability

hypothesis. Second, SUM and DIFF are uncorrelated, whereas, Gc and Gfv

usually correlate (r 3 .54 in this study). Thus, using SUM and DIFF

prov._asless ambiguous interpretations than using Gc and Gfv directly.

Although students were randomly assigned, the equivalence of groups

was checked. There were no significant mean or variance differences

among the treatment conditions on any of the aptitude measures and only

minor differences in the pattern of correlations in the three treatments.

Thus, no systematic aptitude differences among the three groups could be

identified.

Outcome Measures

Reliabilities of the immediate and delayed posttest were estimated

at .82 and .84, respectively, using coefficient alpha. Correlations

between total scores and major part scores on the immediate and delayed

posttests are presented in Appendix B.

Means and standard deviations for all parts of both posttests are

reported in Table 4. While treatment differences on the immediate

posttest were not always large, group averages in VE and FE were consist-

ently higher on items corresponding to the type of assistance the group

had received. On the average, students in VE and FE also obtained higher

scores on the problems than students in MIN. Thus, the mean total post-

test score was higher for VE and FE than for MIN.

This pattern was not found in the delayed posttest means, also

reported in Table 4. Here, MIN showed a slight overall advantage over

17

r).1/4.0

Table 4

Meann and Standard Deviations on PontAent

Immediate PoulAest. Delayed Pouttest

Treatment MIN V'. FE MIN VE FE

Outcome Mean S.D. Mean S.D. Mean S.D. Mean S.D. Mean S.D. Mean S.D.

Total Posttest 26.27 7.20 29.52 5.25 28.34 4.66 28.89 6.80 27.98 6.18 26.39 6.39

Verbal Total 10.11 2.94 11.89 1.82 10.23 2.11 10.91 2.30 10.09 1.96 10.11 2:22Part 1 7.43 1.68 8.48 1.30 7.41 1.57 7.57 1.93 6.95 1.61 7.16 1.79Part 2 2.68 1.58 3.41 1.00 2.82 1.11 3.34 .96 3.14 .85 2.95 1.03

Figural Total ,.57 2.71 10.50 2.62 11.20 1.71 11.11 3.08 10.82 2.74 9.48 2.81Part 1 3.52 1.27 4.09 1.01 4.27 .85 3.93 1.28 3.84 1.01 3.57 1.15Part 2 _ 3.95 1.06 4.05 .91 4.09 .80 3.98 1.15 3.57 1.00 3.05 .99Part 3 2.09 1.14 2.36 1.12 2.84 1.03 3.20 1.27 3.41 1.26 2.86 1.29

Problems 6.59 2.67 7.14 2.11 6.91 2.17 6.86 2.46 7.07 2.29 6.80 2.54) Verbal Correct 4.02 3.24 5.52 2.83 4.09 3.23 4.61 3.24 5.34 3.28 5.14 3.32

Figural Correct 3.55 2.97 3.43 2.67 3.64 2.74 4.25 3.37 4.91 3.45 4.95 3.54Verbal First 2.14 2.46 4.20 2.83 2.52 2.52 2.25 2.66 2.70 2.75 2.59 2.74Figural First 1.80 2.48 .98 1.68 1.95 2.06 2.50 3.02 2.48 2.54 2.98 3.14

VE and FE on total posttest :irate. Thus, although elaborating and

simplifying instruction (as In VE dIld FE) apparently ptoduced immediate

galns, information acquired through such Instruct: Lou was nut: retained as

well as Lt was In MEN. MIN actually showed a small average gain lrom

immediate to delayed tests, while VE and FE showed losses. The greatest

Losses occurred when treatment and posttest item type were alike. That

is, the greatest losses on verbal items appeared in VE; the greatest

losses on figural items appeared in FE.

On the immediate posttest, there were small differences among groups

in the type of explanation given on the problems. On average, students

in VE gave correct verbal explanations more frequently than did students

in either MIN or FE. Verbal explanations were also more likely to be

given before figural explanations by students in VE. Similarly, in FE,

correct figural explanations to the problems were, on average, given

before verbal explanations. Similar trends were found on the delayed

posttest.

Correlations Between Aptitude and Outcome

Table 5 gives selected correlations between outcome and aptitude

measures. (See Appendix C for complete correlation matrices.)

Significant correlations between SUM and all outcome measures

appeared in all treatments, while correlations for DIFF never differed

from zero. The correlations between total posttests and SUM were similar

in the three treatments, but part scores on the immediate posttest

showed some variation across treatments, particularly when item type and

treatment matched. So, for example, SUM and the immediate verbal total

correlated .50 in VE, but .74 and .72 in MIN and FE, respectively.

Similarly, SUM and the immediate figural total correlated .50 in FE, but

19

0 0

Table ')

Corralatlutm lletweett Selected Aptitude ant Putteai VaViAlvu

'!'reatmout

--- AptitudeOutcome Measure----:.

SUM

MI N

UHF GRAPH SUM 1)1. Fl GRAPH SUM

FE

DLFF

Immediate Posttest

Total Score 83* 04 69* 75* 02 64* 79* 12 65*Vethal Total 74* -05 63* 50* 00 38* 72* 05 65*Figural Total 68* 04 65* 69* -02 64* 50* 22 39*Problems 73* 13 57* 59* 06 47* 60* 03 46*

Delayed Posttest

Total Score 78* 03 71* 83* 00 62* 76* 03 70*Verbal Total 54* 05 38* 72* 01 42* 52* 04 58*Figural Total 70* -04 76* 78* -07 61* 69* 08 54*Problems 77* 09 65* 69* 07 58* 70* -06 66*

Note. Decimals omitted from correlations

*2 less than .05

f111 :UI' f1'1 111 NITA Altd Vt.. .0

colavb!IIIina wIlh 11t1 nolo vIiInnIIV IdonthaI In V. and Vt. antiowhat

!MIA I I 4! I I 11. hi I Ito do III votI lemil 1 0;$1 , I Ili' I III 1 0 I .t1 I ton Ill! WOVII

'AN and iho 1'1 11:11 WAri Iar1',0:1( III vr.

Cnirolallnun holwoon OkAPH iutit tint Imilioafalo unIctuo wcio gonolally

lower 111,in those holweon ;1h4 and onloomo. Thoro wore, howover, idle)

OWtt r t orre I .11 mill hot wool, (;:tAni 1111(1 I initivd I It( 1. (' ()I1W WIWI% I VIII.. alit(

treatment wore mathod, On the delayed ponttent, there wore nnIy

differences among the treatments In the correlations of GRAPH with total

posttest score and the probiems. The corretation between the verhat

total and GRAPH was greatest in FE. The figural total and GRAPH had the

largest correlaLion in MIN.

Regression Analyses on Outcome

Cronbach and Snow (.1977) recommended generalized regression analysts

for investigating ATI. The model for the present study took the form:

Y= 0 t'SS N)131 BG C "T T "ST ST

BDT

DT +BGT

CT

where:

Y = uevendent variable

B0 = constant term

Bs, BD, Bc = regression coefficients for SUM, DIFF, GRAPH

S, D, G = score on SUM, DIFF, GRAPH

T= regression coefficient for treatment

T = orthogonal treatment contrast

BST'

BDT'

$GT

= regression coefficients for first-order ATI

Two orthogonal contrasts represented the three treatments. The

first contrast (T1) compared MIN with VE and FE (coded 2, -1, -1,

21

1 ',1/1.111 1 \'4.,1 1 I II.: 4241 "41,1 , 11114 ,1421 I to

I I cz, I I v 4: I v I h ^I I n 11,Ic11 Iil 1 4111110 WO 1-, 111141111 42.1 le V 111111 1 I

III V 1111; 11 011111142 :111 1 11111 J I 1 11 :4111 I I 11,1c. ,

4111;11 :I I d 421142 I yZIC:1 tsle 111111111 1 1111 111 1 111 11441 I :11'111 can ilki

ImmodIalc and dolayod 12I 1211 1111 III (t.:till( 43 WIWI 11:141(1, W1 1 11

VIII 1 lib 14201 turf vd 11110 ( 1142 oqnat lion III a a11c11 l r 1041 1111101 . Ati( 1111110 ma In

r Za W4-11.0 Oili t! 10(1 1) 1)1 11 d41( (HOU! r 4,21 1 d, Wi I Il ;1111 rani oral! r I I d1 I I)

I Or* I IIto HuttelaI --allI t It y hypot DiFF was ent tared next to test the

a t 101'eut hit -011)1 1,1 yitnthwa CHAN! wita I lion out rtat 141 Atititulti Itti

specific contribution, independent ot the proportion or its effects that

were associated with general and differential ahilify. Treatment main

effects were then entered using the two orthogonal. A"ontranta. Following

all main effects, first-order ATI were entered. Thin order wan used for

all dependent varlables.

Total Score ATAlyses

The results of the regression analysen for the !mmediate and delayed

total posttests are presented Lu Table 6. The percentage of variance

accounted for reflects the change in the squared multiple correlation

coefficient as each predictor entered the equation. The F-ratio tested

whether this change in R2was significant using the formula:

AR2/Ki

1-R2

t/N-K

t-1

where:

AR2= increment in R2

K = number of predictors in change

R2

t= R

2for full model

N = total sample size

Kt= number of predictors in total R2

22

I (.

',Willi,' I ', 61 I. 111/ 114. k I' 4'f1,1 hilt I I I..I.1I 1%1 ,f 1

V i I I'

Fill I 1141,14. I

A111 1111411' 1'141 1114 I tri

II I

I I

1111114'.1 I :11 rti::1

VZi I I

114 11411111 4'41 1.'141

')

/

.3

1:1i III

?1..11

lII.'I

V:I I 141111.4!

Acwint

611.6

I .11

1.111A

II 1.1/11A

!111t1 '11. 1 ??1{. /11A (11 . 1 }OA

III VI' .4 I.ItI .1

(:1(A1'11 11.11 4. 'IBA 1. 'I 14.1)A

411 Iwo! Ha III 1...1 I vt't ;I /1. () 4). t`ok 2. /

1'1 4.0 16. 2',)A I .11 ().(18,1/4

2 .1) 2.44 .1) 1,44

IC:11 01414'4' Al' I It 1. 1 2.24A .1

SUM x '1'1 2.9 I . /BA .0 1SUM X '12 I. .0 <I .0 <1

DIFF X 'I'I. .3 I . 22 .2 1

DIFF X 12 .0 .1.

GRAPH X Ti .0 .0GRAPH X '['2 .1 .4 1.53

Residual 120 29.5 31.4

.05

.WI I1.!.1t. .....,i i 1 .iii.I . t Ii .1

I ht.; I .II 1.t. I I ti . ,I, I I I; 1.14" .. H. I l 13,,1% 11 I II

A...:1...,1 p.,,,11,_,t., 111.w ILI 1 I i It II.IL:Al L I 1,,,,, ,,,11 IL". i i, i, IL.' . .1 , I 1, ,

,

III (110 CI III 111111ll,t1 I AI 1.11:1 I i C:31 .111t1 *,11 hi: I I

II 110 tit I I 0:11

lilt III t I I LI, I 71 1111411 L!.I l "I I. sif I It 11 I tit, c I ti I ht.,

ImmvdInto iinnt(cI And v41 IAnAc, In 1110 doInvod

Thetiv Iho mcAn dIIIotoinctrs IdonIIIIod In IAhIn

VE And FE Ahowed higher Immodtato outcomel (14n did NIN: Itlioton IA

hotwoon VF. And r. were not lignill Ant . In conllaat, on tho dlayed

11w1 t1 1 4I, MIN lIwwvd .1 highor Average than did VI'. and rr.

Inter:14114mA wery toatod in the general(:'Ott modol, then, nnatand

ardtzed rogronalon cootticionta within each tloatment wort' plottod

grAphivaiiy tot. itorproto,tion, !;IIM X 11.0AiIIWIlt lutel'Ac1 1011 war{

statistically significant on the immediate posttest, but not on the

delayed posttest. This interaction accounted for 2.97. of the hmnediate

posttest variance; it is shown graphically in Figure 1. The relative

advantage of high ability students was most pronounced in MIN. In other

words, VE and FE appeared particularly helpful for low ability students,

reducing the difference between them and high ability students. There

were smaller treatment differences at the mean and reduced ATIs on the

delayed posttest.

Part Score Analyses

Verbal items. The results of the generalized regression analyses

of verbal outcome measures appear in Table 7. Again, SUM accounted for

24

I), 1

i I

lJ

1.

!'l

1(1

0 I l _1 1 I _1

-4.0 1.0 .2.0 1.0 0 1.0 2. 1.0 4.0

YIN

!t1

0 1 I 1

4.0 1.0 '1.0 1.0 o 1.0 1.0 1A1 4.0

ligury I. Relation of Total Posttest Scoren to SUM,with Unatandardized Regression CoefficientsShown in rarentheses.

IIM

Table 7

Summary of Stepwise Regression of Verbal Items

Immediate Posttest Delayed Posttest

Variable d.f. % VarianceAccounted For

F - ratio% VarianceAccounted For

F - ratio

Full Model 11 57.5 14.74* 40.4 7.40*

Aptitude Main Effects 3 41.7 39.22* 34.6 23.23*

SUM 1 37.1 104.68* 34.0 68.48*

DIFF 1 .0 <1 .2 <1

GRAPH 1 4.6 12.98* .4 <1

Treatment Main Effects 2 10.0 14.11* 2.9 2.92

Ti 1 2.8 7.90* 2.9 5.84*

T2 1 7.2 20.31* .0 <1

First-Order ATI 6 5.8 2.73* 2.8 <1

SUM X Tl 1 3.4 9.60* .0 <1

SUM X T2 1 1.3 3.67 .1 <1

DIFF X Ti 1 .7 1.98 .0 <1

DIFF X T2 1 .0 <1 .0 <1

GRAPH X Tl 1 .1 <1 .4 <1

GRAPH X T2 1 .3 <1 2.3 4.63*

Residual 120 42.5 -- 59.6 --

*P. < .05

the largest proportion of explained variance in each posttest. GR.=

accounted for a significant proportion of variance in the immediate

posttest, accounting for 4.6% of the variance in it. Students with

higher aptitude scores had higher outcome scores. DIFF was never signi-

ficant.

Treatment main effects correspond to the mean differences shown

previously. On the immediate posttest, treatment main effects accounted

for 10.0% of the variance; VE was superior to MIN and FE. Treatment main

effects accounted for 2.9% of the variance in the delayed posttest, with

MIN superior to \ and FE.

First-order ATI accounted for 5.8% of the variance in the immediate

posttest; ATI with SUM accounted for most of this variance. Figure 2

shows that VE was particularly helpful for low ability students.

The only significant ATI on the delayed posttest was between GRAPH

and treatment. As shown in Figure 3, only in FE did students with high GRAPH

scores outperform students with low GRAPH scores.

Figural Items. Table 8 presents the results of the generalized

regression analyses for figural items. As before, SUM and GRAPH accounted

for a significant proportion of the variance on both the immediate and

delayed posttests. DIFF was not significant, accounting for only .5% of

the immediate posttest variance and .0% of the delayed posttest variance.

Treatment main effects accounted for 6.6% of the variance on the

immediate posttest and 6.0% of the variance on the delayed posttest.

Thus, on the immediate posttest, VE and FE were superior to MIN, on

average. FE had a slight advantage over VE. In contrast, on the delayed

posttest, both MIN and VE were superior to FE.

27

15

10

0

-4.0 -3.0 -2.0 -1.0 0 1.0 2.0 3.0 4.0

SUM

15

0-4.0 -3.0 -2.0

Figure 2. Relation of Verbal Items to SUM, withUnstandardized Regression CoefficientsShown in Parentheses.

jUE'

-1.0 0

SUM

1.0 2.0 3.0 4.0

VE (.04)

MIN (.12)

FE (.13)

0 5 10 15 20

GRAPH

25 30

15

f-cn

10

FW

0

5

0

0 5 10 15 20 25 30

Figure 3. Relation of Verbal Items to GRAPH withUnstandardized Regression CoefficientsShown in Parentheses.

A I1

GRAPH

Table 8

Summary of Stepwise Regression of Figural Items

Immediate Posttest elayed Posttest

Variable d.f.% VarianceAccounted For

F - ratioVariance

Accounted ForF - ratio

Full Model 11 54.3 12.94* 62.2 17.96*

Aptitude Main Effects 3 43.3 37.86* 54.2 57.45*

SUM 1 35.7 93.65* 49.9 158.66*

DIFF .5 1.31 .0 <1

GRAPH 1 7.1 18.62* 4.3 13.67*

Treatment Main Effects 2 6.6 8.66* 6.0 9.54*

T1 1 5.1 13.38* 2.9 9.22*

T2 1 1.5 3.93* 3.1 9.86*

First-Order ATI 6 4.3 1.88 2.0 1.06

SUM X Ti 1 .8 2.10 .0 <1

SUM X T2 1 1.9 4.98* .0 <1

DIFF X Ti 1 .4 1.05 .6 1.91

DIFF X T2 1 .o <1 .0 <1

GRAPH X Ti 1 .1 <1 1.4 4.45*

GRAPH X T2 1 1.1 2.89 .0 <1

Residual 120 45.7 37.8

*2. < .05

The SUM X treatment interaction was, again, significant on the

immediate and not on the delayed posttest. In Figure 4, the irmediate

regression slope on SUM was shallower in FE than in MIN and VE. FE was

particularly helpful to low ability students in reducing differences

between them and high ability students. The mean disadvantage on the

delayed posttest for students in FE can also be seen.

Interactions with GRAPH accounted for 1.2% of the variance in the

immediate posttest, and 1.4% of the variance in the delayed posttest.

While not significant in the immediate posttest, the interaction suggested

that FE reduced the advantage of students with high GRAPH scores. On

the delayed posttest, both VE and FE reduced the advantage of students

with high GRAPH scores. These relations are shown in Figure 5.

Probleas. As with all other dependent variables, SUM accounted for

the largest proportion of explained variance in the problems on both the

immediate and delayed posttests (see Table 9). Although GRAPH was not

a statistically significant predictor of the immediate posttest, it

accounted for 1.3% of its variance, and did account for a significant

proportion of variance (4.9%) on the delayed posttest. Again, the effects

of DIFF were small. No treatment main effects were significant, and the

only significant ATI was, again, with SUM on the immediate posttest. As

shown in Figure 6, differences between high and low ability students were

greatest in MIN.

Summary of Regression Analyses

SUM accounted for the vast majority of variance in all dependent

measures, and GRAPH accounted for significant proportions of variance in

most. Again, because GRAPH and SUM were correlated, and because SUM was

entered into the regression analyses before GRAPH, effects associated

31

15

0-4.0 -3.0 -2.0 -1.0 0 1.0

SUM

2.0 3.0 4.0

15

Hy

HW

OI... 10

5

FE (.94)

0

-4.0 -3.0 -2.0 -1.0 0 1.0 2.0 3.0 4.0

SUM

Figure 4. Relation of Figural Items to SUM, withUnstandardized Regression CoefficientsShcwn in Parentheses.

A "16

15 15

10

5

FE (.04) MIN (.27)

MIN (.16)

10

5

0 0

10 15 20 25 30

GRAPH

VE (.09)

FE (.10)

0 5 10 15 20 25 30

GRAPH

Figure 5. Relation of Figural Items to GRAPH, withUnstandardized Regression CoefficientsShown in Parentheses.

43

Table 9

Summary of Stepwise Regression of Problems

Immediate Posttest Delayed Posttest

Variable d.f.% VarianceAccounted For

F - ratio% VarianceAccounted For

F - ratio

Full Model 11 45.8 9.21* 58.2 15.21*

Aptitude Main Effects 3 42.0 30.98* 56.3 53.64*

SUM 39.9 88.28* 51.2 147.12*DIFF 1 .8 1.77 .2 <1GRAPH 1.3 2.88 4.9 14.08*

Treatment Main Effects 2 1.0 1.11 .2 <1

Tl 1 .8 1.77 .0 <1T2 i .2 <1 .2 <1

-First-Order ATI 6 2.9 1.07 1.9 <1

SUM X Ti 1 2.1 4.65* .2 <1SUM X T2 1 .1 <1 .3 <1DIFF X Ti 1 .0 <1 .0 <1DIVE X T2 1 .1 <1 .9 2.59GRAPH X T1 1 .5 1.11 14 1.15GRAPH X T2 1 .1 <1 .1 <1

Residual 120 54.2 41.8

*2.< .05

0

-4.0 -3.0 -2.0 -1.0 0 1.0 2.0 3.0 4.0

SUM

0

-4.0 -3.0 -2.0 -1.0 0 1.0 2.0 3.0

SUM

Figure 6. Relation of Problems to SUM, withUnstandardized. Regression CoefficientsShown in Parentheses.

with GRAPH reflect its specific variance, not variance shared with sun.

The differential-ability hypothesis, tested by DIFF was never significant.

Treatment main effects were significant for the total, verbal, and

figural scores on both posttests. The immediate posttest showed a gen-

eral advantage for VE and FE over MIN. VE was most advantageous on

verbal items, FE on figural items. But this trend was reversed on the

delayed posttest where students in MIN outperformed those in VE and FE.

In fact, the lowest mean figural part score occurred in FE.

All significant ATI on the immediate posttest involved general

ability (SUM); VE and FE reduced the advantage of high ability students.

This advantage was reduced most in VE on verbal items and in FE on figural

items.

Similar relations were not found on the delayed posttest. High

ability students continued to outperform low ability students on the

delayed posttest; the relative advantages for students in VE and FE were

not retained over time. Significant ATI were obtained only with GRAPH.

Thus, in this study, instruction that was most effective for im-

mediate learning was not most effective in the long run. ATI effects

suggested that this shift may have come primarily from low ability students

who did not retain the additional information that enhanced immediate

learning.

36

CHAPTER 4

SUMMARY AND CONCLUSIONS

The present study examined the effects of verbal and figural sup-

71enents on learning, and their relation to general abi-ity, Gc and

Gfv, and a specific graph-processing test. This chapter summarizes

prior research and the procedures and results of the present study.

Implications for future research and educational practice are discussed.

The Research Problem

Although numerous studies have investigated interactions between

aptitude and verbal and figural instructional supplements, few consistent

relations have been established. In some studies, the regression of

outcome on aptitude was steeper when aptitude and instructional condi-

tion were matched; in others, the regression was shallower. Some studies

obtained similar regression slopes. These relations varied, in part,

as a function of the delay between instruction and the posttest. Incon-

sistencies also resulted from not specifying aptitude and treatment in

sufficient detail or considering all the ways they might be matched.

The Present Research

The present study compared the effects of minimal instruction,

instruction elaborated with verbal supplements, and instruction elaborated

with figural supplements. Aptitude was represented by a Gc composite,

a Gfv composite, and a graph-processing test. The Gc and Gfv composites

were summed to indicate general ability and their difference was used

to investigate their differential impact. Immediate and delayed outcome

measures included verbal items, figural items,ard froblems that could be

solved either verbally or figurally. Learning was described as a function

of aptitude and instructional material.

37

t- 0

The Effects of General Ability

On the immediate posttest, students in VE and FE did better than

students in MIN, suggesting that the elaboration provided in these con-

ditions helped students learn. Significant ATI suggested that the elabo-

ration was particularly useful to low ability students. High ability

students did as well or better in MIN. Thus, the regression of achieve-

ment on general ability was steepest in MIN and reduced in VE and FE.

Partitioning of the total test score by item type indicated that

VE was particularly helpful on verbal items and FE was particularly helpful

on figural items. Again, significant ATI indicated that these treatments

were particularly helpful to low ability students. Hence, the regression

of verbal items on general ability was least steep in VE; the regression

of figural items on general ability was least steep in FE.

Examination of, learning outcomes on retention, however, led to

strikingly different conclusions. While students in MIN were worst on

average achievement on the immediate posttest, they peiformed best on

the delayed test.

VE and FE provided more information to learners through additional

explanations and examples. MIN required students to provide this infor-

,mation for themselves, thereby demanding more active work from learners.

More able students, capable of doing it, did equally well in MIN as in

VE and FE. Less able students that could not generate that information

for themselves benefitted from the assistance. The gains were short-lived,

however. Active mental work, necessary in MIN, appeared to aid retention.

Hence, there cas a greater decline in performance in VE and FE than in

MIN. This contention was further supported by the observation that losses

38

were greatest when the assistance was most direct. That is, lossos on

verbal items were greatest in VE; losses on figural items were greatest

in FE.

The Differential Effect of Gc and Gfv

The differential impact of Gc and Gfv as measured in this study,

did not enter differently into outcome on aptitude relations. This may

be due, in part, to a failure to adequately distinguish Gc from Gfv.

That is, measures of Gc and Gfv shared a considerable proportion of

variance. Reducing that overlap might increase the chance of detecting

differences in their impact. Thus, future research in this area must

strive to do this.

The Effect of GRAPH

The instructional materials in this study used many graphic displays.

Therefore, GRAPH was included as a specific-ability measure. Sianificant'

main effects were associated with GRAPH at both testings, even after account-

ing for the effects of general ability. As with general ability, students

with higher aptitude scores did better. Thus, learning outcomes were not

fully described by the effects of general ability.

Conclusions and Implications

This study provided evidence that neither aptitude nor instructional

treatment alone can fully describe learning outcomes. Interactions between

them exist and can be demonstrated. Further, instructional supplements,

whether verbal or figural, can be effective in filling-in for students

weaknesses and reducing differences between high and low ability students.

Such supplements, however, must be used with caution. Reducing the

difficulty of instructional materials may indeed enhance immediate learning,

39

but these advantages may be short-lived. In the present study, increasing

the difficulty of the work required for initial learning appeared to in-

crease retention. The benefits in immediate learning must be weighed with

the need to ensure that information is retained.

The implications for educational practice are clear. The present

study indicated that instruction that enhances immediate learning is not

necessarily best for retention. Ultimately, educators must be concerned

with how much information is retained and not limit their concerns to

immediate outcomes. Thus, not only must achievement be assessed at more

than one point in time, curricula must be developed to promote long-term

learning. The current emphasis on testing after only short delays should

be reconsidered.

Additional research is necessary to confirm the findings of this

study and support these contentions. ATI research is one avenue for ex-

ploring this area, but it should be supplemented with more basic research

in information processing. Improved methods of distinguishing Gc from Gfv

are required to explore their differential impact on learning. These

methods may emerge as we gain a better process understanding of these

abilities through further research.

Finally, researchers should examine both immediate and delayed out-

comes, and attempt to identify instructional conditions likely to promote

long-term retention. At a minimum, delayed outcome measures may be added

to instructional research conducted in different contexts. Additional,

more directed research may probe more deeply'the relations among instruc-

tional materials, immediate learning, and retention. The present study

suggests that we cannot limit research to immediate outcomes if we are

truly interested in the long-term impact of instruction.

In conclusion, this study examined the relations among aptitude,

instruction,,and learning. While it provided data to help answer some

questions in this area, it raised many others that only future research

may resolve.

41

References

Allison, N. B. Learning parameters and human abilities. Unpublished

report, Educational. Testing Service, 1960.

Bracht, G. H. Experimental factors related to aptitude-treatment inter-

actions. Review of Educational Research, 1970, 40, 627-645.

Butcher, H. J. Human intelligence: Its nature and assessment. New York:

Harper and Row, 1968.

Carry, L. R. Interaction of visualization and general reasoning abilities

with instructional treatment in algebra. Unpublished doctoral disser-

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Cattell, R. B. Theory of fluid and crystallized intelligence: A critical

experiment. Journal of Educational Psychology, 1963, 54, 1-22.

Cattell, R. B. Abilities: Their structure, growth, and action. Boston:

Houghton Mifflin, 1971.

Cronbach, L. J. The two disciplines of scientific psychology. American

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Cronbach, L. J. and Snow, R. E. Aptitudes and instructional methods: A

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Eastman, P. M. The interaction of spatial visualization and general reas-

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Graham, F. K. and Kendall, B. S. Memory-For-Designs Test. Perceptual

Motor Skills, 1960, 11, 147-188.

42

Guilford, J. P. The nature of human intelligience. New York: McGraw-

Hill, 1967.

Gustafsson, J.-E. Verbal versus figural in aptitude-treatment interactions.

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Institute of Education, University of GOteborg, No. 36, 1974

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Educational Psychology, 1978, Vol. 70, No. 3, 319-323.

Lipsey, R. G. and Steiner, P. 0. Economics. New York: Harper and Row,

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3

t I I 1111 t Honristio modols for the generation of aptitude-treatment

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44

APPENDIX A

MEANS, STANDARD DEVIATIONS, AND CORRELATIONS BETWEEN APTITUDES-

Meas, St audit t'd 'ley t. , awl Cot' rt... I at lam.

of AptItude Measures In MIN (N " 44)

Variable Mean S.D. (I.) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

(I) Vocabulary Multiple-Choice 15.20 4.83 71 64 12 02 22 31 42 89 22 65 67

(2) Vocabulary F111-In 27.18 5.15 65 23 25 33 39 57 39 74 49

(1) 'Ferman Concept Mastery 30.64 5.29 49 41 49 69 68 87 00 20

(4) Copylng 32.36 9.09 58 60 44 32 85 68 -52

(5) Memory for Designs 17.16 L.90 37 15 24 26 63 51 -36

(6) Paper Folding 13.80 3.66 53 34 39 82 70 -42

(7) Advanced Progressive Matrices 23.59 5.15 66 53 75 74 -21

(8) GRAPH 22.11 5.95 63 55 68 09

(9) Cu .08 .99 49 86 51

(10) Gtv .06 .96 86 -50

(11) SUM .14 1.f9 01

(12) D1FF .02 .99

Note. Decimals omitted from correlations

MOi110, ;;iandard neviailoun. and Corielallona

61 Apt I t udc tioanuteu In VI.: (N ti/;

Variable Mean ;;. I). (I) ( 2) ( (4) (6) (/) (11) (9) (10) (II) (12)

(I) Vocabulary MullIplo-Choice 15.25 4.73 61 66 26 1.6 36 33 14 85 :16 ,68 52

(2) Vocabulary F111-in 26. 14 5.89 16 48 57 61 49 91 66 8/1 25

(1) Terman Concept Mastery 30.16 5./4 25 29 50 50 43 91 51 80 43

(4) Copying 31./5 9.03 33 62 57 54 37 81 67 -49

(5) Memory for De!;igns 16.98 2.02 34 40 51 30 66 54 -40

(6) Paper Folding 1.3.43 1.85 50 64 54 81 76 -31

(1) Advanced Progressive Matrices 24.43 5.99 62 55 81 77 -30

(8) GRAPH 23.48 5.51 41 75 65 -39

(9) Cc .01 1.03 58 89 44

(10) Cfv .03. 1.05 89 -48

(11) SUM .04 1.85 -02

(12) D1FF -.02 .96

Note. Decimals omitted from correlations

Means, :;tnudald nevintlonn, snd Cottelntios.,

tot 1\1.1 I I kith, 14. (II

V,1r I,IIile Mean !;.D. (I) ("7.) ( /) (4) (6) (1) (8) () ( 10) (11) (12)

O) Vocahnlary MnItIple.ChnIce 15.48 4.1? 1(1 /9 49 15 1/ 52 46 9'2 80 41

(7) VocahnIary FIII-In 2/.16 t9 17 I)1 50 I) ) Ysl /8

(0 Teman Concept Mastery 29.91 4.14 /19 21 1/ 9t) /9 40

(4) CopyIng 11.64 10.82 /1/4 40 53 11 48 /9 73 -'16

(5) Memory For Designs 11.14 2.01 26 59 38 20 73 54 -58

(h) Paper Folding 11.32 3.15 61 44 46 11 67 -29

(/) Advanced Progressive Matrices 25.52 5.25 56 56 87 82 -36

(8) CRAPH 23.05 4.99 56 54 63 00

(0) Gc .05 .97 55 87 44

(10) Gfv -.01 1.02 88 -51

(11) SUM .04 1.75 -05

(12) DiFF .07 .95

Nolo. Decimals omitted from correlations I I'

I X It

POSTTI LAT 1

49

V:11 I

1111114'11 1,11 a 11 1. ,1

I 1 1. 1 1

Iii) ! 1..11 I 1.11

11 I It,111 I 1,,i I

( 7i) l'i ,I) I

I

NI)t. 4. III.,- OW It t 141 I I (.in r 1,1 1 4 IA( I ow; .

1(cl 1.111 lit( I .11)p.11 III 1114 111.1111 ti

I

I t

i

t, I

it'.

',/

Posttest. Correlations in MIN (N =

Variable (1) (2) (3) (4) (5)

Immediate Posttest

(1) Total Score 86 89 84 92

(2) Verbal. Total 66 56 87

(3) Figural Total 64. 80

(4) Problems

belayed Posttest

(5) Total Score

(6) Verbal Total

(7) Figural. Total.

(8) Problems

70

Note. Decimals omitted from correlations.

44)

(6) (7) (8)

75 81 82

75 73 78

61 81 62

57 56 71

82 88 89

56 65

67

Variable

Posttest Correlations in VE (N = 44)

Immediate Posttest

(1) Total Score

(2) Verbal 'Total

(3) Figural Total

(4) Problems

Delayed Posttest

(5) Total Score

(6) Verbal Total

(7) Figural Total

(8) Problems

0 (2) (3) (4) (5) (6) (7) (8)

75

-

86

48

-

78

40

48

-

87

65

78

63

69

65

59

42

87

-

78

50

78

54

93

76

83

61

68

71

84

58

65

Note. Decimals omitted from correlations.

Variabl

Ineuediate

(1) To

(2) Ve

(3) Fi

(4) Pr

Delayed Po

(1) To

(2) Ve

(3) Fi

(4) Pr

Posttest Correlations in FE (N = 44)

(1) (2) (3) (4) (5) (6) (7) (8)

'osttest

:al Score 81 72 8(1 88 71 76 75

:bal. Total 41 44 71 67 60 54

;oral Total 36 67 44 70 54

)blems

ittest

67 54 50 66

Ca 1 Score 80 88 84

r b a 1 Total - 57 50

;oral Total 62

)blems

Note. Decimals omitted from correlations.

APPENDIX C

CORRELATIONS BETWEEN APTITUDE AND OUTCOME

Vorabulai

Vocabulat

Turman Cc

Copying

Memory (

Paper Fo

Advanced

GRAPH

Cc

Gtv

SUM

NIT

Correlations Between Aptitude and Outcome

in Total Sample (N = 132)

Immediate Posttest Delayed Posttest

Total Verbal Figural Prob- Total Verbal Figural Prob-Score Total Total lems Score Total Total . lems

-y Multiple Choice 52 41 39 48 51 39 44 49

-y Fill-in 63 !(.) Yi 54 (6 53 513 59

,ncept i!astery 6R 57 c7 69 49 63 65

41 40 26 35 46 30 44 42

)r Designs 40 40 35 21 42 36 35 38

ding 49 34 36 49 54 36 53 49

Progressive Matrices 64 51 51 51 65 49 59 58

66 56 58 49 65 42 61 63

69 53 56 60 70 53 62 65

63 54 49 51 68 49 62 61

75 61 60 63 78 58 71 72

05 -02 06 08 01 03 -02 03

Note. Decimals omitted from correlations

Vocabulary h

Vocabulary I

Terman Conc.

Copying

Memory for

Paper FoldirIn

Advanced Pr(

GRAPH

Gc

Gfv

SUM

DIFF

Correlations Between Aptitude and Outcome

in MIN (N = 44)

Immediate Posttest Delayed Posttest

TotalScore

VerbalTotal

FiguralTotal

Prob-lems

TotalScore

VerbalTotal

FiguralTotal

Prob-lems

lultiple Choce 53 42 40 56 47 34 38 50

'ill-in 62 52 53 57 62 44 53 64

pt Mastery 79 68 67 70 73 51 64 74

50 57 32 40 45 24 47 44

)esigns 49 60 41 23 50 50 40 40

ig 48 39 40 47 48 28 48 48

)gressive Matrices 68 52 63 62 60 35 59 59

69 63 65 50 71 38 76 65

73 61 60 69 69 49 58 71

70 67 57 57 66 I:4 63 62

83. 74 68 73 78 54 70 77

04 05 04 13 03 05 04 09

Note. Decimals omitted from correlations.

Correlations Between Aptitude and Outcome

in VE (N = 44)

Immediate Posttest Delayed Posttest

TotalScore

VerbalTotal

FiguralTotal

Prob-lems

TotalScore

VerbalTotal

FiguralTotal

Prob-- lems

Vocabulary Multiple Choice 45 32 39 35 50 48 43 43

Vocabulary Fill-In 74 50 64 62 76 71 67 65

Terman Concept Mastery 63 38 59 51 71 54 68 65

COpying 44 30 43 31 53 52 50 39

Memory for Designs 38 21 46 19 38 28 41 29

Paper Folding 54 33 39 58 62 47 63 52

Advanced Progressive Matrices 64 51 61 40 71 67 67 55

GRAPH 64 33 64 47 62 42 61 58

Gc 68 45 61 56 75 65 67 65

Gfv 66 44 61 49 73 63 72 //

57

SUM 75 50 69 59 83 72 78 69

DIFF 02 00 -02 06 00 01 -07 07

Note. Decimals omitted from correlations.

Vocal

Vocal

Term

Copy

Memo'

Pape

Adva

(;RAP

Cc

Ctv

SLIM

NIT

Correlations Between Aptitude and Outcome

in FE (N = 44)

Immediate Posttest Delayed Posttest

TotalScore

VerbalTotal

FiguralTotal

Prob-lens

TotalScore

VerbalTotal

FiguralTotal

Prob-lems

milary Multiple Choice 66 57 /6 50 60 40 56 54

)ulary Fill-in 71 66 51 48 65 48 6/: 51

in Concept Mastery 71 59 55 51 63 44 58 57

Lug 38 39 08 37 41 20 40 42

ry for Designs 40 47 20 23 41 30 29 44

r Folding 55 43 40 45 54 35 49 50

Iced Progressive Matrices 64 58 38 52 67 51 . 56 61

I65 65 19 46 70 58 54 66

76 68 55 55 70 49 66 59

62 60 33 50 64 43 56 63

79 72 50 60 76 52 69 70

12 05 22 03 03 04 08 -07

Note. Decimals omitted from correlations.

....au, as .Nlubr ',Mee-Muer ju 140,,

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