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1-SSESSMENT OF ABBREVIATION METHODS FOR

" "--- AUTOMATED TACTICAL__SYSTEMS,.

• ' ".Franklin oses an !.awrence M./Potash

x3~ I " 1)f ;

• HUMAN FACTORS TECHNICAL AREA

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_ L.- /,-/--e/ / D C2

A0A:

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K!: JU. S. Army X Research Institute for the Behavioral and So I Sciences

Aug•*, 79- .

Approved for public relo ,e; distribution unlimited. -

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FOR THE BEHAVIORAL AND SOCIAL SCIENCES

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JOSEPH ZEIDNER Colonel, U S Army Technical Director Commender

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Technical Report 398

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ASSESSMENT OF ABBREVIATION METHCDS FOR __

AUTOMATED TACTICAL SYSTEMS _____________

6. PERFORMING ORG. REPORT NUM3ER

7. AUTHOR(@) S. CONTRACT OR GRANT NUMBER(.)

Franklin L. Moses and Lawrence M. Potash

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U.S. Army Research Institute for the BeV'aviora{ AREA & WORK UNIT NUMBERS

and Social Sciences 2Q163743A774

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Abbreviations Data element dictionary

Data retrieval Tactical operations system (TOS) iNatural language Automated data systems

4 Que•ry language

26, A ACT- (omWAse m .evemw eb n0ee60uy a" Ideoftf bY block ratbee) I •" Alternative methods of producing abbreviations of single words for use

in automated military systems were empirically evaluated. Each of 50 enlisted

men performed three tasks designed to assess five different abbreviation

methods including two versions of truncation, two versions of contraction,

and one procedure based on current Army practice. In the first four methods,

abbreviation length was directly relateC to word length. In Task A, partici6 pants used a 10-point scale to rate preference for abbreviations for each of

(Continued)

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60 terms. Thirty of these terms were repeated in Task B; the other 30, in

Task C. Task B required participants to decode 60 abbreviations into

their original terms. Finally, Task C asked participants to encode (i.e.,

generate) a meaningful abbreviation for each of 60 terms. Results showed

that abbreviations produced using simple truncation were consistently preferred, easily decoded, and frequently used for encoding terms. Scores

for abbreviations from current Army practice were among the lowst except

in Task C (encoding). Experience with abbreviations in Task AI(preference)

made decoding of identical abbreviations nignificantly easier in Task B,

but did not affect the abbreviations encoded by participants in Task C.

Simple truncation is the method suggested to pxoduce good single wore abbreviations quickly and to reduce the errors and the time requirements

for user interactions with battlefield automated systems.

'414

4-4 f "71 

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Unls4fe

SEURT CLSIICTO OFTISPG(Wo Dd ntI
Technical Report 398

ASSESSMENT OF ABBREVIATION METHODS FOR

AUTOMATED TACTICAL SYSTEMS

.ranklin L. Moses and Lawrence M. Potash

Raymond C. Sidorsky, Team Chief

Submitted by:

Edgar M. Johnson, Chief

HUMAN FACTORS TECHNICAL AREA

Approved by:

Frank J. Harris, Acting Director

ORGANIZATIONS AND SYSTEMS

RESEARCH LABORATORY

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

5001 Eisenhower Avenue, Alexandria, Virginia 22333

Office, Deputy Chief of Staff for Personnel

Department of the Army

August 1979

Army Project Number Information Processing

20163743A774 and Display

Approved for public release, distribution unlimited.

44"'
ARI Research Reports and Technical Reports are intended for sponsors of

R&D tasks and for other 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.

ii

* p -_

o"S

€~
FOREWORD

The Human Factors Technical Area is concerned with improving man/

machine systems to acquire, transmit, process, disseminate, and utilize

information from the increasringly complex battlefield. The research is

fozused on the interface problems and interactions within command and

contrci centers and is concerned with such areas as topographic products

and procedures, tactical symbology, user-oriented systems, information

management, staff operations and procedures, and sensor systems integration and utilization.

One area of special research int-erest involves the design and evaluation of procedures to increase efficiency and accuracy of user- *

computer interactions. Advances in user-approachable systems would reduce errors, increase input rates, and provide for well-structured

outputs to help realize the potential benefits of automation for command

and control applications. The present research evaluated ilternative

methods for creating abbreviations of military terms. It is part of a

continuing effort to provide the command staff with efficient vocabularies, message structures, and "natural" language elements for interacting with battlefield automated systems. Such research suggests techniques and methods which •:an be incorporated into plans for Army-wide

automated systems.

Research on characteristics of user-approachable systems is conducted as an in-house effort augmented by contracts with organizations

selected for their specialized capabilities and facilities. These efforts are responsive to requirements of Army Project 2Q163743A774 and

to speciaW requirements of the U.S. Army Combined Arms Combat Development

Activity, Fort Leavenworth, Kans. Special requirements are contained in

Human Resource Need 78-149, "Interactive Procedures for Data Inputting,

Organization, Retrieval and Purge."

SJSEPH Z ER

echnical Director

v
ASSESSmi.NT OF ABBREVIATION METHODS FOR AUTOMATED TACTICAL SYSTEMS

BRIEF

Requirement:

To evaluate alternative methods for producing abbreviations of

single words for use as data element codes in battlefield automated

systems.

Procedure:

Each of 50 enlisted men (E4 and above) performed three tasks designed to assess five different abbreviation methods: two versions of

truncation, two versions of contraction, and one procedure based on

current 

was directly 

Army practice. 

related to word 

In the 

length. 

first four 

For 

methods, 

all research 

abbreviation 

tasks, 120 

length 

single

1

words and their Army abbreviations were selected from the 1977 Army

Tactical Data Systems Standard Data Element Dictionary (DED) intended

for use with automated systems.

i In Task A, participants used a 10-point scale to rate preference

for abbreviations for each of 60 terms. Thirty of these terms were

repeated in Task B and the other 30 in Task C to determine if such

minimal experience would influence results. Task B required participants to decode 60 abbreviations into their original terms. Task C

asked participants to encode (i.e., generate) a meaningful abbreviation

for each of 60 terms. Since the context of an abbreviation can provide

clues about its meaning, half of the participants in Tasks B and C were

told the DED category of each item presented.

Results:

Single word abbreviations produced using simple truncation were

consistently pref-erred, easily decoded, and frequently used for encoding terms. Scores for abbreviations from the DED were among the lowest

except in Task C (encoding). There was no clear-cut second-ranking

method although both forms of contraction did well. Experience with

abbreviations in Task A (preference) made decoding of identical abbreviations significantly easier in Task B, but did not affect the abbreviations encoded by participants in Task C. There was no effect on performance in Task B or in Task C of knowing the context (i.e., DED

category) for items in the research.

vii-".- ' " - -- -. -

MC~EDIfiG PAGS 1ILJ.K

050 0 JIM•
Utilization of Findings:

Simple truncation is the suggested method for quickly producing

single word abbreviations which are preferred and easily decodable.

With this method, battlefield system designers should produce good data

element codes. In addition, such abbreviations presumably should benefit users by reducing input time and errors in interactions with battlefield systems. Overall, the abbreviations produced by simple t.runcation

are not intended to replace commonly accepted abbreviations and are not

likely to be judged acceptable in all cases.

viii

- - - ----4-FT-
ASSESSMENT OF ABBREVIATION METHODS FOR AUTOMATED TACTICAL SYSTEMS

CONTENTS

Page

BACKGROUND ............................ ........................... 1

OBJECTIVE ............................ ........................... 2

METHOD ............................. .............................. 3

Participants ........................ ......................... 3

Task ............................ ............................. 3

Materials ....................... ........................... 3

PROCEDURE ........................... ............................ 4

Task A: Preference ..................... ...................... 5

Task B: Decoding ...................... ....................... 5

Task C: Encoding . . . .................... 5

RESULTS ............................ ............................. 7

Task A ........................... ............................ 7

Task B .......................... ............................ 8

Task C .......................... ............................ 8

DISCUSSION ...................... ............................ 12

Alternative Abbreviations ............ ................... 12

User Experience ............... ........................ .. 13

SUMMARY AND CONCLUSIONS .............. ..................... .14

REFERENCES ...................... ............................ 15

APPENDIX A. SUMMAZY OF ABBREVIATION METHODS .............. .. 17

B. RESEARCH TERMS RANDOMIZED FOR TESTING FROM THE

ARTADS STANDARD DATA ELEMENT DICTIONARY ....... .. 19

C. INSTRUCTIONS TO PARTICIPANTS .... ............ 23

D. ANALYSIS OF VARIANCE TABLES .... ............. 29

DISTRIBUTION ................... ........................... 33

ix

L"

.g. .
CONTENTS (Continued)

Page

LIST OF TABLES

Table 1. Preference ratings for the .Cive abbreviation methods 7

2. Correctly decoded abbreviations for each of five

methods (iiberal scozing) ...... ................. 9

3. Correctly decoded abbreviations for each of five

methods (strict scoring) ............. ................ 10

4. Participant-produced abbreviations that matched

abbreviations produced by each of the five methods . . . 11

D-1. Analv3is of variance for acceptability ratings of

abbreviation methods ......... .................. .. 29

D-2. Analysis of variance for number of abbreviations

correctly decoded using liberal scoring .............. 30

D-3. Analysis of variance for number of abbreviations

correctly decoded using strict scoring ........... ... 31

D-4. Analysis of variance for number of abbreviations

that conform to abbreviations produced by the

five methods ............. ...................... ... 32

LIST OF FIGURES

Figure 1. Modified Latin Square design for Task B (decoding

abbreviations) .......... ...................... 6

x
ASSESSMENT OF ABBREVIATION METHODS FOR AUTOMATED

TACTICAL SYSTEMS

The use of abbreviations as datL ele.ment codes in battlefield

automated systems reduces the amount of display area required for items

and is expected to decrease input time and errors. However, the multitude of acronyms and abbreviations available in Army systems confuses

users. A good abbreviation should be quickly and easily ,iscriminated

from other abbreviations in a particular system, and it should be easily

decoded and remembered. In addition, it should be compatible with a

variety of different system configurations to facilitate implementation.

The present effort was designed to determine standard methods for creating abbreviations that have clear and inmediate associations with their

original words.

The design and evaluation of procedures for creating abbreviations

is part of implementing the Army's program to standardize data elements

and codes (AR 18-10). The fundamental purpose of this program is to

facilitate integration of systezs and direct computer-to-computer com- t

munications. One of the efforts at standardization is in Xrmy Tactical r

Data Systems (ARTADS). A Standard Data Element Dictionary (DED) has

been developed in the broad area of tactical command/control to reflect

needs of the Tactical Operable Segment Tactical Operations SysteJ: (TOS 2 )

the All Source Analysis System (ASAS), and the Tactical Fire Control

System (TACFIRE).l The 1977 DED was the source of terms for testing

in the current research.

BACKGROUND

A variety of methods are available for constructing abbreviations,

including use of acronyms, contractions, truncations, or some variation

of these (Barrett & Grems, 1960; Bourne & Ford, 1961b; Luhn, 1958;

Davidson, 1962; Hodge & Pennington, 1973). However, with but few exceptions (Hodge & Pennington, 1973; Nystrom & Gividen, 1978; Nawrocki,

1979), there is a lack of empirical data concerning methods that produce short forms for which both the short fcrm designating a word or

concept and the meaning are easily associated, learned, and remembered.

For example, consider the ranqA of differences among five abbreviations

for the term reinforcing: RNF, REINF, RINFO, RNFRC, and RIFCG. The

first reflects -urrent Army practice, and the others represent two

variations of truncation and two variations of contraction. Guidelines

are needed for choosing among such alternatives.

A recent and intensive effort called the TRADOC Data Element Standardi-

"zation Program was initiated in 1978 to develop standards for all tactical Battlefield Automated Systems (BAS).

I
Hodge and Pennington (1973) analyzed the ways people create abbreviations and their ability to correctly interpret abbreviations produced by others. Participants were asked to create abbreviations for

words varying in length from four to nine letters and to reconstruct

the original words from abbreviations previously produced by another

group. Results showed that (a) the percentage of letters used in an

abbreviation declined systematically with increasing word length, although the actual number of letters veed showed a moderate increase;

(b) rruncation was used more often than contraction with the longer

high frequency-of-usage words whereas the reverse tended to be the

case for the low frequency-of-usage words of any length; and (c) the

median number of different abbreviations increased systematically with

word length. At a minimum, the research by Hodge and Pennington gave

clues about the relationship among abbreviations, different word

lengths, and frequency of usage.

Nystrom and Gividen (1978) investigated the ease of learning different types of codes used to categorize input messages in an automated

system. Their results suggest that for message titles containing multiple words, the coding should be done with acronyms. In general, use of

arbitrary letters or words should be avoided.

Nawrocki (1979) investigated the accuracy of interpreting abbreviations created with alt,'taative abbreviation methods. He found no difference in the number of abbreviations correctly interpreted for a truncation method compared tt a contraction procedure that removed vowels.

However, such cnat'actions led to co:isiderably more spelling errors than

were caused by truncation. Truncation produced significantly more grammatical errors where the endings or tense of words were incorrect. In

terms of abbreviation lengths, procedures using fewer letters (i.e.,

greater "economy") resulted in poorer performance.

Clearly, a variety of suggestions exist for shortening single as

well as multiple word items. However, no generalizable recommendation

has emerged for methods which generate abbreviations that are preferred,

easily decoded, and used with minimal learning. Some abbreviation rules

may lead to forms which require constant looking up and, therefore, are

harder to use than the original terms. Other ru~es may be appropriate

for some items and not for others. For example, use of acronyms is

highly des.rable only when they are easily remembered and associated

with the items represented. Typically, logically compelling arguments

or personal choices are the primary basis for choosing among abbreviation methods. The present effort employed empirical measures to assist

in choosing among alternative methods for abbreviations of single words

OBJECTIVE

The oLjective was to evaluate the effectiveness of five abbreviation methoqs using three evaluation criteria. The first criterion,

preference, was used to assess general acceptance of different

2
abbreviation formats. Interpretation or decoding, the second criterion,

was used to determine how well abbreviations produced by different methods actually suggest the terms they represent. The third criterion,

encoding of abbreviations, determined which methods people naturally

to create ab breviations. In summary, the research Susegoal was to

identify abbreviation methods whose use with single words may gain easy

acceptance and may increase speed and accuracy for interactions with

tactical data bases.

METHOD

Participants

Participants were 50 military personne! .(E4 and above) who had diverse backgrounds. They were assigned to the Military District of Washington, D.C., and participated in the experiment as a group.

< Task

The experiment consisted of three tasks. In Task A, participants how well single word military terms were represented Sjudged by ab brevi-

•° ations generated using five different methods. Task B required participants to reconstruct military terms from abbreviations produced by the ,•

same five methods used in Task A. Finally, in Task C, participants

were instructed to generate an abbreviation for each military term

presented.

i

Materials

Five different methods used for generating abbreviations in

Tasks A and B were chosen from 12 possible candidate methods (Appendix A). The following methods were selected:

i. Data Element Dictionary (DED). Abbreviations taken directly

from the DED represent current Army practice and provide comparisons for abbreviations produced by the other four methods.

2. Simple Truncation. Starting from the right end of the word,

drop off letters u.,til the required word size is obtained

(Bourne & Ford, 1961ab).

3. Tr•ication/Second Letter Out. Automatically eliminate the

second character of the word counting from the left side.

Then use simple truncation (Bourne & Ford, 1961ab).

4. Contraction/Vowels Out. Keep the first character on the left,

remove vowels an d H, W, or Y (from right Sbut to left) until

• the correct number of letters is reached. Supplement the

L

• • : : • : * S__ , ! • •! •=
I -WV W W-:-*~~'-

method with simple truncation if nec,?ssary (modified from

Davidson, 1962).

5. Contraction/Frequent Letters Out. Keep the first charact.,r

and eliminate letters from right to left on the basis of their

freqzuency of occurrence in proper nAmes until the desired abbreviation length is reached. Highest frequency letters are

elimiuated first (Bourne & Ford, 1961a,b).

Each of the five methods was used to abbreviate 120 single word

terms (Appendix B) taken from the DE3D. Lzngths of DED abbreviations

had no consistent scheme, all other abbreviations were generated withi

4lengths varying according to guidelines empiric,lly generated by Hodge

and Pennington ,1973) as follows:

Number of .. tters Number of Letters

in Original 'Term in Abbreviation

8 or more 3 3

The abbreviations taken from the DED sometimes had a prefix letter

(e.g., "p" for personnel) so that an abbreviation could be even longer

than the original term. Overall, the DED scheme was as follows:

Range of Number

Number of Letters Mean Number of Letters of Letters in

in Original Term in Abbreviations Abbreviations

5 3.5 1-6

6-7 4.5 1-6

8 or more 4.9 1-7

The total number of terms in each word-length category follows:

Number of Letters

in Original Term Number of Terms

5 2

6-7 2197

8 or more 97

PROCEDURE

Participants were told that the research was aimed at evaluating

various ways to abbreviate military terms. The relationship of such

abbreviati3ns to computerized information systems and the importance

of having abbreviations that are easily recognized and interpreted was

explained. Illustrations were given to show how some abbreviations are

4
not as good as others. Instructions emphasized that no special training was required for completion of the task and that no individual

would be graded or evaluated. Participants read apecific instructions

(Appendix C) prior to working on each of the three parts of the research.

Task A: Preference

All participants in Task A used test materials containing the same

60 military tetms. Each term was followed by five abbreviations gener3ted using the five methods being evaluated. Parti.cipants were required

to use an 11-point scale for rating how well the abbreviations represented a T.articular term. On the scale, "0" was defined as "ansatisfactory," and "'0" was defined as "excellent." The presentation order

of abbreviations for each military term was determined by use of a

random number table.

Task B: Decoding

In this part of the research, participants were presented with 60

abbreviations generated using the five methods and were instructed to

write the original term for each of th.. abbreviations. Thirty of the

abbreviations were for terms used in Task A; the other 30 abbreviations

were for new terms (experience condition, previously seen versus not

previously seen). Each abbreviation representad a different term.

participants SAll did not see the same 60 abbreviations. For a given participant, each of the five abbreviation methods was used on

a different block of 12 terms, 6 terms previously seen and 6 new ones.

By using five gronps of particicpants, all possible combinations of the

five blocks of 12 terms using the five abbreviation methods were represented. Abbreviations representing the terms were randomly assigned to

the 60 positions so that abbreviations from a particular method would

be scattered and a "position effect" minimized. The same random order

was used for all groups. For 25 participants (5 per group), each abbreviation was accompanied by a cue to help in reconstructing the original term (cue condition). Cues consisted of military categories for

terms as specified in the DED (for example, the cue support mission

accompanied RNF, the abbreviation for reinforcing). In a parallel condition, the r(maining 25 participants had the same sets of abbreviations

but had no accompanying cues. The research design for Task B was a

modified Latin Square design (Figure 1).

Task C: Encoding

[ All participants in Task C were presented with 60 terms and were

instructed to generate one "best" abbreviation for each term. The

length of the abbreviation had to be three or more letters but less

than the total number of letters in the term being abbreviated, Thirty

5 .4
""~. 7////

/ // A AA

,/ / / / /1

3/

Y /

G2 BB B B

//

3 4 5

.- G Groups of five participants

B =Abbreviated terms previously seen (blocks of six)

B'= Abbr-eviated terms not previously seen (blocks of six)

Figure 1. Modified Latin Square design for Task B

(decoding abbreviations)

•-.

7 

6 0
of the terms had previously been used only in Task A; the remaining 30

terms had not been presented previously (experience condition). As in

Task B, the military categories for terms were specified for half of

the participants but not for the other half (cue condition).

RESULTS

The effectiveness of abbreviation procedures was assessed in three

ways: preference, decoding, and encoding measures. Since a different

research design was used for each of the three experimental tasks, the

results are presented most clearly in separate sections.

Task A

Preferences expressed in the form of numerical ratings were analyzed using a one-way analysis of variance (ANOVA) with the five abbreviation techniques as the main effect and participants as a replication factor. There was a statistically significant difference

(p < .01) among ratings for the different :echniques (Appendix D).

A Neuman-Keuls test of means showed that abbreviations produced by

simple truncation and by contraction with vowels removed were preferred

over abbreviations produced by all other techniques (Table 1). The

DED abbreviations and truncation/second letter out were statistically

less acceptable than any other method.

Table 1

Preference Ratings for the Five Abbreviation Methods

Mean

rating Method

J5.46 Contraction/vowels out

5.10 Simple truncation

4.25 Contraction/frequent letters out

3.48 Truncation/second letter out

3.12 DED

Note. Means which are significantly different from each

other, p < .01, are not bracketed together.

7
II

Task B

The number of abbreviations correctly decoded in Task B was determined using both liberal and strict scoring criteria. With liberal

scoring, some of the decoded terms which were counted as correct had

spelling errors or different endings from the intended terms. Decoded

terms counted as correct under strict scoring criteria were error free.

A five-factor ANOVA (based on the mQdified Latin Square design)

applied to liberal scores showed statistically significant differences

(p < .01) for abbreviation method, for experience with abbreviations

(seen, not previously seen), and among blocks of abbreviations

(Table D-2). The block factor is not of interest because of the

counterbalanced research design. Only two of the significant interactions merit mention. The Experience x Method interaction may suggest

that the relative decodability of abbreviations created by different

methods varied with experience. The Experience x Residual x Cue effect, while significant, was too small to be useful in data

interpretation.

Mean scores (Table 2) showed that previously seen abbreviations

(X[ 4.30) were more accurately decoded than abbreviations not previously

seen (W = '.72). Using the Neuman-Keuls test, the mean scores for abbreviation methods were compared for differences. Simple truncation

scored best in six of eight comparisons. It was better than all other

methods for not-previously-experienced abbreviations. For terms experienced earlier in the research, simple truncation scored better

than DED abbreviations and contraction/frequent letters out.

A five-factor ANOVA, parallel to the one just discussed, was applied to data scored by strict criteria (Table D-3). Only some of the

minor interactions differed from the earlier analysis using liberal

scoring criteria. A Neuman-Keuls test of mean scores (Table 3) for

the five abbreviation methods indicated that simple truncation and

contraction/frequent letters out were better than most of the other

methods for items not previously experienced. Once again, the DED

abbreviations tended to be the worst technique overall. The small

range of scores resulting from strict scoring perhaps limited the number of statistically significant findings.

Task C

Abbreviations produced by participants were scored for correspon- .

dence with abbreviations produced by the five methods used in earlier

tasks. A two-way ANOVA (Table D-4) showed significant differences

among the five methods (p < .01) and a significant Methods x Experience

interaction effect (p < .01). Data were collapsed across the cue/no

cue condition since no noticeable differences occurred. Similarly,

no differences in scores resulted from the use of liberal versus strict

scoring criteria defined in Task B's results. Table 4 shows mean scores

8
Table 2

Correctly Decoded Abbreviations for Each of

Five Methods (Liberdl Scoring)

Previously seen items Not previously seen items

Mean and Mean and

percentage percentage

Method decoded Method decoded

Simple truncation 4.66 (78%) Simple truncation 13.38 (56%)

Truncation/second Contraction/

letter out 4.54 (76%) frequent letters

C r iout 2. J (45%) Contraction/

vowels out 4.36 (73%) Truncation/second

letter out 2.58 (43%)

Contraction/

frequent letters DED 2.54 (42%) 4

out 4.14 (69%)

Contraction/

DED 3.82 (64%) vowels out 2.40 (40%)

Column mean 4.30 Column mean 2.72

Note. Means which are significantly different, p < .05, from each other

are not bracketed together.

.4

".4.. 44.." . . .. .• '• • • •':- m | !r • - : ' -
Table 3

Correctly Decoded Abbreviations for Each of

Five Methods (Strict Scoring)

(i

Previously seen items Not previously seen items

Mean and Mean and

percentage percentage

Method decoded Method decoded

Contraction/ Simple truncation 2.08 (35%)

frequent letters

out 3.60 (60%) Contraction/

frequent letters

Contraction/ out 2.02 (34%)

vowels out 3.58 (60%)

Truncation/second

Truncation/second letter out 1.64 (27%)

letter out 3.46 (58%)

Contraction/

Simple truncation 3.18 (53%) vowels out 1.54 (26%)

DED 2.86 (48%) DED 1.50 (25%)

Column mean 3.34 Column mean 1.76

Note. Means which are significantly different, p < .05, from each other

are not bracketed together.

j 110

Al.4 II 
Table 4

Participant-Produced Abbreviations That Matched Abbreviations

Produced by Each of the Five Methods

Previously seen items Not previously seen items

Mean and Mean and

percentage percentage

Method of matches Method of matches

Simple truncation 2.42 (40%) DED 1 3.14 (52%)

Contraction/ Simple truncation 2.dO (47%)

vowels out 2.34 (39%) iContraction/ ,

DED 2.30 (38%) vowels out (1.38 (23%)

Contraction/ Contraction,/ . (%

frequent letters frequent letters

ou1I.02 1.702 (17)t

out ot 1.02t

Truncation/second Truncation/second

letter out .22 (04%) letter out .08 (01%)

Column mean 1.66 Column mean 1.68

Note. Means which are significantly different, p < .05, from each other

are not bracketed together.

"A.,
for the five abbreviation methods and the two experience conditions.

A Neuman-Keuls test for differences among mean scores showed that participants most frequently generated abbreviations which matched those

produced by the DED or the simple truncation method. For previously

seen terms, the contraction/vowels out miethod also was frequently

matched. Overall, the DED approach scored well in Task C, but not in

the two earlier tasks.

DISCUSSAN

The results of this research strongly support simple truncation

to efficiently produce a high percentage of acceptable abbreviations

for use as data element codes in battlefield automated systems. In

contrast, the use of abbreviations from the 1977 ARTADS Data Element

Dictionary received very weak support. Participants not only preferred

abbreviations produced by simple truncation, but they decoded such abbreviations more accurately than those produced by other methods. Abbreviations from the DED were less preferred and less accurately decoded

than abbreviations generated by other methods. Even in the encoding

task, when participants frequently generated DED abbreviations, simple

truncation provided a comparable score. Clearly, simple truncation is

an effective abbreviation method. However, its utility should not

totally exclude the use of alternative methods or the influence of

user experience on choosing abbreviations.

Alternative Abbreviations

One way to interpret the research data is to consider how abbreviations produced by alternative methods could affect the accuracy of

information transfer. Task B, which required decoding, indicates how

many errors users are likely to make in understanding different abbreviations. For example, 14% more errors are likely with abbreviations

from the DED than with those produced by simple truncation. No method

unambiguously ranks second in error reduction. However, abbreviations

from the DED may cause as many as 9% more errors than abbreviations

produced by contraction/vowels out and 12% more errors than abbreviations generated by truncation/second letter out. These values fluctuate

for different tasks, but give some meaning to the range of performance "differences from using different abbreviation methods.

Some of the abbreviations produced by simple truncation will be

considered unreasonable by system designers and users. Although simple

truncation did well most consistently under research conditions, its

absolute success could have been better. The best results occurred in

decoding (Task B), where 78% of the abbreviations produced by simple

truncation were decoded correctly. Other abbreviations could be improved by avoiding simple truncation. When word endings such as "ed"

and "ing" are important, for example, Nawrocki (1979) found that truncation produces many ending errors compared to contraction. Sometimes,

12
traditional and tamiliar abbreviations from the DED may be best choices.

There is no substitute for good judgment in using alternative methods

as supplements to simple truncdtion for improving the overall quality

of a set of abbreviations. Reasonable alternatives would be both forms

of contraction, which scored well and are good competitors for simple

t:uncation. However, simple truncation should be accepted as the best

initial approach for creating most abbreviations.

The support for simple truncation in the current research is

reasonably compatible with other findings. Nawrocki's (1979) research

showed that truncation produced many good abbreviations, but did not

differ substantially from contraction using vowel removal. Bourne and

Ford (1961b) recommended simple truncation as a good method, although

they suggested that it might be improved by omitting the second letter

with its "weak discriminating power." The suggestion was tested explicitly in the current research (i.e., truncation/second letter out)

and did not produce better results than simple truncation. Finally,

Hodge and Pennington (1973) found that participants favored simple

truncation for abbreviating longer words (more than seven letters)

corresponding to word lengths used in the current work.

Thus, according to Hodge and Pennington (1973), length of terms

is a potentially important factor in choosing an appropriate abbreviation method. In the present experiment, the majority of terms tested

(81%) were more than seven letters long. Longer terms were selected

in part because they discriminate well among alternative abbreviation

methods. In addition, abbreviations are most important in long words

because they represent meaningful and obvious saving in the number of

letters used. Finding a good abbreviation method, such as simple truncation, for longer terms as well as for some shorter ones, should solve

many abbreviation problems.

User Experience

Users benefit from abbreviations which are easy to remember.

Therefore, one aspect of the research looked at the effect of experience on results. The learnability of abbreviations is addressed indirectly by preference judgments (Task A). Abbreviations which are

preferred are likely to be easier to remember. %.i a 10-point scale,

abbreviations from the DED were about 2 points less popular than abbreviations produced by simple truncation and contraction/vowels out.

User opinion should be considered in selecting abbreviations because

it can affect system acceptability.

In a more direct test of experience, abbreviations previously

seen in the preference test (Task A) were decoded in Task B more accurately than those which were not previously seen. An interesting

finding was that experience improved decoding scores for simple truncation, but not as much as it improved scores for other abbreviation

13
7 IT

methods. Even limited experience with abbreviations produced by different methods seems to reduce their statistical difference in a decoding task.

No specific effects of research experience were found on encoding

in Task C, which required the creation of abbreviations. However, the

high scores for DED abbreviations in only this task may be due to the

military background of all participants. Participants may have relied

on such "common" abbreviations when they were easier to create than potentially better alternatives. The only fair conclusion from the results is that DED abbreviations may be easily created. However, their

preference ratings (Task A) and decoding scores (Task B) are inferior

to other methods. Further work should be done to clarify the role

that prior experience and training can have in determining efficient

abbreviations for both single- and multiple-.word terms.

SUMMARY AND CONCLUSIONS

Simple truncation is an easy-to-use method that generates a high

proportion of consistently preferred and easily decodable abbreviations

for single words. This method should benefit system designers by reducing the time needed to produce many good abbreviations for use as

data element codes. Such abbreviations presumably should benefit users

by reducing input time and errors in interactions with battlefield systems. However, the abbreviations produced by simple truncation are not

intended to replace commonly accepted abbreviations and are not likely

to be judged acceptable in all cases.

14

\ M
- 1 1 .- • .•

I

SREFERENCES

ARTADS, Standard data element dictionary. Fort Monmouth, N.J.: Office

of the Project Manager. U.S. Army Tactical Data Systems, 1977.

Barrett, J. A., & Grems, M. Abbreviating words sys...ematically. Communications of the Association for Computing Machinery, 1960,

3, 323-324.

Bourne, C. P., & Ford, D. F. A study of the statistics of letters in

English words. Information and Control, 1961a, 4, 48-67.

Bourne, C. P., & Fo~d, D. F. A study of methods for systematically

abbreviating Lnglish words and names. Journal of the Association

for Computing Machinery, 1961b, 8, 538-552.

Davidson, L. Retrieval of misspelled names in an airlines passenger

record system. Communications of the Association for Computing

Machinery, 1962, 5, 169-171.

Hodge, M. i:., & Pennington, F. M. Some studies of word abbreviation

behav.ior. Journal of Experimental Psychology, 1973, 98, 350-361.

Luhn, H. P. Superimposed coding with the aid of randomizing squPres

for use in mechanical information searching systems. In Casey,

Perry, Kent, & Berry (Eds.), Punched cards--their application to

science and industry (2nd ed.). New York: Reinhold, 1958.

Nawrocki, L. H. Word abbreviations in man-computer communication s_

tems. (ART Working Paper MF 79-04). Alexandria, Va.: U.S.

Army Research Institute, 1979.

Nystrom, C. 0., & Gividen, G. M. Ease of learning alternative TOS

message reference codes. (ARI Technical Paper No. 326). Alexandria, Va.: U.S. Army Research Institute, 1978. (AD A061697)
APPENDIX A

SUMMARY OF ABBREVIATION METHODS

Eleven abbreviation methods were identified by an extensive literature search. A twelfth method was simply the set of existing abbreviations in the 1977 ARTADS Data Element Dictionary (DED). Four of the 11

non-DED methods have been defined in th! main report. The other seven follow.

Contraction/Frequent Letters in Subject Words Out. Keep the first

character and eliminate letters from right to left on the basis of their

frequency of occurrence in subject words until the desired abbreviation

length is reached. Highest frequency letters are eliminated first

(Bourne & Ford, 1961a,b).

Contraction/Frequent Letters in Written English Out. Same method

as above based on written English and different frequency tables (Barrett & Grems, 1960).

Contraction/Letters Out by Position Frequency in Subject Word.;..

Same method as above based on the frequency of letter use by position

(Bourne & Ford, 1961a,b).

Contraction/Letters Out by Position Frequency in Proper Names.

Same method as above using proper names (Bourne & Ford, 1961a,b).

Contraction/Letters Out by Frequency and Redundancy. Keep the

first letter, and from right to left eliminate all U's following Q's;

then eliminate the second letter of double consonants followed by the

second letter of double vowels. irurther eliminate letters one at a

time based on a frequency scale (Barrett & Grems, 1960) until the desired abbreviation length is achieved.

Contraction/Letters Out Using Bigram Rankings for Proper Names.

Keep the first character and eliminate letters based on the frequency

with which they occur in adjacent letter pairs (bigrams) for proper

names. The letter on the right of a pair always is eliminated and in

the case of bigrams with identical frequencies, the rightmost pair is

considered first. For example, using a table of "Bigram Rankings for

a Composite Sample of Proper Names" (Bourne & Ford, 1961a), the word

ablation has the following ranks:

169 276 29 94 130 273 34 12

A B L A T I 0 N space

A score for each letter is derived by adding ranks for the two bi,.rams

associated with letters to produce:

17 RCMGPG IN
A B L A T I 0 N space

445 305 123 224 403 307 46

By removing letters with th*e lowest numbers (highest frequency) the

sample abbreviation becomes "ABLIO."

Contraction/Letters Out Using Bigram Rankings for Subject Words.

Same method as above based on a bigram table for subject words (Bourne &

Ford, 1961a).

A major factor in selecting methods for comparison with the DED

was that they should produce different abbreviations for more than 50%

of the items abbreviated. This constraint was essential since the

candidate terms for abbreviation were limited to those presented in

the DED. The constraint also meant that any two methods having extensive overlap could, in a practical sense, be represented by only one

of the methods.

Two samples of one-word terms from the DED (N 23; N = 89) were

initial]y used to assess the amount of overlap among the 11 methods

and the DED abbreviations. Five methods were eliminated because they

produced more than 70% overlap. The remaining six methods plus the

DED abbreviations were evaluated using a sample (N = 120) of one-word

terms from the DED. Only 21% of the resulting abbreviations were

unique. Two more methods were eliminated because they produced identical abbreviations for more than 50% of the tested terms. An evaluation

yielded only 41% overlap among the five remaining methods. These five

methods were used in the research in conjunction with a selection of

120 terms from the DED. V

SI.

18

K1 *t~' ~
. ;r. ,. 7 - -3 7 77s

APPENDIX B

RESEARCH TERMS RANDOMIZED FOR TESTING FROM THE ARTADS

STANDARD DATA ELEMENT DICTIONARY

Military term Category

Telegraph Communication/electronic equipment

Detonated Activity

Rowboat Vehicle

Airfield Terrain

Probable Evaluation of accuracy

Loudspeaker Commuiication/electronic equipment

Aviation Staff element or function

Telephone Communication/electronic equipment

Organization Staff element or function

Point Area (type of)

Veterinary Unit organization type (special)

Sprayed Activity

Demolition Disposition

Responsibility Disposition

Contact Activity

Observed Activity

Finance Unit organization type (special)

Surrendered Activity

Carbine Weapon (type of)

Restricted Disposition

Screening Deployment

"estroyed Activity

Artillery Staff element or fux'ztion

Attack Mission

Weather Staff element or function

Rifleman Personnel

Unconventional Disposition

Repatriate Personnel

Jamming Activity

Ordnance Unit organization type (principle)

Advance Activity

Saboteur Persornnel

Pipeline Terrain

Suspected Activity

Unclassified Security

Propaganda Report or document

Approach Activity Checkpoiiit Disposition Emplacement Terrain

Reinforcing Support mission

Helicopter Vehicle

Tractor Vehicle

Switchboard Communication/electronic equipment

19

I I il I
Military term Category

Microwave Communication/electronic equipment

Special Deployment

Translator Collection agency

Photographic Communication/electronic equipment

Bulldozer Vehicle

Troops Personnel

Infantry Unit organization type (principle)

Withdraw Activity

Disengage Activity

Shotgun Weapon (type of)

Motorcycle Vehicle

Missionary Personnel

Terrorized Activity

Outgoing Activi.ty

Brambles Vegetation area type

Enlisted Personnel

Infrared Communication/electronic equipment

Mountainous Terrain

Helipad Terrain

Confidential Security classification

Captured Activity

Depression Terrain

Orchard Vegetation area-type

Beachhead Disposition

Airplane Vehicle

Shooting Activity

Surgeon Staff element or function

Newspaper Report or document

Defector Personnel

Incoming Activity

Chaplain Staff element or function

Security Staff element or function

Attached Assignment status

Vineyard Vegetation area type

Plantation Vegetation area type

Crashed Activity

Church Terrain

Strafing Activity

Objective Disposition

Positioned Activity

Partisan Personnel

Fortificatln Terrain

Waterfall Terrain

Amphibious Vehicle

Aeromedical Unit organizition type (special)

Intercepted Activity

Ambulance Vehicle

Infiltrate Activity

Automatic Weapon (type of•

Improbable Evaluation of accuracy

20

I Mi
Military term Category

Roadblock Terrain

Neutralized Activity

Reconnaissance Unit organization type (special)

Reported Activity

Battery Communicationjelectronic equipment

Guerilla Perso.,•.ul

Teletype Comrunication/electronic equipment

Powerline Terrain

Sighted Aztivity

Rectangle Area (ty'pe of)

Generator Cow.munication/electronic equipnent

Sailboat Vehicle

Agent Personnel

Cavalry Unit organization type (special)

Antitank Weapon (type of)

Unreliable Evaluation of reliability

Counterdttack Activity

m Administrative Unit organization type (principle)

Penetrating Activity

"Strongpoint Disposition

Chemical Unit organization type (principle)

Troposcatter Communication/electronic equipment

Television Communication/electronic equipment

Cemetery Terrain

Compressor Vehicle

Concentrate Activity

Envelope Activity

21

40,
. ., ,+•• . . . .• .. . . .. .

APPENDIX C

INSTRUCTIONS TO PARTICIPANTS

Part I

(Preference Ratings: Task A)

In Part I, we are trying to find out how well you like different

abbrcviations. Please look at the example shown below:

Data item Abbreviations

Personnel Unsatisfactory Excellent

PRSNL 0 1 2 3 4 5 6 7 8 i :0

1% 8

PEOEL 0 1 2 3 4 5 6 7 8 9 10

PESEL 0 1 2 3 4 5 6 7 8 9 10

PERSN 0 1 2 3 4 5 6 7 8 9 10

PSONL 0 1 2 3 4 5 6 7 8 9 10

Notice the Data Item and then the list of five differen.: abbreviations. Each of thie five abbreviations is followed by a 0 to 10 scale.

The Data Item is always the word that is represented by the five abbreviations next to it. YOUR TASK IS TO TELL US HOW GOOD EACH ABBREVIATION IS FOR ITS ITEM. In deciding how good an abbreviation is, ask

yourself: "How clearly does the abbreviation represent (i.e., suggest)

the data item?" In Example No. 1 above, we think that the abbreviation

PRSNL is much better than the abbreviation PEOEL for the word personnel.

The scale next to each possibility is used to rate its "goodness." The

two ends of the scale are labeled 0 (unsatisfactory) and 10 (excellent)

so that you know what the scale means. There are no right or wrong

answers on these scales--only your opinions! Two abbreviations in the

example have been rated to show you how the system works. Obviously,

the 2 rating for the abbreviation PEOEL says that the rater considers

it to be a very poor abbreviation; in contrast; the 9 rating for the

abbreviation PRSNL shows that he thinks that it's a very good abbreviation. Circling a "0" would show that the abbreviation is completely

unsatisfactory and a "10" is the best possible goodness rating that can

be given. The "5" rating is the middle point--the choice which means

that an abbreviation is neither good nor bad--it's in between. The

other numbers are used to show how much you like an abbreviation (6,7,

8,9) or how poor you think it is (1,2,3,4). The rating for each abbreviation is up to you.

23

PAEBLAIW
Before you work the rest of Example No. 1, here are some suggestions: Start out by trying to find an abbreviation that you really

like and one that you really do not like for a particular data item.

You may not always have strong feelings, but this typically is a good

approach. Rate each of these abbreviations. Then, go on to the three

that are left to be rated. Do not be concerned if several abbreviations seem equally good (or bad) to you. If that is the case, just

circle the same number on the scale for them. When you are done with

a group of five abbreviations, please check to see that each scale

number reflects how good an abbreviation is compared to others in that

group. If you want to change a rating, ERASE THE CIRCLE AROUND THE

OLD CHOICE AND CIRCLE THE NEW CHOICE. Now, please go on and do Example No. 2 below. If there are any questions, PLEASE RAISE YOUR HAND.

Data item Abbreviations "

threaten

Unsatisfactory Excellent

THREE 0 1 2 3 4 5 6 7 8 9 10

TEAEN 0 1 2 3 4 5 6 7 8 9 10

THRTN 0 1 2 3 4 5 6 7 8 9 10

TEATN 0 1 2 3 4 5 6 7 8 9 10

TREAN 0 1 2 3 4 5 6 7 8 9 10

AT THIS POINT YOU SHOULD HAVE CIRCLED FIVE NUMBERS, ONE FOR EACH OF THE

ABBREVIATIONS. Ask questions by raising your hand during the task if

you have any problems.

Now, rate each of the data items in Part I of the booklet. Then,

go on to Part II and finally Part III. Each part has its own instructions. Remember, if you have any questions, don't hesitate to ask.

24

• " ' - " A -I A~LI. •- I I
- - I I I I I

Part II

(Decoding: Task B--Cue Condition)

In this part of the research we are trying to determine how well

the different abbreviations suggest the data items that they represent.

An example of the materials that 7ou will be using for this part of

the study is shown below:

Abbreviation Category Corresponding item

APL Fruit]III 1I[1 7[l7

In this example the abbreviation is "APL." You are to decide what

the original data item was and print it in the blocks on the right hand

side of the page beneath the heading "Corresponding item." The word

beneath the heading "Category" describes the type of thing or group of

items that the abbreviation is part of. In this example "Fruit" means

that the original data item was some kind of fruit. If you thought

that the original data item was "apple" (that is that APL stands for

"apple") you would print "apple" in the space provided beneath the

heading "Corresponding item" and your answer would look like this:

Abbreviation Category Corresponding item

APL Fruit IopI~IleI I I I 11" 1'

If you don't "really know" what the original data item was then

take a guess. You might be right! For each abbreviation in Part II,

please write the corresponding data item. Remember that all of the

items in your task will be related to military use. (Note: You will

have seen some of the items earlier.) IF THERE ARE ANY QUESTIONS,

PLEASE RAISE YOUR HAND. IF YOU HAVE NO QUESTIONS NOW, PLEASE TURN THE

PAGE AND START.

25

•i I l r 'D q - l l , • •
(Decoding: Task B--No Cue Condition)

In this part of the research we are trying to determine how well

different abbreviations suggest the data items that they represent.

An example of the materials that you will be using for this part of the

study is shown below:

Abbreviation Corresponding item

APLI II II

In this example the abbreviation is "APL." You are to decide what

the original data item was and print it in the blocks on the right hand

side of the page beneath the heading "Corresponding item." In this

example, if you thought that the original data item was "apple" (that

is that APL stands for "apple") you would print "apple" in the space

provided beneath the heading "Corresponding item" and your answer would

look like this:

Abbreviation Corresponding item • • I I I I I I I ! I I II I I I

-I

if you don't "really know" what the original data item was then

take a guess. You might be right! For each abbreviation in Part II,

please write the corresponding data item. Remember that all of the

items in your task will be related to military use. (Note: You will

have seen some of the items earlier.) IF THERE ARE ANY QUESTIONS,

PLEASE RAISE YOUR HAND. IF YOU HAVE NO QUESTIONS NOW, PLEASE TURN

THE PAGE AND START.

26

-.>4,
Part III

(Encoding: Task C--Cue Condition)

In the third and last part of this research, we want you to tell

us how you would abbreviate the data items. An example of the materials

that you will be using is shown below.

Data item Caoýry Corresponding abbreviation

apple Fruit111 til 111

The word that you are to abbreviate is beneath the heading "Data

item." In this example, the data item to be abbreviated is "apple."

As in part II, the word beneath the heading "Category" describes the

type of thing or group of items that this particular item is part of.

In this example the data item represents a fruit. You are to make up

an abbreviation for the data item and write it in the string of blocks

beneath the heading "Corresponding abbreviation." In this example, if

you chose to abbreviate "apple" using APL your answer would look like

this:

Data item Category Corresponding abbreviation

apple Fruit -jJI i

In making up your abbreviations please keep the following rules

in mind:

1. Your abbreviations must be 3 ox more letters long.

2. Your abbreviation can be as long as you N•ant it to be except

that you must use less i Qtters than the number of letters in

the whole word.

3. You are to try to use the minim'm number of letters possible

(conciseness)--but not t..ts than 3 letters--while at the

same time trying to maximize the degree to which the abbieviation suggests the data item it represents (meaningfulness).

For each data item in Part IIl please write you! choice for the

corresponding abbreviation. Remember that all of the items in your

task will be related ti military use. (Note: You will have seen some

of the items earlier.) IF THERE ARE ANY QUESTIONS PLEASE RAISE YOUR

HAND. IF YOU HAVE NO QUESTIONS, PLEASE TURN THE PAGE AN) START.--DON'T

FORGET RULES 1, 2, and 3 ABOVE!!!

27

i '
NOTE TO READER: Instructions for the "No Cue Condition" were identical

except that the "Category" did not appear-.

14

28
APPENDIX D

ANALYSIS OF VARIANCE TABLES

Table D-1

Analysis of Variance for Acceptability Ratings

of Abbreviation Methods

Source of variation df MS F p

Betweep participants 49 4.5453

Within participants

Methods 4 50.6180 65.9260 .01 '

Residual 196 0.7678

Total 249

29

4.'
- - --- - -~ 

Table D-2

Analysis of Variance for Number of Abbreviations Correctly Decoded Using Liberal Scoring

Source of variation 

df MS S~p F

Between Cues participants Groups 1 8.7120 1.66 NS Groups 4 3.1670 0.60 NS Cues x Groups 4 2.7970 Error 0.53 NS

40 5.2340

"Within participants SMethods4 "Methods 

4 9.9120 11.06 . Blocks of Words 39.29 .01

4 8. 3270 9.29 Residual .01

12 1.3836 Methods x Cues 1.54 4 0.6520 0.73 NS Blocks of Words x Cues 40.650 0.3 NS 4 4.7570 5.31 .01

Residual x Cues 12 0.7803 0

:iError 2 

Eror2160 0.87 NS

0.8965

"Experience 1 313.6320 178.14 .01 Experience x Cues 1 1.8000 Experience x Groups 1.02 NS 4 13.5570 7.70 .01 Experience x Cues x Groups 4 1.3350 0.76 NS

Error 3 40 1.7606

Experience x Methods 4 3.0520 3.44 .025 Experience x Blocks of Words 4 11.4070 12.85 .01 Experience x Residual 12 .. 1586 1.31 NS Experience x Methods x Cues 4 1.2200 1.37 NS - EpiCues 

Experience x Blocks of Words x 4 6.9050 7.78 Experience x Residual .01 x Cues 12 2.3050 2.59 Error .01 4 160 0.8875

STotal 

499

30

7 "
Table D-3

Analysis of Variance for Number of Abbreviations Correctly

Decoded Using Strict Scoring

Source of variation df MS F p

Between participants

Cues 1 6.5000 1.35 NS

Groups 4 3.1750 0.66 NS

Cues x Groups 4 2.8525 0.59 NS

Error 1 40 4.8160

Within participants

Methods 4 5.2750 5.33 .01

Blocks of Words 4 8.4450 8.53 .01

Residual 12 0.9933 1.00 NS

Methods x Cues 4 1.0925 1.10 NS

Blocks of Words x Cues 4 0.6225 0.63 NS

Residual x Cues 12 0.4316 0.44 NS

Error 2 160 0.9897

Experience 1 312.0500 144.74 .01

Experience x Cues 1 11.2500 0.58 NS

Experience x Groups 4 4.0250 1.87 NS

Experience x Cues x Groups 4 1.1650 0.54 NS

Error 3 40 2.1560

Experience x Methods 4 3.4250 3.52 .01

Experience x Blocks of Words 4 2E.2250 26.91 .01

Experience x Residual 12 1.5833 1.62 NS

Experience x Methods x Cues 4 0.4450 0.46 NS

Experience x Blocks of Words

x Cues 4 5.3450 5.48 .01

Experience x Residual x Cues 12 0.7066 0.72 NS

Error 4 160 0.9747

Total 499

31

y... Ai

II I iUi,
Table D-4

Analysis of Variance for Number of Abbreviations That Conform to

Abbreviations ',rodi=ed by the Five Methods

Source of variation df MS F p

Setwe'n participants 49 2.62

Within participants

Method 4 116.40 42.85 .01

Error 1 196 2.72

Expexience 1 0.39 0.43 NS

Error 2 49 0.90

Methods x Experience 4 1U.26 9.62 .01

Error 3 19" 1.17

Total 499 I

32

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34