Faculty Perceptions of Academic Dishonesty · search literature, academic dishonesty has been the subject of research for decades, addressing a wide variety of issues and questions,

*E Holly Seirup PincusLiora Pedhazur Schmelkin

Faculty Perceptions of Academic Dishonesty

A Multidimensional Scaling Analysis

One need not search far for evidence that academic

dishonesty is ubiquitous in our society. Indeed, newspaper accounts of

cheating by students, teachers, and administrators appear on a fairly reg-

ular basis, and HBO recently premiered a movie, Cheaters (May 20,2000), based on a Chicago high school's cheating scandal. In the re-

search literature, academic dishonesty has been the subject of research

for decades, addressing a wide variety of issues and questions, includingwhat academic dishonesty is, how prevalent it is, who cheats, why stu-

dents cheat, what the faculty reactioii is, and what the institutional re-

sponse is. For a review of much of this research, see Cizek (1999),Crown and Spiller, (1998), and Whitley (1998).

One of the main issues that emerges from the literature relates to in-

consistencies in the definition of academically dishonest behaviors and

the lack of consensus and general understanding of academic dishonesty

among all members of the campus community. According to Robertsand Rabinowitz (1992), "Our ability to alter the environment in whichcheating takes place will be determined by our understanding of howpeople (both faculty and students) perceive cheating and its seriousness"

(p. 189).Various attempts have been made to define academic dishonesty. For

example, in an August 1993 report published by the United States De-

partment of Education, Maramark and Maline note: "Cheating takes

l-lolly Seirup Pincus is vice president tor Campus Life, and Liora Pedhazur Schmelkin

is Leo A. Guthart Distinguished Professor of Teaching Excellence, Hojstra University

Hempstead, NY Please direct all correspondence to the first author at vpshjs@hofs-

tra.edu.

The Journal of Higher Fducation, Vol. 74. No. 2 (March/April 2003)

Copyright ©O 2003 by The Ohio State University

Acacdemic Dishonesty 197

many formns-from simnply copying another student's paper to stealing anexam paper to forging an official university transcript" (p. 3).

Gehring and Pavela, in a 1994 report on academic integrity to the Na-tional Association of Student Personnel Administrators, offer the follow-ing definition:

We regard academic dishonesty as an intentional act of fraud, in which a stu-dent seeks to claim credit for the work or efforts of another without autho-rization, or uses unauthorized materials or fabricated information in any aca-demic exercise. We also consider academic dishonesty to include forgery ofacademic documents, intentionally impeding or damaging the academicwork of others, or assisting other students in acts of dishonesty. (p. 5)

The definitions and classifications that have been attempted are broadand ambiguous. Most people agree that ch-eating is unethical (Barnett &Dalton, 1981), and yet there remains some confusion about what partic-ular behaviors constitute academic misconduct. Some forms of acade-mic dishonesty are apparent to everyonie: plagiarism, copying fromsomeone else's exam, purchasing term papers, stealing a test, or forginga university document. Other more questionable formns of academic be-haviors are still debated among faculty, students, and administrators:collaborating on homework and take-home exams when individual workis specified, handing in the same work for two separate classes, or inap-propriately utilizing the services of a tutor or a writing center (Fass,1986).

Even plagiarism, which most people describe as academically dishon-est behavior, is sometirnes controversial. For example, Miller, in an arti-cle in the Chronicle of Higher Education !( 1993), argues that plagiarismmay not be universally understood, and teachers cannot assume thatevery student comes into the classroom with the same belief system.

Russell Baker, in an op-ed article in Thle New York Times, offers an-other example of unintended plagiarism:

Charges of plagiarism, which have become so common lately, may well bethe fault of the computer instead of the author. That's because volumes of re-search material from other people's work get stored in the electronic filealong with the manuscr-ipt in progress. The author searching his index for anappropriate citation finds a file name for stuff he stored up a year or two ago,presses a couple of keys and-shazam!-like magic, another author's para-graph is inserted whole into the manuscript, its attribution lost somewheredown the cracks in the electronic floorboards. (1 995, p. A25)

In addition to the general problem of arnbiguity of definition, differ-ences exist among the various studies as to the assessment of severity ofthe various indicators of academic disho.nesty (e.g., Cannon, Fox, &

198 The Journal of Higher Education

Renjilian 1998; Franklyn-Stokes & Newstead 1995; Graham, Monday,

O'Brien, & Steffen, 1994; Nuss, 1984; Roig & Ballew, 1994; Sims,

1995). One potential explanation for these differences could be due to

the different scales used by the researchers. For example, Cannon et al.

(1998) used a 5-point rating scale, with I indicating that the depicted

scenario was definitely not representative of academic dishonesty, and 5

indicating that it definitely was. Graham et al. (1994) used a 4-point

scale, with I = "not cheating" and 4 = "very severe," whereas Sims

(1995) used a 6-point scale, ranging from not at all dishonest to very se-

vere. Nuss (1984), on the other hand, used a forced-choice ranking sys-

tem whereby respondents ordered the 14 presented behaviors from most

serious to least serious. It is not surprising, therefore, that differences

emerged in the particular ordering of the behaviors on the various

continua.The purpose of the present study was to focus specifically on faculty

in an attempt to uncover some of their underlying perceptions and to

gain a better understanding of how they conceptualize academic dishon-

esty. Specifically, do faculty conceptualize academically dishonest be-

havior on a single dimension or on multiple dimensions, and what is the

nature of these dimensions?Moreover, given the ambiguity that exists in the definitions, the

choice of the analytic method-multidimensional scaling (MDS)-was

particularly important, because it was desired to utilize a methodology

that does not automatically constrain the results to a single dimension

and allows for multiple dimensions to emerge. In addition, it does not

impose the researchers' a priori conceptions of the relevant dimensions.

MDS (for discussions of various MDS methods and their assumptions,

see, for example, Davison, 1983; Kruskal & Wish, 1978; Schiffman,

Reynolds, & Young, 1981) is a set of methods that attempt to uncover

perceptions or cognitions of a stimulus set in a relatively unconstrained

fashion. In the present research, the advantage of utilizing MDS was

that it yielded information from the faculty on their underlying percep-

tions of the academic behaviors with little constraint or bias from the re-

searchers. For example, if faculty were asked a priori to rate each illus-

tration of academic dishonesty on how serious they perceive it to be,

then it is possible that the scale provided (seriousness, in this example)

may predetermine faculty members' perceptions and responses. More-

over, rating a set of stimuli on a single rating scale may produce a lack

of discernable differentiation among the stimuli if all or most of the rat-

ings are concentrated on one end of the rating scale. Thus, with a 7-

point rating scale, where the anchors are labeled I = "not at all serious"

and 7 = "very serious," if respondents view most of the stimuli as being

----- ----------------------- ....... .. ..... .......... -- .............. ��- ...... .......... ,- .. .. ......... ,_ -- ------

Academic Dishonesty 199

in the very serious end of the scale, the resulting ratings will all be neg-atively skewed and similar in value, even though the underlying percep-tions may be differentiated. The main point is that respondents "maydraw on what is supposedly a purely formal feature of the rating scale,namely its numeric values" (Schwarz, 1999, p. 95), and their responsesmay be influenced and constrained by the nature of the rating scale it-self. Another advantage of MDS is that it provides a graphical presenta-tion of the results, thereby making the underlying dimensions more po-tentially discernible. "In useful or interesting applications, thecharacteristics we discover in this way are seldom totally unsuspectedor surprising. On the other hand, they are usually part of a much longerlist of characteristics which might just as plausibly have appeared. Oneuseful role of MDS is to indicate which particular characteristics areimportant in contrast to others which are just as plausible" (Kruskal &Wish, 1978, p. 35).

Method

Instruments

Two versions of the data collection instrument were developed. One,considered the primary instrument, consisted of pairwise similarity rat-ings and will henceforth be called the MEIS version. The other consistedof bipolar rating scales and will be referred to as the Rating Scale (RS)version. The same list of examples of academically dishonest behaviors(e.g., plagiarizing, taking a test for someone else, using crib sheets) wereused in both the MDS and RS versions. The original list of examplesbased on the research literature was reviewed by several faculty, admin-istrators and students to verify that a thorough and representative listwas generated. From the feedback received, modifications to the listwere made, and the final list contained 283 behaviors. The complete listappears in Table 2.

Both the MDS and RS versions of the instrument contained the samebackground sections. The background portion included a demographicsection that requested information such as school, level of primaryteaching (graduate or undergraduate), tenure status, and sex. In addition,a section on incidents that a faculty member may have encountered waspresented, followed by a section on policy concerns.

MDS version. In the MDS version. pairwise ratings of the 28 exam-ples of academic dishonesty were requested of the respondents. This re-quired them to use their own frame of reference to "judge the similarity


of the behaviors in each pair" on a scale of I (very different) to 9 (verysimilar). For example:

Very VeryDifferent Similar

plagiarizing123456789

failing to report a grading error

With 28 stimuli, 378 pairs were constructed. These were developedaccording to a maximally efficient ordering of the pairs as derived byRoss (1934). This ordering ensures separation of the stimuli and also

their placement (in the first or second position of a pair). Asking respon-

dents to complete 378 pairwise similarity comparisons would have beentoo time consuming and onerous a task. Therefore, the 378 ordered pairswere systematically assigned to four forms labeled A, B, C, and D.Forms A and D had 95 pairs, and forms B and C had 94 pairs. Althoughthe specific pairs were not identical, the four forms could be considered

equivalent with each stimulus appearing between five and eight times oneach one of the forms.

RS Version. In order to externally validate the interpretation of theMDS analysis, 10 bipolar rating scales (seriousness, minor vs. major vi-

olation, effect of student intent on faculty response, flexibility, ease of

detection, difficulty of proving, clear example. firm versus lenient sanc-tion/resolution required, should a notation be placed on the transcript,formal versus informal resolution) were developed based on characteris-tics that have previously been identified in the literature. As is typicallydone in MDS interpretations (e.g., Davison, 1983; Kruskal & Wish,1978; Schiffman et al., 1981), unidimensional rating scales can be

thought of as exploratory "hypotheses" of the important attributes in the

dimensional space and are used to "'objectify' the process of naming[the] dimensions, or to 'verify' the names used by the researcher"(Schmelkin, 1985, p. 227).

Participants were asked to rate each of the behaviors using a 9-pointscale. Using the first scale of seriousness as an example:

Not VerySerious Serious

123456789 plagiarizing

Requiring ratings of each of the 28 behaviors on the 10 scales would

have yielded a total of 280 ratings per respondent. Once again, in the

hopes of alleviating respondent fatigue, two bipolar forms were created,each containing five scales. Consequently, faculty only had to complete140 ratings.

................ I..",- ', ............ ...................... 1111-----------------------_-------------------------- . .............. -----,---- -- -------- ..-_

Academic Dishonesty 20(1

Sample and Procedures

The study was conducted at a private university in the Northeast en-rolling 12,000 students, approximately 7,000 of them full-time under-graduates. About 1,000 faculty members are active during any given se-mester, half full-time and half adjuncts. From the pool of active faculty,150 full-time faculty and 150 adjunct faculty were randomly selected toparticipate in the study, for an initial sample of 300. The 300 facultymembers were randomly assigned to receive one of four MDS forms orone of two RS forms with 25 full-time and 25 adjunct faculty receivingeach form.

Following mail survey procedures outlined in Dillman (1978), threecomplete mailings were conducted, with the two follow-ups occurring atthree weeks and seven weeks after the original mailing; a reminder post-card was sent one week after the original mailing. The complete mail-ings included: (a) one of the six instrumenits in booklet form, (b) a per-sonalized cover letter explaining the project, (c) a postage-paid returnenvelope, and (d) a postage-paid return postcard.

Faculty were guaranteed anonymity as no identification markingswere placed on the instruments or the envelopes. In order to be able tosend follow-up mailings to those who did not respond, a separate re-sponse postcard was utilized. Faculty were instructed (in the cover let-ter) to return the postcard when they comp]eted the questioinaire so thatthey would be removed from the follow-up list.

Response Rate and Final SampleOf the 300 instruments originally mailed, 72% (216) were returned,

and 71% (212) were usable. Of the 212 tuseable instruments returned,the breakdown by form was similar, as were the response rates by fac-ulty status. Of those who responded, 48% (102) were full-time faculty,45% (96) were adjunct faculty, and 7% (14) did not indicate their status.There were 63% (133) males, and 36% (77) females. Of the overall sam-ple, 77% (161) primarily taught undergraduate classes. The mean num-ber of years teaching was 16.33 (SD = 11.90). Comparisons of the finalsample with the complete faculty census information at the time of thedata collection revealed that the sample was representative based uponthe variables studied (e.g., status, sex, rank, teaching emphasis, tenure,division or school affiliation).

Results

The primary data set for the MDS analysis consisted of a super meanmatrix. Prior to generating this matrix, differences between various


subgroups (e.g., based on sex, status) were explored. One-way analysis

of variance results indicated that there were no major differences based

on full-time/adjunct status, sex, primary teaching emphasis, tenure sta-

tus, rank, or division. Consequently, the means from all the pairwise

similarity ratings across the four forms were collected into one super

mean matrix.This 28 x 28 (stimulus by stimulus) lower-half mean matrix consti-

tuted the raw input into the MDS analysis. Using the ALSCAL proce-

dure of SPSS with ordinal symmetric similarity data, solutions were

sought for one to six dimensions. Decisions as to appropriate dimen-

sionality in MDS were made on both statistical, as well as substantive,

interpretive grounds. The statistical indices used were the Stress, S-

stress, and RSQ values. The first two are badness of fit measures, with

lower values indicating better solutions. RSQ, on the other hand, indi-

cates the proportion of variance in the data accounted for by the solu-

tion. An examination of these values (see Table 1) indicated that there

appeared to be improvements in fit as dimensionality increased from I

to 2, and perhaps 2 to 3, with subsequent leveling off beyond 3 dimen-

sions. Therefore, the 2- and 3-dimensional solutions were examined in

more detail in order to determine which was more appropriate from a

substantive standpoint.When reviewing the 2- and 3-dimensional solutions in detail, it was

noted that the 3-dimensional solution did not appear to add very much

more substantively. In fact the third dimension was not interpretable,

and the first two were substantially the same as the two dimensions of

the 2-dimensional solution. Therefore, the 2-dimensional solution, ac-

counting for 82% of the variance, was retained as most appropriate. Fig-

ure 1 presents the solution graphically, whereas Table 2 provides a com-

plete listing of the stimuli, their corresponding abbreviations on the

figure, and the actual coordinates. In interpreting the dimensions, an in-

ternal examination is presented first, followed by an external validation.

TABLE 1

Goodness/Badness of Fit Indices for the MDS Solutions

# Dimensions Stress S-stress RSQ

6 0.129 0.084 0.923

5 0.152 (.101 0.905

4 0.175 0.119 0.88

3 0.212 0.158 0.857

2 0.254 0.210 0.819

1 0.299 0.310 0.748

---------.- ................................ {. . . . .............. _

Academic Dishoonesty 203

15 n te0 oo t0 otre

nofootnt

1.0 studnote f Isebib

notcontr for ulas

.5 *owyhw obtdurngcol a . plagiar

hhavewrit0.0 T hieet00 * f~~~~~~~~ra pap purpap

Dim2 tutor

obtexam

-.5 subsame iveanSw stealtstf9writpap

grderror taketest sabotageexcuse giveltrtaeetsbtg

-1.0

-1.5 _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

-4 -3 -2 -1 0 1 2 3 4

Dim. 1

FIG. I

Dimension I

Behaviors such as "sabotaging someone else's work," "forging a Uni-versity document," "stealing a test," "usinig crib sheets," and "obtaininganswers from someone else during an exam" anchor one end of the di-mension or continuum. At the other extreme are "studying from some-one's notes," "failing to report a grading error," "not contributing a fairshare to a group project," "delaying taking an exam or turning in a paperdue to a false excuse," and "utilizing a tutor or writing center inappro-priately."

This dimension was labeled Seriousness. At one end of the continuumare behaviors that faculty code as severe and that are clearly consideredacademically dishonest behaviors with some bordering on illegal. At theother end of the continuum are those behaviors that are perceived asbeing less severe. Looking at Figure 1, it is clear that the stimulus"studying from someone else's notes" is not considered a serious viola-tion. In fact it is not considered an academically dishonest behavior at allby many of the respondents.

Examining the behaviors that fell in the middle range of the continuum


TABLE 2Stimulus Listing and MDS Coordinates

Academic Behavior Abbrcv. Dim. I Dim. 2

collaborating with others on an assignment that wasassigned as individual work collab -1.0348 0.3221

copying homework copyhw - 0.7275 0.3788copying information without utilizing quotation marks quote -0.4589 1.3288copying material without proper footnotes or citations footnt -0.5973 1.1805delaying taking an exam or turning in a paper due to

a false excuse excuse -1.4964 -0.9800failing to report a grading error grerror -2.1533 -0.8934falsifying or fabricating a bibliography biblio 0.1905 0.9695forging a University document forge 1.5256 -0.5299giving answers to sonieone else during an exatn givans 0.310)0 -0.5699giving exam questions to students in a later section givexam 0.3327 -0.9959having someone else write a term paper for you havewrit 1.0361 0.0292hiring a ghostwriter hireghst 0.8976 -0.0376inputting information or formulas needed for an exam

into a calculator formula -0.0343 0.6773not contributing a fair share in a group project notcont -2.0186 0.7301obtaining a copy of the exant to be given prior to class obtprior 1.0465 -0.4143obtaining a test from a previous semester obtprev -0.3354 1.2590obtaining answers from someone else during an exam obtdur 1.1009 0.4000plagiarizing plagiar 0.9288 0.3000purcitasing a termti paper to be turned in as one's own purpap 0.9507 -0.1309sabotaging someone else's work (on a disk, in a lab, etc.) sabotage 1.7820 -0.9611stealing or copying a test steal 1.1298 -0.6007studying fronm someone else's notes studnote -3.1690 0.9129submitting the same term paper to another class

without permission samepap -0.8971 -0.5948taking a test for someone else taketest 0.9614 -0.9447using crib sheets crib 1.1271 0.2284utilizing a term paper or exam from a fraternity or

sorority test file ftatpap 0.0277 -0.1117utilizing a tutor or writing center inappropriately tutor -1.2454 -0.2490writing a term paper for someone else writpap 0.8205 -0.7000

is also interesting. These behaviors are seen by some as serious, whileothers disagree. An example is the stimulus that fell right at the center ofthe graph, "utilizing a term paper or exam from a fraternity or sororitytest file." Using previous exams has been viewed by some as cheating,while other professors may even encourage this type of behavior as anexcellent study tool.

In order to validate the internal interpretation of the dimension pre-sented above, the bipolar rating scales were used as a method of externalvalidation. Means on each of the 10 bipolar scales were computed. As inthe case of the pairwise similarity ratings, tests were performed on thesemeans which indicated that there were no statistically significant differ-


ences between subgroups. Therefore, means over all individuals withinthe groups were collapsed by form. Each of the 10 means was regressedon the coordinates of the 2-dimensional M[DS solution. The results ofthese analyses are summarized in Table 3, which presents the multiplecorrelations (R) and the optimum weights corresponding to each. Thelatter "are the direction cosines, that is, regression coefficients normal-ized so that their sum of squares equals 1.00 for every scale" (Kruskal &Wish, 1978, p. 37). In order to be useful in interpretation, R valuesgreater than 0.90 are desired, although values of 0.70 are often used; pshould be ' 0.01. In addition, the coefficients should be large for atleast one of the dimensions (Kruskal & Wish, 1978).

Of the 10 scales, 7 have high R values of 0.88 or above and are there-fore highly interpretable. These scales are seriousness, major vs. minorviolation, formal vs. informal resolution, degree of flexibility (when thesituation is encountered), clarity, firm vs. lenient sanction required, andwhether a notation should be placed on the transcript. For each of thescales, there is a high coefficient corresponding to the first dimension.

The 7 scales seem very interrelated and focus on both the nature of thebehavior itself (whether it can be viewed as serious, is a major violation,and is a clear example of academically dishcnest behavior) as well as thesanctions or consequences that faculty deem are appropriate. It is under-standable that serious behaviors are identified as being clear unambigu-ous examples and are considered major violations, where a formal, firm

TABLE 3

Multiple Regression of Bipolar Scale Ratings on Dimensions of Perceptions of Academic Dishonesty

Regression Weights(Direction Cosirnes)

Ratinig Scales Dimension Dimension Multiple Correlation (R)1 2

Not at all serious/Very serious 0.97 -0.24 0.89*Minor violation/Major violation 0.98 -0.22 0.92*Mostly informal (resolution needed)/Formal 0.84 -0.30 0.90*Intent (of student) does not affect me/ -0.99 0.14 0.58*

Intent affects meNo flexibility (if extenuating circumstances)! -0.95 0.32 0.94*

A great deal of flexibilityVery difficult to detect/Very easy to detect 0.92 0.39 0.37Very difficult to prove/Very easy to prove 0.80 0.60 0.33Unclear (example of academic dishonestv)/Clear 0.97 -).23 0.88*Lenient (resolution or sanction)/Firm 0.99 -0.16 0.95*Should never be noted on transcript! 0.98 -(1.18 0.95*

Sthould always be noted on transcript

*p<O.O.


means of resolution would be sought, including a notation on the tran-script. These behaviors would allow for little flexibility when resolu-tions are sought.

Dimension 2

Turning now to the second dimension, it is not as clearcut. However, itdoes appear that there is a comparison of behaviors having to do withpapers and homework, with "copying information without using quota-tion marks," "copying material without proper footnotes," "falsifying orfabricating a bibliography" anchoring one end of the dimension. At theother extreme are behaviors that are related to exams in the classroom,such as "failing to report a grading error," "delaying to take an exam orhand in a paper due to a false excuse," "giving exam questions to stu-dents in a later section." This dimension is therefore intelpreted as Pa-pers vs. Exams.

The bipolar rating scales were not useful in helping to shed more lighton dimension number two. The lack of external validation suggests thatfor this interpretation, other more appropriate rating scales may need tobe utilized in future research.

Discussion

The multidimensional scaling analysis coupled with the external vali-dation (bipolar rating scales) indicated that faculty perceive academi-cally dishonest behaviors on two dimensions: a clear-cut continuum ofSeriousness and a somewhat more ambiguous Papers vs. Exams dimen-sion. No differences in faculty perception of academic dishonesty werefound due to full-time/adjunct status, sex, rank, tenure status, primaryteaching emphasis, and/or division.

That academically dishonest behaviors are perceived on a continuumof seriousness is consistent with others findings in the literature, al-though the specific ordering may differ (e.g., Cannon et al., 1998;Franklyn-Stokes & Newstead 1995; Graham et al., 1994; Nuss, 1984;Roig & Ballew, 1994; Sims, 1995). This finding validates the notion thatfaculty do not perceive academic dishonesty dichotomously as an all ornothing situation. Rather, faculty view the various potential indicators ofacademic dishonesty on a continuum of severity, which for faculty is re-lated to the clarity of the definition. It is important to underscore that inthe primary MDS analysis this dimension emerged without its explicitstipulation. That is, faculty were not asked to directly rate or comparethe behaviors in terms of their seriousness. Such comparisons may haveraised the possibility that the subsequent results were constrained by the

-: - ---------- ------ -- . ..... ..... ................................ . ....................................... .


researchers' a priori conceptions. Instead, faculty's internal representa-tions of academic dishonesty emerged fromn the analyses.

Given the different methodology utilized, it is noteworthy that there issome congruence between the current findings and those found in the re-search literature in terms of which behaviors are viewed as most serious.For example, Sims (1995) found that the most serious behaviors wereusing someone else's paper, taking an exam for someone else, askingsomeone to take an exam, purchasing a paper, and using crib sheets duringan exam. Nuss (1984) found that copying d:uring an exam, paying some-one to write a paper, and using signals during an exam were seen as mostserious. For faculty in the Graham et al. (1994) study, the most serious be-haviors were taking a test for someone else, copying a term paper, havingsomeone else write a paper, and copying du-ring an exam. And in the Lip-son and McGavern (1993) study, it was cheating during an exam and sub-mitting someone else's work. Similarly, less serious behaviors generallyfocus on not contributing a fair share in a group project, giving false ex-cuses, and submitting the same paper to two or more classes (e.g., Grahamet al., 1994; Lipson & McGavern, 1993; Nuss, 1984; Sims, 1995).

Although less clear-cut and not substantiated by the rating scaleanalyses, there is also some corroboration from the research literaturefor the second dimension, which appears to distinguish between exam-related behaviors and paper-related behaviors. In their discussion of thecomplexity of the definition of academic dishonesty, Newstead,Franklyn-Stokes, and Armstead (1996) referred to the separation ofcoursework (which includes paper assignments) and exanm cheating. Theseriousness dimension enters into this separation, for exam-based cheat-ing was generally seen as more serious than coursework-based cheating(Ashworth, Bannister, & Thorne, 1997; Franklyn-Stokes & Newstead,1995; Nuss, 1984). This was especially so for students' perceptions.

Our own preliminary research into students' perceptions of academi-cally dishonest behaviors has yielded results that are consistent withwhat has been found with the faculty, although some differences didemerge (Schmelkin, Spencer, Gilbert, Lieberman, & Pincus, 1999). Stu-dents also perceived the behaviors in two dimensions, one focusing onseriousness, and the other differentiating between exam-based andpaper-based cheating. The differences between the faculty and the stu-dents were in emphasis. Although there is general agreement on whatare perceived to be less serious offenses, some behaviors that are notconsidered that serious by students (e.g., "sabotaging someone else'swork") are considered very serious by faculty.

Most universities have developed guidelines and policies about acade-mic dishonesty, which often include examples of cheating. Unfortunately,


the examples are typically limited to behaviors that have been com-monly agreed upon as representing academic dishonesty (e.g., using cribsheets, plagiarizing, copying from another student during an exam).What consistently has been missing from these lists of examples havebeen the ambiguous behaviors. It is clear from the present data and fromthe literature that not all cheating behaviors are viewed alike. Further,differences exist between different constituencies (e.g., faculty, stu-dents) in their views. It is not surprising, therefore, that "problems withdefinition often lead to inconsistent application of penalties (rangingfrom reprimand to expulsion) leaving students confused about what spe-cific activities constitute cheating or believing that less serious forms ofcheating are acceptable" (Maramark & Maline, 1993, p. 7).

In addition, most policies do not take into account the fact that fac-ulty's views about these issues are complex and that they see the behav-iors on various continua. When considering whether the response shouldbe educational or punitive, there is usually no consideration of where theparticular behavior "falls" on the continuum of seriousness. This lack offlexibility in many policies might be a contributing factor in understand-ing why faculty memiibers may feel reluctant to report a student who theybelieve is involved in a less serious incident.

Our findings suggest there is a strong interplay between whether aca-demically dishonest behaviors are seen as major violations and theseverity of the sanctions that should be imposed. It is probably safe toconclude that faculty would prefer that sanctions be applied differen-tially depending on the severity of the behavior. We, therefore, recom-mend that policies be made more explicit as to differential sanctions.

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TITLE: Faculty Perceptions of Academic Dishonesty: AMultidimensional Scaling Analysis

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Faculty Perceptions of Academic Dishonesty · search literature, academic dishonesty has been the subject of research for decades, addressing a wide variety of issues and questions,