Cheating in college
College Cheating: Immaturity, Lack of Commitment, and the Neutralizing Attitude Author(s): Valerie J. Haines, George M. Diekhoff, Emily E. LaBeff and Robert E. Clark Source: Research in Higher Education, Vol. 25, No. 4 (1986), pp. 342-354 Published by: Springer Stable URL: http://www.jstor.org/stable/40195757 . Accessed: 23/10/2014 20:05
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COLLEGE CHEATING: Immaturity, Lack of Commitment, and the Neutralizing Attitude
Valerie J. Haines, George M. Diekhoff, Emily E. LaBeff, and Robert E. Clark
Through the use of a 49-item questionnaire administered to 380 university students, we
investigated student cheating on exams, quizzes, and homework assignments. More than half the students reported cheating during the academic year on at least one of the above. The purpose of this paper was to uncover fundamental factors underlying cheat-
ing behavior. Through the use of correlational and factor analysis, three primary factors were identified: student immaturity, lack of commitment to academics, and neutraliza- tion. We offer interpretations of these factors and suggestions for testing these and other factors in future research.
Student dishonesty on college campuses throughout the nation has been widely recognized as epidemic (“Cheating in College,” 1976; Wellborn, 1980). Although cheating has been noted by faculty and students alike, its occurrence does not appear to be on the decline. In fact, there seems to be general agreement that cheating is endemic to education in the secondary schools as well as at the college level. Methods of cheating often provide a study in creativity ranging from the sophisticated distribution of term papers through so-called paper mills, to devising ways of carrying informa- tion into the classroom, to the not-so-sophisticated means of looking at someone else’s paper during an exam. Since it is unlikely that those asso- ciated with academia for any length of time would deny the presence of student cheating, it is important to search for processes that underlie this behavior.
Correspondence to: Emily E. LaBeff, Division of Social and Behavioral Sciences, Midwest- ern State University, Wichita Falls, Texas 76308. Valerie J. Haines, George M. Diekhoff, and Robert E. Clark, Midwestern State University.
Research in Higher Education © 1986 Agathon Press, Inc. Vol. 25, No. 4
342
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COLLEGE CHEATING 343
Research into college student cheating has been diverse. Based on the premise that a majority of educators would like to identify those likely to cheat, numerous studies have attempted to discern those characteristics and circumstances which “predispose” some students to engage in this activity. Some important determinants that have been examined include the student’s sex, age, previous academic performance, class standing, academic major, fraternity-sorority membership, extracurricular involvement, as well as the student’s level of test anxiety. Although some significant correlations be- tween these variables and cheating have been reported, each has been found to rely on circumstances that vary from situation to situation. These moder- ating factors include the arrangement of seating during exams, as well as the importance and difficulty of the exam (Baird, 1980; Barnett and Dalton, 1981; Bronzaft et al., 1973; Fakouri, 1972; Harp and Taietz, 1966; Johnson and Gormly, 1972; Leming, 1980; Newhouse, 1982; Singhal, 1982; Stannord and Bowers, 1970). In addition to various demographic variables, Eve and Bromley (1981) reported cultural conflict and internal social control to have significant predictive ability with regard to college cheating. Students who were found to have high levels of cultural conflict were most likely to cheat on exams; those who demonstrated high levels of internalized social control cheated less.
Attention has also been directed toward the impact of administrative attitudes upon the occurrence of cheating on campus. According to one study (Singhal, 1982), most divisions within colleges vare not paying enough attention to the incidence of cheating, and when cheating is detected, they do not possess skills adequate to deal with the problehi. Bonjean and McGee’s (1965) comparison of the honor system versus the proctor system revealed the former to be more effective in controlling cheating. According to their findings, students in the honor system were more likely to possess a clear understanding of the rules regarding class dishonesty than were those students in classes where the proctor system was used. Such findings provide possible explanations for the higher rate of honest behavior.
In contrast, further study of the effects of social control by Tittle and Rowe (1973) demonstrated that moral appeal had little or no impact on cheating while the delivery of a sanctioned threat resulted in a significant decrease in cheating activity. According to the authors, “fear of a sanction is a more important influence than moral appeal in generating conformity to the norm of classroom honesty” (Tittle and Rowe, 1973, p. 492). In their final analysis of the data, the authors noted that those students with the lowest grades were least affected by threat of sanction. Such findings fit well within the framework of general deterrence theory according to which the greater the utility of an act, the greater the severity of punishment required for deterrence.
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344 HAINES ET AL.
Focusing on the identification of conditions under which select causal structures can influence cheating behavior, Liska (1978) found neutraliza- tion to be an important factor in college cheating. Neutralization, first defined by Sykes and Matza (1957), is similar to rationalization which can be used before, during, or after deviant behavior to deflect the disapproval of others and self. Liska employed various combinations of social processes (i.e., socialization, interpersonal social control, and social selection) com- bined with psychological processes (attitude impact on behavior) and found the concept of neutralization to be strongest in the absence of social control accentuations.
The present study was conducted with the following objectives in mind: (1) to describe the incidence of college cheating and further document its existence; (2) to examine the occurrence of cheating from within the frame- work of Sykes and Matza’s (1957) neutralization theory; (3) to identify demographic as well as personal characteristics of students who cheat; and (4) to search for the fundamental factors underlying cheating behavior. This latter goal is the primary focus of this report.
METHODOLOGY
Data were gathered through the completion of a 49-item questionnaire administered during the spring of 1984 to 380 undergraduate students at a small state university in the Southwest. The student population (N= 4,950) was unevenly distributed throughout the university’s programs, with a dis- proportionate number majoring in business administration. While our pri- mary concern was to use data collection techniques that would maximize the return rate, we also sought to secure a relatively representative sample in terms of major areas of study. Therefore, our questionnaire was adminis- tered only to those students enrolled in courses classified as part of the university’s required core curriculum. At the time of the study, a cursory examination of enrollment sheets of the classes used, which noted each student’s major, supported this strategy. However, subsequent analyses indi- cated that in our sample, freshmen and sophomores were overrepresented (84% of the sample versus 60% of the university population). Females were also slightly overrepresented (62% of the sample versus 55% of the univer- sity population).
There were obvious disadvantages associated with the use of self-adminis- tered questionnaires for data-gathering purposes. We were forced to accept student responses without the benefit of contest. In order to maximize the return rate, the questionnaire was administered during regularly scheduled class periods in which permission of the instructor had been secured. Par- ticipation was on a voluntary basis. In order to promote honesty of re-
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COLLEGE CHEATING 345
TABLE 1. Prevalence of Cheating
Type of Cheating Yes No
Cheated on major exams 23.7% (90) 76.3% (290) Cheated on daily/weekly quizzes 22. 1 % (84) 77.9% (296) Cheated on assignments 34.2% (130) 65.8% (250) Overall cheating measure (on ex-
ams, quizzes, or assignments) 54.1% (206) 45.9% (174)
sponses, students were encouraged to be as open as possible with a guaran- tee of complete anonymity. They were instructed to limit their responses regarding whether or not they had cheated to that academic year. This included the entire fall semester of 1983 and half of the spring semester of 1984.
The questionnaire required approximately 30 minutes to complete and forced-choice response categories were employed through most of the instru- ment. The questionnaire also contained items concerning demographic characteristics, the incidence of cheating in three forms (on major exams, quizzes, and class assignments), perceptions of and attitudes toward cheat- ing by other students, the effectiveness of several alternative deterrents to cheating, and an 11 -item neutralization scale.
Four pilot studies involving approximately 100 students were conducted during the initial planning stages of the project. Several problem areas were noted at that time, and appropriate changes were made in the questionnaire.
RESULTS
Extent of Cheating
As mentioned, three measures of cheating behavior were used in the instrument: cheating on major exams, on quizzes, and on class assignments. Table 1 shows the prevalence of cheating by each measure as well as the overall cheating score which involved cheating in any of the three forms. Slightly less than one-fourth of the students reported cheating on major exams or quizzes, whereas just over one-third reported cheating on class assignments. Nevertheless, when counting the total number of students who admitted cheating in any form, more than one-half (54.1%) of the students had cheated. This overall cheating measure was used in all subsequent analy- ses. It should be noted that this percentage is quite similar to the results obtained in other recent surveys of college cheating (Baird, 1980; Liska, 1978; Singhal, 1982). Also, in our study, only 1.3% of the students reported having ever been caught cheating.
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346 HAINES ET AL.
Cheating and Neutralization
In order to more fully understand the attitudinal processes involved in student cheating, we turned to the concept of neutralization of deviance first presented by Sykes and Matza in their important 1957 essay. We wanted to know whether or not neutralization was associated with cheating behavior and if students were, in essence, justifying their cheating behavior so as to provide protection “from self blame and the blame of others” (Sykes and Matza, 1957, p. 666).
Sykes and Matza discussed five specific types of neutralization: denial of responsibility, denial of the victim, denial of injury, condemnation of the condemners, and appeal to higher loyalties. In each case, the individual professes to support a particular societal norm or law but also recognizes special circumstances which allow or even require the individual to violate the norm or law. This neutralization process is presumed to free the individ- ual to deviate without considering himself or herself a deviant, thus elimi- nating or reducing the sense of guilt or wrongdoing. Each of these five types of neutralization were represented in 11 hypothetical situations adapted from Ball (1966). Responses of our sample to the items provided an indica- tion of the students’ tendency to neutralize. The 11 hypothetical statements and student’s Likert-type responses to each are summarized in Table 2 for cheaters and noncheaters.
An evaluation of the psychometric qualities of the neutralization scale showed very high internal consistency with all items showing item-total correlations greater than .64. The average inter-item correlation was .54. Split-half reliability, as measured by Cronbach’s alpha, proved to be very high (a= .93). Shortening the scale by eliminating any of the items would have reduced the reliability of the scale. Consequently, full-scale scores were used as our measure of neutralization.
As shown in Table 2, cheaters showed higher levels of neutralization (i.e., lower scores) on all 11 items of the neutralization scale. Total neutralization scores differed significantly between the two groups as well (/ = 6.90, df= 377, /?< .001). Given the importance of neutralization among cheaters, we further examined our data in ways designed to clarify the processes associated with neutralization and cheating. Correlations between neutral- ization scores and student’s ratings of the effectiveness of various deterrents to cheating were examined and found to be low, but statistically significant, and present a compelling pattern. As can be seen from Table 3, those who show high neutralization (i.e., low neutralization scores) are most deterred by the formal, institutional consequences of being caught cheating (i.e., threat of receiving an F, being dropped from the course, or fear of university reprisal). They are least deterred by guilt over cheating or disapproval of
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COLLEGE CHEATING 347
TABLE 2. Techniques of Neutralization: Cheaters vs. Noncheaters
Cheaters Noncheaters
Neutralizing Statements Mean SD Mean SD
1. The course material is too hard. No matter how much he studies, he cannot under- stand the material. 3.08 .62 3.44 .67
2. He is in danger of losing his scholarship due to low grades. 3.09 .67 3.42 .68
3. He doesn’t have time to study because he is working to pay for school. 3.04 .66 3.36 .67
4. The instructor doesn’t seem to care if he learns the material. 2.74 .79 3.17 .76
5. The instructor acts like his/her course is the only one he is taking. Too much mate- rial is assigned. 2.68 .75 3.16 .74
6. His cheating isn’t hurting anyone. 3.23 .65 3.47 .61
7. Everyone else in the room seems to be cheating. 2.96 .77 3.32 .75
8. The people sitting around him made no attempt to cover their papers and he could see the answers. 3.13 .64 3.39 .66
9. His friend asked him to help him/her cheat and Jack couldn’t say no. 3.01 .70 3.45 .66
10. The instructor left the room to talk to someone during the test. 2.97 .74 3.41 .69
11. The course is required for his degree, but the information seems useless. He is only interested in the grade. 2.98 .72 3.37 .69
Total Neutralization Scores 32.90 5.41 36.95 6.01 (t = 6.90, df= 377, /?<. 001)
friends, this guilt having been handled by neutralization. In short, neutral- izers seem to function at a relatively low level of moral development (Kohlberg, 1964), being concerned primarily with punishment and the reac- tions of authority figures.
Demographic Characteristics and Cheating
A comparison of the demographic makeup of cheaters and noncheaters
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348 HAINES ET AL.
TABLE 3. Correlations between Neutralization Scores and Cheating Deterrents
Deterrents Correlations
Family a- =.02 a? = 380 /7= .38
Friends r=.15 n = 38O p=.OO2
Guilt a- =.25 /7 = 38O p=.00\
Embarrassment a* =.03 a* = 380
p=.30 F for cheating r=.14
aj = 38O p=.002
Instructor drop r=.13 a? = 380 p=.005
Fear of university a* =.13 a? = 380 p=.005
(see Table 4) showed that cheaters tended to be younger, to be single, to have lower grade-point averages, to be receiving financial support from parents, and to be more involved in extracurricular activities such as intramural or
varsity sports and fraternities and sororities. If they worked at all, it was
generally on a part-time basis. Surprisingly, and in contrast to other recent research (Baird, 1980; Fa-
kouri, 1972; Johnson and Gormly, 1972), no significant differences between cheaters and noncheaters were found in relation to either sex or academic classification (i.e., year in school). It is possible, however, that our sample differed from those studied previously in that ours was heavily weighted with freshmen, sophomores, and females.
Age showed the most substantial correlation with cheating in that the
younger students were more likely to report cheating in any of the three forms. It might be that age has become more significant today as more nontraditional students are returning to college. Following age, involvement in intramural sports, lower GPA, and being single showed the strongest correlations with cheating. The correlations for the other variables, such as source of financial support and varsity sport involvement, were not substan- tial, but they were statistically significant.
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COLLEGE CHEATING 349
TABLE 4. Correlations between Demographic Characteristics and Cheating
Cheaters Noncheaters Variables Correlations (scored 1) (scored 0)
Age r=A0 M=20.3 M=25.6 /?<.001 (a? = 205) (/i =174)
Marital status r= – .33 p<.00\
Single (scored 0) 88.8% 60.9% (n =182) (a? =106)
Married (scored 1) 11.2% 39.1% (a? = 23) (a? = 68)
Grade-point average r=-.23 A/=2.54 M=2.84 /7<.001 (a? =179) (/f = 135)
Source of financial support a* =.17
/7<.OO5 Parents (scored 1) 37.6% 22.2%
(aj = 73) (aj = 34) Other source
(scored 0) 62.4% (/i =121) 77.8%
(« =119) Varsity sports a* =.12
/?<.005 Involved (scored 1) 6.3% 1.1%
(a? =13) (n = 2) Not involved
(scored 0) 93.7% 98.9% (/? =192) (/i= 172)
Intramural sports r= .27 /7<.001
Involved (scored 1) 26.8% 5.7% (a? = 55) (a? =10)
Not involved 73.2% 94.3% (scored 0) (a? =150) (a? =164)
Fraternity/Sorority r = . 1 7 /7<.OO5
Involved (scored 1) 19.5% 7.5% (a? = 40) (w =13)
Not involved 80.5% 92.5% (scored 0) (a? =165) (a? =160)
Employment status r= – .22 /7<.001
Less than full-time 82.0% 62. 1 % (scored 0) (a? =168) (a? =108)
Full-time 18.0% 37.9% (scored 0) (a? = 37) (n = 66)
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350 HAINESETAL.
TABLE 5. Stepwise Discriminant Analysis Comparing Cheaters vs. Noncheaters
Significance Variable Total Overall of Added
Step Entered % Variance Significance Predictor
1 Age 15.9 F(l,203) = 38.46 p<.00\
2 Neutralization 22.1 F(2,202) = 29.79 F(l,376) = 29.93 p<.001 p<.0\
3 Notice others cheating 25.4 F(3,201) = 24.47 F(l,375)= 16.59 p<.001 /?<.01
When considered together, these variables can be used as rough indicators of the maturity and commitment to academics on the part of the students. Tentatively, we can say that students who cheat tend to be immature and to show a lower level of commitment to academics in that their GPAs are lower. Additionally, they are more likely to be involved in nonwork, extracurricular activities.
An Overall Comparison of Cheaters and Noncheaters
A stepwise discriminant analysis (summarized in Table 5) was used to clarify the nature of the differences between cheaters and noncheaters. Age was selected on the first step. At step two, scores on the neutralization scale were entered and added significantly to the discrimination of cheaters and noncheaters (F(l,376) = 29.93, p<.0\). The fact that neutralization was se- lected prior to any of the other demographic variables (except age) suggests that although cheating does occur more frequently in some demographic groups than in others (as identified earlier), it is primarily because those demographic groups are more likely to neutralize their cheating behavior. Only age is as reliably and consistently related to cheating as is the neutraliz- ing attitude. Neutralization, it seems, is fundamental to cheating and can best be characterized as a common denominator for cheaters.
Although additional discriminating variables added little to discriminat- ing power, one variable, added at the third step of the discriminant analysis, is worth noting. At step three, the variable addressing the degree to which respondents noticed other students cheating was entered and added a small, but statistically significant margin of additional discrimination. This vari- able consisted of a Likert-type item, scored 1 to 5, on which cheaters indi- cated noticing more cheating (M=2.71, SD=.$$) than did noncheaters (M= 2.14, SD= .75). Singly, this variable showed a correlation with cheating of -.33.
The finding that cheaters see more cheating by others than do noncheaters is not surprising. Part of the neutralizing attitude displayed by cheaters toward their cheating behavior involves just this kind of justification:
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COLLEGE CHEATING 351
TABLE 6. Principal Components Analysis Summary Table: Varimax Rotated Factor Loadings”
Variables FI FII Fill
Age .72 Grade-point average .67 Neutralization .69 Marital status .74 Employment status .41 – .42 Fraternity/sorority .66 Notice others cheating .48 Varsity sports .51 Intramural sports .71 Parental financial support – .75
Eigenvalues 2.83 1.12 1.07 Percentage of variance 28.3 11.2 10.7
“Only loadings of .4 or greater are shown.
“Those around me are cheating, therefore it is fair for me to cheat in order to compete effectively.” Of course, in order to use this argument to justify their cheating behavior, cheaters may very well tend to perceive higher levels of cheating, either inaccurately, as a result of their projecting their own motives and actions onto others, or accurately, as a result of being sensitized and attuned to cheating behavior.
Factor Analysis of Variables Related to Cheating
The pattern of results presented thus far has led to the tentative conclu- sion that a limited number of fundamental factors underlie cheating behav- ior: immaturity, lack of commitment to academics, and a neutralizing atti- tude toward cheating. This conclusion was put to the test by factor-analyzing those variables found to be related to cheating behavior: age, grade-point average, neutralization scale scores, marital status (married vs. single), em- ployment status (full-time vs. less than full-time employment), membership in a fraternity or sorority, degree to which other students are noticed cheat- ing, involvement in varsity sports, involvement in intramural sports, and whether or not students were dependent upon parental financial support.
The results of this factor analysis (a principal components analysis with varimax rotation) are summarized in Table 6. Three factors with eigenvalues of 1.0 or greater were extracted, accounting for 50.4% of the total variance.
Factor I, accounting for 28.3% of the variance, was most strongly repre- sented by age, marital status, students’ dependence upon parental financial
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352 HAINESETAL
support, and employment status. Students showing high scores on Factor I were older, married, not dependent upon parents, and were employed full- time. Factor I was thus interpreted as reflecting maturity.
Factor II, accounting for 11.2% of the variance, was most strongly repre- sented by involvement in intramural sports, membership in a fraternity or sorority, involvement in varsity sports, and employment status. Those indi- viduals scoring high on Factor II were heavily involved in nonwork extra- curricular (i.e., “play”) activities that might distract from attention to aca- demics, e.g., sports and fraternities and sororities. Accordingly, Factor II was interpreted as reflecting students’ level of commitment to academics.
Factor III, accounting for 10.7% of the variance, was represented most strongly by neutralization scale scores, grade-point average, and the degree to which other students were perceived as cheating. Students showing high scores on Factor III tended not to neutralize (or cheat) because their grades were higher. Factor III was interpreted as mostly involving the neutralizing attitude.
DISCUSSION AND CONCLUSIONS
The primary purpose of this study was to identify basic factors underlying cheating in college. Given previous diverse research on cheating, it was important to look for fundamental forces in cheating as an end in itself. Three underlying factors were discovered: immaturity, lack of commitment to academics, and the neutralizing attitude.
Given that the cheater tends to be younger, single, and either unemployed or employed only part-time, and to be more involved in outside (“play”) activities, it can be suggested that he or she is more immature than the noncheater. This conclusion was also reflected by the cheater’s low level of moral development exhibited by a refusal to be deterred from cheating by anything other than the forces of formal social control.
A second factor related to cheating is the cheater’s lack of investment in his or her education. The students in this study who admitted cheating were less likely to have paid for their own tuition and books than were non- cheaters. Reliance on parents for financial support may lead cheaters to place less value on the formal aspects of an education than do their counter- parts who have made a greater personal financial investment.
It can be suggested that this factor plays a role in students’ perceived need to cheat. Given cheaters’ high level of participation in extracurricular activi- ties, it may be that they do not allow enough time to study and perhaps give studying a low priority. Also related to this factor is the cheater’s generally lower GPA. Cheaters may feel more pressure to cheat in order to maintain adequate grades.
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COLLEGE CHEATING 353
The third factor found to be related to cheating was neutralization. Atten- tion was focused on the application of Sykes and Matza’s (1957) techniques of neutralization to cheating activities. The use of such techniques conveys the message that students recognize and accept cheating as an undesirable behavior; however, its occurrence can be excused in certain instances. This approach enables those who cheat to do so with a clear conscience. The evidence suggests that under certain circumstances, cheaters neutralize so effectively that they really do not think cheating is wrong, either for them- selves or for others.
Given the continuing presence of cheating in the university setting, it is necessary to further test the salience of these three factors in more diverse university environments. Since our sample was limited to a small state uni- versity, it is important to examine factors in cheating in a wide range of institutions including prestigious private colleges, large state universities, and religious schools. Additionally, cross-cultural studies of cheating might prove especially useful in identifying broader societal forces underlying cheating behavior.
It is important to address broader research questions suggested by our study. For example, factors at the college level that can increase the maturity of the students might be investigated. What kind of environment can in- crease the maturity of students? Factors contributing to lack of commitment to academics and perhaps to student alienation from the learning process should be examined. What social forces contribute to lack of commit- ment? Moreover, the processes in learning neutralizing attitudes should be studied and integrated with the variety of work in the study of deviance. How do students learn to neutralize and what would deter it? We consider these questions to be of considerable importance to institutions of higher education.
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354 HAINES ET AL.
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Received September 3, 1986
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Article Contents
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p. 350
p. 351
p. 352
p. 353
p. 354
Issue Table of Contents
Research in Higher Education, Vol. 25, No. 4 (1986), pp. 307-396
Volume Information
Front Matter
Tenure, Retirement, and the Year 2000: The Issues of Flexibility and Dollars [pp. 307-315]
Preferred Directions and Images for the Community College: A View from Inside [pp. 316-327]
Characteristics of Graduate Students in Biglan Areas of Study [pp. 328-341]
College Cheating: Immaturity, Lack of Commitment, and the Neutralizing Attitude [pp. 342-354]
Supply and Demand of Doctorates in Economics [pp. 355-364]
Using Discriminant Analysis to Predict Faculty Rank [pp. 365-376]
Work and Life Away from Work: Predictors of Faculty Satisfaction [pp. 377-394]
Back Matter
