ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
1
W1.2
Assessing the understanding of academic integrity of university students
Justin Louder, Ed.D.
Marcelo Schmidt, M.Ed.
Paper presented at the annual meeting of the Southwest Educational Research Association, San
Antonio. February 6, 2013 (3:00 - 4:15).
ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
2
ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
Abstract
Educational institutions must remain vigilant of the academic integrity of their students. It is
thus, paramount that student perceptions, knowledge and practices pertinent to academic
integrity be assessed periodically. The current study assessed the understanding of academic
integrity of university students by academic classification and gender. Archival data retrieved
from a 12-item survey based on the university’s stated academic integrity policies was used.
Specifically, we examined items in which students collectively underperformed and those that
have been supported by the literature as being historically problematic (i.e., plagiarism and
collusion). Logistic regression was used to analyze each survey item considering gender,
classification, and student age as predictors. The data analysis indicated that gender is a predictor
of understanding of academic integrity. We did not find that classification nor student age were
significant predictors of understanding of academic integrity. Previous studies have suggested
that male students are more prone to infract on academic integrity. We suggest that this may be
in part, due to a lack of clear understanding of certain items within academic integrity.
Key words: Academic integrity, university students, student knowledge
3
ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
Introduction
Educational institutions concerned with high ethical standards and practices must remain
vigilant over the academic integrity of their students. Despite efforts to ameliorate academic
integrity on university campuses, academic dishonesty remains a complex and widespread
problem. In assessing the extent of academic dishonesty, a few scholars have concluded that the
incidence of such has been increasing (e.g., McCabe & Trevino, 1997), reaching “epidemic”
proportions (Hutton, 2006, p. 171), and may continue to escalate if not properly addressed (Estep
& Olson, 2011). Others, however, contend that the number of students committing academic
infractions has remained rather stable over time (Whitley, Bichlmeier, & Jones, 1999; Brown &
Emmett, 2001). Regardless of the trend, it is collectively accepted that academic dishonesty is
pervasive (McCabe, Trevino, & Butterfield, 2001) and has become sufficient of a problem to
merit attention from university educators and administrators. In doing so, academic integrity
policies have been established as a means to uphold professional and ethical standards, guard the
values of integrity, and prevent further occurrences academic dishonesty among students.
However, a myriad of changes in cultural and moral values, advances in technology and
instructional delivery, and faculty attitudes make the matter of academic integrity one which
must be constantly reassessed. Over the past three decades scientific inquiry on the topic of
academic integrity has grown exponentially with the core of research focusing on identifying
student cheating modalities, on the demographics characteristics of those who cheat, and on the
reasons why students choose to engage in in dishonest academic behavior.
4
ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
Literature Review
Student violations of academic integrity take up several forms. Currently, it appears that
collusion and plagiarism may be among the most common forms of academic dishonesty. In a
review of cheating in academic institutions, McCabe, Treviño and Butterfield (2001) identified
that between 1963 and 1996, plagiarism was consistently the highest self-reported form of
academic dishonesty. Achey Kidwell, Wozniak, and Laurel (2003) found that from a sample of
students who self-reported cheating patterns, the majority (47%) engaged in plagiarism, followed
by collusion (46.7%), and illegally obtaining questions prior to taking an exam (45.8%). A
similar trend was found by Whitley (1998) when reviewing over 100 studies on academic
dishonesty. Among the studies reviewed by Whitney (1998), nine studies addressed plagiarism
and had a prevalence range of 3% to 98% with a mean of 47%. While 36 studies examined the
prevalence rates in cheating during examination and in homework reporting a range of 4% to
82% (M= 43.1%) and 3% to 83% (M=40.9%) respectively. It appears that plagiarism from
digital sources is more problematic than from printed press (Ellery, 2008) and that its practice
may be on the rise (Park, 2004).
A substantial amount of research has been focused on identifying demographic
characteristics of students who commit academic integrity infractions. It is paramount to the
proper implementation of preventive measures and interventions. Several studies have assessed
gender differences and academic integrity with a focus on incidence, type of infractions
committed, and reasons for engaging in academically dishonest behaviors. Evidence from these
studies suggests that male students exhibit more troubling patterns relative to academic integrity.
This propensity has been identified as early as half a century ago (Bowers, 1964) and has been
documented repeatedly since then. For example, Davis, Grover, Becker, and McGregor (1992)
5
ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
surveyed over 6,000 students throughout several high schools and colleges finding that female
self-reported cheating prevalence ranged from 9% to 51% while male self-reported cheating
prevalence was reported ranging from 64% through 83% across schools. A difference in
academic dishonesty by gender was found to be true in discipline specific studies as well.
Chapman and Lupton (2004) found that from a sample of 443 American business students,
cheating self-reports were approximately 66% for male and a substantially reduced 45% for
female students. And while the bulk of studies on academic dishonesty has involved American
students, male prevalence transcends nationalities and has been identified in Canadian (Genereux
& McLeod, 1995), Japanese (Kobayashi & Fukushima, 2012), and Taiwanese (Lin & Wen,
2007) collegiate students. What may appear to solidify this notion of male propensity is the
detection of differences in academic integrity by gender observed in experimental designs. One
such study conducted by Niiya, Ballantyne, North and Crocker (2008) reported instances of
cheating at 71% and 41% for males and females respectively in controlled laboratory conditions.
It should be noted, however, that a few studies have not detected gender differences
relative to academic dishonesty. For example a study by Haines, Diekhoff, LaBeff, and Clark
(1986) examined self-reported cheating behaviors of university students during exams, quizzes,
and class assignments and found no difference between genders. Haines and colleagues (1986)
however, cautioned that the sample of female students was overrepresented in their study and
that this may have influenced their results. Favoring this no difference position is a metaanalytic study that considered gender differences on attitudes toward academic dishonesty and
actual instances of academic dishonest behavior. The meta-analysis found that gender differences
in attitude towards academic dishonesty were large with female students exhibiting higher
standards of honesty yet a gender difference in actual behavior was small or non-existent when
6
ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
controlling for certain study variables (i.e., observation vs. self-reported; student major; Whitley,
Bichlmeier, & Jones, 1999). Further, some studies have found mixed findings according to
gender and cheating modalities. When investigating traditional cheating modalities, fraudulent
excuse making and plagiarism, Roig and Caso (2005) found male prevalence in traditional
cheating and fraudulent excuse making yet non-significant differences between male and female
students in instances of plagiarism.
In addition to gender, other student demographics that have merited extensive study are
age and student classification. Yet, similarly to gender differences, findings regarding age and
classification have been relatively equivocal. The dominant trend of findings appears to suggest
that younger students engage in cheating more so than older students (Haines et al., 1986; Klein,
Levenburg, McKendall, & Mothershell, 2007). Also, studies have identified that freshman
students are considered to be within the most dishonest academic classification (Lin & Wen,
2007). Thus, it may be concluded that age exacerbates the incidence of academic dishonesty.
Surprisingly, however, graduate students are not exempt from cheating nor do they represent a
small portion of those engaging in academic dishonesty and the incidence of cases is similar to
that of undergraduate student populations. In a study focusing on graduate student cheating
behaviors, Zastrow (1970) found that 40% of students in a sample had been identified as
cheaters. Self-reported incidence of cheating of graduate students was recorded between 2.5%
and 55.1% (Wadja-Johnston, Handal, Brawer, & Fabricatore, 2001)
There are several reasons or factors that influence student propensity to engage in
academic dishonesty. Often cheating is accompanied by “neutralizing techniques” such as
rationalizing academic dishonesty or denial (McCabe & Treviño, 2001; p. 227). Moral attitudes
(Grimes, 2004); laziness (e.g., McCabe, Travino, & Butterfield, 1999; Newstead, Franklyn-
7
ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
Stokes, & Armstead, 1996), differences in institutional control (e.g., Davis, Grover, Becker, &
McGregor, 1992; Diekhoff et al., 1996; McCabe & Trevino, 1997; McCabe, Trevino, &
Butterfield, 2002; Roig & Marks, 2006); cultural differences (e.g., Chapman & Lupton, 2004;
Grimes, 2004); fulltime versus part-time academic enrolment (Smyth & Davis, 2003); and
student’s knowledge and understanding of what constitutes academic integrity (Brimble &
Stevenson-Clark, 2005).
Studies have indicated that some students do not perceive that certain instances of
academic dishonesty actually constitute academic integrity infractions. This may in part be due
to a lack in understanding of what constitutes academic misconduct. As such, it has been
suggested that understanding academic integrity policies may be central to the problem of
academic dishonesty (McCabe & Trevino, 1993).
Several studies have indicated that few
students have adequate knowledge of the university’s academic integrity policies (e.g.,
Spaulding, 2009).
This lack of understanding has been manifested by student failure to
appropriately identify instances of academic misconduct in surveys (McCabe & Trevino, 1993;
Brimble and Stevenson-Clarke, 2005). In a study examining the effect of student understanding
of the stated academic policies, McCabe, Butterfield & Treviño (2006) found that understanding
and acceptance of the academic policies was inversely related to academic misconduct. Despite
this, a dearth of studies has sought to assess student understanding of academic integrity policies
(Jordan, 2001). Thus, the purpose of our study was to contribute to the body of literature
pertinent to collegiate student understanding of academic integrity. We hypothesized that in
agreement with current literature we would find that a) gender would be a predictor of
understanding of academic integrity, and b) that student academic classification would predict
8
ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
understanding of academic integrity as evidenced in our understanding of academic integrity
survey.
Methodology
For this study, archival data from a study that was conducted at a large university located
in the southwestern region of the United States was used. Students had completed surveys during
a student-centered event which had as a purpose to bring about awareness of academic integrity
among the student population. A total of 1150 surveys were completed and used in the
quantitative analysis. In order to assess student understanding of academic integrity, a 12
question survey based on the academic integrity survey designed by Dr. Donald McCabe and
reflective of academic integrity stated policies of the university was created. Questions were
presented to students in a ‘true and false’ format; however they were subsequently coded as ‘1
and 0’ (i.e. a correct identification equals one point and incorrect identification equals zero
points) for purposes of statistical analysis. Upon inspection of the survey results, it was
determined that students exhibited understanding difficulties on items 8, 11, and 12 which
pertain to fraudulent excuse making respectively (see appendix A for survey items). Driven by
present literature that indicates that students may not fully understand the concept of plagiarism
(e.g., McGregor & Williamson, 2005), we also analyzed survey item 6 which pertains to
plagiarism. Given the categorical binary nature of the data, we analyzed each survey item with
binary logistic regression. Statistical analyses were conducted using SPSS V. 20.
Results
Descriptive statistics indicated that there were a total of 1049 student participants of
which, 17.8% reported their academic classification as freshman, 18.8% as sophomore, 20.1% as
9
ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
10
junior, 21.5% as senior, and finally, 21.5% as graduate students with an average age of 22.08
years with a range of 18 through 54 years. In terms of gender, 62.3% reported as female and
37.7% reported as being male.
Insert table 1 about here
First we examined item 8 of the survey “It is cheating to obtain questions or solutions for
a test before taking it without having permission from your professor”. This statement was
identified correctly by 88% of the survey respondents. The logistic regression model indicated
that gender was a significant predictor of identifying the statement correctly (b = .574, p < .01).
The odds ratio for gender indicated that female students were 1.77 times more likely than male
students to identify the statement correctly (See table 2). The variables classification and age
were not found to be significant predictors of correctly identifying this statement.
Table 2.
Logistic Regression for Obtaining Solutions for a Test Prior to Taking it.
95% CI for Odds Ratio
B(SE)
Lower
Odds Ratio
Constant
1.88 (0.87)
Gender
.574* (0.21)
1.17
1.78
Note: * p < .01. R2 = (Cox & Snell), .01.
Upper
2.68
Our second logistic regression model examined survey item 11 which seeks to capture
student understanding of collusion. The statement “It is ok to collaborate with other students on
academic assignments without having permission from your professor” was identified correctly
by 70% of the respondents thereby becoming the survey item with which students exhibited the
most difficulty in identifying correctly. Gender was found to be a significant predictor for
identifying the collusion statement correctly (b = .536, p < .001). No other variables were found
to be significant predictors of correctly identifying the collusion statement.
ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
11
Table 3.
Logistic Regression for Collusion.
95% CI for Odds Ratio
Odds Ratio
B(SE)
Lower
Upper
Constant
1.88 (0.87)
Gender
.536* (0.15)
1.27
1.70
2.30
Note: * p < .001. R2 = (Cox & Snell), .018. Model λ2 (6) = 16.53, p < .01
While item 12 pertaining to fraudulent excuse making was identified correctly by 88% of
students, indicating that more than 10% of students exhibited difficulties with understanding the
statement, the logistic regression model did not identify any variable predictive of identifying
this survey item correctly. However, with item 6 of the survey which pertains to plagiarism, the
logistic regression model indicated that gender was a significant predictor of correctly
identifying this statement (b = 1.51, p < .001). The odds ratio suggested that female students
were 3.16 more likely to identify this statement correctly. As with all previous models, neither
student classification nor age was found to be significant predictors.
Table 4
Logistic Regression for Plagiarism.
95% CI for Odds Ratio
Odds Ratio
B(SE)
Lower
Constant
1.23 (1.35)
Gender
1.15* (0.51)
1.71
3.16
2
2
Note: * p < .001. R = (Cox & Snell), .01 Model λ (6) = 17.54, p < .01
Upper
5.84
Discussion
The importance of student understanding and acceptance of academic integrity policies
have been identified as central to curbing the incidence of academic dishonesty. However, a
dearth of literature addressing the matter of student understanding of academic integrity policies
exists. Thus, we sought to contribute to the body of literature in this area by assessing
understanding of academic integrity policies of a large group of students using archival data. We
particularly focused on student demographics which is characteristic of the research in this area.
ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
Gender was found to be predictive of correctly identifying academic integrity policy statements
with female students consistently being more likely to identify the statements correctly. We
proffer, with caution, that correctly identifying academic integrity policy statements
demonstrates understanding of such statement. Nearly half a century of research has identified
male propensity to infract upon academic integrity. This propensity has been attributed to males
having more favorable attitudes toward cheating (Whitley et al., 1999) such as academic
dishonesty being an acceptable practice (Lin & Wen, 2007). Given our findings, we suggest that
a lack of clear understanding of academic integrity may contribute to male propensity.
Students in lower classification (e.g., freshman, sophomore) may be more prone to
engage in academic dishonesty (Vandehey, Diekhoff, & LaBeff, 2007). Nonis and Swift, (2001)
found this trend to be true of younger students as well. While this may be true to propensity to
engage in academic misconduct, we suggest that this may not necessarily be a product of
misunderstanding of academic policies as our study found that academic classification was not a
predictor of understanding of academic integrity policies.
Regarding the specific survey items that this study examined, survey item eight
pertaining to students obtaining answers to an exam prior to taking it has been identified in the
literature as a high incidence form of academic misconduct. McCabe (2005) in a summary of
findings of students in North America, including the United States and Canada, found that from a
sample of over 70,000 undergraduate students and over 20,000 graduate students 64% and 79%
respectively perceived obtaining answers to an exam prior to taking it a serious offense while
33% of undergraduate students and 17% of graduate students reported engaging in this type of
cheating. Our study found that 88% of students correctly identified this type of academic
dishonesty. While this suggests that there may be a lack of understanding relative to this
12
ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
cheating modality, we also consider that students may simply be challenging the statement as
they may not perceive this type of cheating to be severe.
Collusion, assessed by survey item 11, has been identified by previous studies as a form
of academic dishonesty that is problematic for students to understand. It appears that students
struggle with identifying a difference between legitimate acceptable collaboration and
unacceptable collusion (Barrett & Cox, 2005). Barrett and Cox (2005), in fact found low student
response to a collusion scenario compared to other academic dishonesty scenarios presented to
students and the most amount of variance in terms of responses to the collusion scenario
including that collusion is a beneficial practice to engage in. In similar manner, our study found
the lowest correct identification to the collusion survey item (70.3%) suggesting that there may
indeed be a lack of clear understanding of what collusion constitutes and how students interpret
the severity of collusion as a form of academic misconduct.
Our study found that slightly over 10% of the student sample failed to correctly identify
survey item 12 which assessed the use of fraudulent excuse making by students. However, the
analysis did not find gender, student classification or age to be predictors of understanding of this
prompt. Roig & Caso (2005) who specifically studied fraudulent excuse making by students
found that while there was a male propensity in this form of academic misconduct, female
students were found to express more varied excuses, whether legitimate or not relative to male
students. While this does not suggest gender parity in this form of academic misconduct, it does,
however propose a trend that may offer a glimpse for why no gender differences were found in
our study. We do make the recommendation that fraudulent excuse making should be explained
further to students in general.
13
ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
Finally, given the pervasiveness of plagiarism facilitated by internet copy and paste
functions, we decided to examine one item pertinent to this form of academic dishonesty.
Understanding or misunderstanding of what plagiarism represents has been found to be a culprit
cited by students caught having plagiarized. For instance, Ellery (2008) noted that of 39 first
year college English students who submitted plagiarized essays, 21 admitted having plagiarized
inadvertently rather than by dishonest means. Selwyn (2008) within the qualitative data of his
study on plagiarism found a “mismatch between students’ understandings of online plagiarism
and the understandings and expectations of university authorities” (Selwyn, 2008, p. 476).
While our survey revealed a relatively high (94%) level of understanding as exhibited by correct
identification of the plagiarism prompt, we still looked for trends related to gender, classification,
and age. Our analysis did not find classification or age trends, yet it revealed that female students
were nearly three times more likely to identify the statement correctly thus revealing a higher
level of understanding pertinent to this type of academic misconduct.
The findings in our study confirm our first hypothesis suggesting that gender would
predict understanding of academic integrity policies.
However, our second hypothesis
suggesting that academic classification would be a variable predictive of understanding of
academic integrity policies was not confirmed. Yet, from these findings, we proffer that as
institutions striving to design and implement adequate interventions to minimize the incidence of
academic misconduct must focus on providing students, particularly male students, clear
definitions of what constitutes academic misconduct and that this instruction should be followed
with a check for understanding.
14
ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
References
Barrett, R., & Cox, A. L. (2005). ‘At least they’re learning something’: the hazy line between
collaboration and collusion. Assessment & Evaluation in Higher Education, 30(2), 107122.
Brimble, M., & Stevenson-Clarke, P. (2005). Perceptions of the prevalence and seriousness of
academic dishonesty in Australian universities. The Australian Educational Researcher,
32(3), 19-44.
Brown, B.S., & Emmett, D. (2001) Explaining variations in the level of academic dishonesty in
studies of college students: Some new evidence. College Student Journal, 35(4), 529538.
Bowers, W. J. (1964). Student dishonesty and its control in college. New York: Bureau of
Applied Social Research, Columbia University.
Chapman, K. J., & Lupton, R. A. (2004). Academic dishonesty in a global educational market: A
comparison of Hong Kong and American university business students. International
Journal of Educational Management, 18(7), 425-435.
Davis, S. F., Grover, C. A., Becker, A. H., & McGregor, L. N. (1992). Academic dishonesty:
Prevalence, determinants, techniques, and punishments. Teaching of Psychology, 19(1),
16-20.
Davis, S.F., & Ludvigson, H.W. (1995). Additional data on academic dishonesty and proposal
for remediation. Teaching of Psychology, 22(2), 119-121.
15
ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
Diekhoff, G. M., LaBeff, E. E., Clark, R. E., Williams, L. E., Francis, B., & Haines, V. J. (1996).
College cheating: Ten years later. Research in Higher Education, 37(4), 487-502.
Ellery, K. (2008). An investigation into electronic‐source plagiarism in a first‐year essay
assignment. Assessment & Evaluation in Higher Education, 33(6), 607-617.
Estep, H.M., & Olson, J.N. (2011). Parenting style, academic dishonesty, and infidelity in
college students. College Student Journal, 45(4), 830-838.
Genereux, R. L., & McLeod, B. A. (1995). Circumstances surrounding cheating: A questionnaire
study of college students. Research in Higher Education, 36(6), 687-704.
Grimes, P. W. (2004). Dishonesty in academics and business: A cross-cultural evaluation of
student attitudes. Journal of Business Ethics, 49(3), 273-290.
Haines, V. J., Kiekhoff, G. M., LaBeff, E. E., & Clark, R. E. (1986). College cheating:
Immaturity, lack of commitment, and the neutralizing attitude. Research in Higher
Education, 25(4), 342-354.
Hutton, P. (2006). Understanding student cheating and what educators can do about it. College
Teaching, 54(1), 171-176.
Kobayashi, E., & Fukushima, M. (2012). Gender, social bond, and academic cheating in Japan.
Sociological Enquiry, 82(2), 282-304.
Lin, C., & Wen, L. (2007). Academic dishonesty in higher education: a nationwide study in
Taiwan. Higher Education, 54, 85-97.
16
ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
McCabe, D. L. (2005). Cheating among college and university students: A North American
perspective. International Journal for Educational Integrity, 1(1), 10-11.
McCabe, D.L., & Trevino, L.K. (1997). Individual and contextual influences on academic
dishonesty: A multicampus investigation. Research in Higher Education, 38(3), 379-396.
McCabe, D.L., Trevino, L.K., & Butterfield, K.D. (1999). Academic integrity in honor code and
non-honor code environments: A qualitative investigation. The Journal of Higher
Education, 70(2), 211-234.
McCabe, D.L., Trevino, L.K., & Butterfield, K.D. (2001). Cheating in academic institutions: A
decade of research. Ethics & Behavior, 11(3), 219-232.
McCabe, D.L., Trevino, L.K., & Butterfield, K.D. (2002). Honor codes and other contextual
influences on academic integrity: A replication and extension to modified honor code
settings. Research in Higher Education, 43(3), 357-378.
McCabe, D. L., Butterfield, K. D., & Trevino, L. K. (2006). Academic dishonesty in graduate
business programs: Prevalence, causes, and proposed action. Academy of Management
Learning & Education, 5(3), 294-305.
McGregor, J. H., & Williamson, K. (2005). Appropriate use of information at the secondary
school level: Understanding and avoiding plagiarism. Library & Information Science
Research, 27(4), 496-512.
Newstead, S. E., Franklyn-Stokes, A., & Armstead, P. (1996). Individual differences in cheating.
Journal of Educational Psychology, 88(2), 229-241.
17
ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
Niiya, Y., Ballantyne, R. North, M. S., Crocker, J. (2008). Gender, contingencies of self-worth,
and achievement goals as predictors of academic cheating in a controlled laboratory
setting. Basic and Applied Social Psychology, 30, 76-83.
Nonis, S., & Swift, C. O. (2001). An examination of the relationship between academic
dishonesty and workplace dishonesty: A multicampus investigation. Journal of Education
for Business, 77(2), 69-77.
Roig, M., & Marks, A. (2006). Attitudes toward cheating before and after the implementation of
a modified honor code: A case study. Ethics and Behavior, 16(2), 163-171.
Roig, M., & Caso, (2005). Lying and cheating: Fraudulent excuse making, cheating, and
plagiarism. The Journal of Psychology, 139(6), 485-494.
Selwyn, N. (2008). ‘Not necessarily a bad thing…’: a study of online plagiarism amongst
undergraduate students. Assessment & Evaluation in Higher Education, 33(5), 465-479.
Smyth, L. M., & Davis, J. R. (2003). An examination of student cheating in the two-year college.
Community College Review, 31(1), 17-32.
Spaulding, M. (2009). Perceptions of academic honesty in online vs. face-to-face classrooms.
Journal of Interactive Online Learning, 8(3), 183-198.
Vandehey, M.A., Diekhoff, G.M., & LaBeff, E.E. (2001). College cheating: A twenty-year
follow-up and the addition of an honor code. Journal of College Student Development,
48(4), 468-480.
Wadja-Johnston, V. A., Handal, P. J., Brawer, P. A., & Fabricatore, A. N. (2001). Academic
dishonesty at the graduate level. Ethics & Behavior, 11(3), 287-305.
18
ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
Whitley, B. E. (1998). Factors associated with cheating among college students: A review.
Research in Higher Education, 39(3), 235-374.
Whitley, B. E., Bichlmeier, N., & Jones, C. J. (1999). Gender differences in cheating attitudes
and classroom cheating behavior: A meta-Analysis. Sex Roles, 41(9/10), 657-680.
Zastrow, C. H. (1970). Cheating among college graduate students. The Journal of Educational
Research, 64(4) 157-160.
19
ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
APPENDIX A
Academic Integrity Survey
1. Academic Integrity means that you are accountable for your own work.
2. Making a personal decision to adhere to the standards of ethical behavior is part of academic
integrity.
3. Ethical behavior and independent thought are important for achieving academic success.
4.
Trust and respect among students, faculty, and staff are essential components of education.
5. Academic Integrity is the foundation of professional and educational careers.
6. Don’t worry about plagiarism if you use the web; things from the web do not need to be
cited.
7.
Copying from another student or source during a test is cheating.
8. It is cheating to obtain questions or solutions for a test before taking it without having
permission from your professor.
9. Using materials from other sources and presenting it as your own work is plagiarism.
10. Not citing materials or ideas from other sources in your work is plagiarism.
11. It is ok to collaborate with other students on academic assignments without having
permission from your professor.
12. Submitting false information in order to get an extension on an assignment or to take a
quiz/test later is considered “misrepresenting facts” (e.g., a false doctors’ note).
20
ASSESSING UNDERSTANDING OF ACADEMIC INTEGRITY
APPENDIX B
Table 1. Descriptive Statistics of Study Variables
N
Frequency (%)
Obtaining solutions
1038
True
88.2
False
11.8
Collusion
1050
True
70.3
False
29.7
Fraudulent excuse making
1043
True
88.1
False
11.9
Plagiarism
1041
True
94.7
False
5.3
Gender
Male
379
62.3
Female
629
37.7
Classification
Freshman
180
17.8
Sophomore
190
18.8
Junior
203
20.1
Senior
221
21.8
Graduate
218
21.5
Age
M (SD)
22.08 (4.29)
21