Dr. Hart is Professor of Nursing, Jacksonville University, Jacksonville, Florida. Dr. Morgan is Director of Online Nursing, Baker College, Flint, Michigan.
The authors disclose that they have no significant financial interests in any product or class of products discussed directly or indirectly in this article. The authors thank Dr. Kathy Ingram and the Marilyn Repsher Center of Teaching and Learning at Jacksonville University for a grant supporting this research.
Presented as a poster at the Society of Teaching and Learning Conference, March 10–12, 2010, Statesboro, Georgia; and at the Annual Karen A. Reider Research/Federal Nursing poster session, November 16, 2009, St. Louis, Missouri.
Address correspondence to Leigh Hart, PhD, ARNP-BC, Jacksonville University, 2800 University Blvd. N, Jacksonville, FL 32211. E-mail: email@example.com.
Online registered nurse to baccalaureate in nursing (RN-BSN) degree completion programs continue to grow in popularity. The American Association of Colleges of Nursing reported that more than 390 programs offer at least part of the RN-BSN curriculum online (American Association of Colleges of Nursing, 2009). Online programs are convenient for the typical RN-BSN student. Many of these students work 12-hour shifts on rotating days of the week. This challenging schedule makes it difficult to attend traditional face-to-face classes. Online RN-BSN programs, many of which can be completed entirely online, allow students to continue their education without interrupting their employment.
Although the benefits of online RN-BSN programs are clear, this is a new and developing method of teaching and learning that has not been fully investigated. Is there an unearned advantage to taking a course completely online? Mullens (2000) defined academic dishonesty as “anything that gives a student an unearned advantage over another” (Mullens, 2000, p. 23). In a review of the literature, Harper (2006) found no CINAHL results for terms related to technology, nursing, cheating, dishonesty, online education, web-based education, or e-learning. The recent proliferation of online nursing programs, coupled with the lack of research on academic integrity in these programs, is a concern. Does lack of direct faculty visualization in online programs increase the occurrence of academic dishonesty? How do faculty know that the student registered for the course is the one doing the work?
Educational literature from other disciplines has raised concerns about online education. For example, Lanier (2006) compared 1,262 students in traditional and online criminal justice courses at a large state university. This study found more self-reported episodes of cheating in the online courses than in the traditional courses. The findings were similar to those in the existing academic integrity literature that showed higher reports of cheating among male students, single students, and students with lower grade point averages (Finn & Frone, 2004; Hughes & McCabe, 2006; Lanier, 2006; McCabe & Trevino, 1997; Rakovski & Levy, 2007). Typically, RN-BSN students do not fit this demographic profile. Most are female, married, and older than traditional college students.
Student evaluation is a concern in any type of education. Online courses, especially in programs that use online unproctored testing, magnify this concern. Strategies for maintaining academic integrity in online testing include the use of proctors, large randomized test banks, timed tests, and electronic devices (Hart & Morgan, 2009). Hollister and Berenson (2009) compared examination scores between proctored face-to-face tests and unproctored online tests and found no evidence of an increase in cheating in the unproctored testing environment. Additional research in the area of online students in RN-BSN education is warranted.
Donald McCabe has done extensive work on academic integrity. He recently examined academic integrity in nursing students through a multicampus sample of 1,098 students who were enrolled in traditional BSN, RN-BSN, accelerated, and graduate programs. Because of ethical issues and concerns inherent in the profession of nursing, McCabe (2009), like other researchers, expressed concern that academic dishonesty in the nursing classroom may be a precursor to clinical and workplace dishonesty (Bellack, 2004; Harper, 2006). McCabe (2009) stated that he anticipated finding less cheating among nursing students than among students in other professions; however, this is not what he found. McCabe (2009) found high rates of cheating in accelerated nursing programs and lower instances of cheating among students who were already licensed as RNs and pursing their baccalaureate degree (RN-BSN). However, this study did not compare online and traditional classroom cohorts of RN-BSN students. Academic integrity is a component of professional socialization in nursing, and faculty must seek ways to evaluate and promote this ethic in all forms of nursing education. McCabe recommended future research, conducted by nursing professionals, to verify his conclusions.
According to the Center for Academic Integrity (2009) website, “Academic integrity is a fundamental value of teaching, learning and scholarship. Yet, there is growing evidence that students cheat and plagiarize” (¶ 3). Online nursing education will continue to expand because of the convenience, accessibility, and academic potential of this delivery format. Understanding the effects of online education on academic integrity is an important challenge for both nursing educators and administrators.
Gallant and Drinan (2008) proposed a four-stage model for institutionalization of academic integrity. The four stages are: (1) recognition and commitment, (2) response generation, (3) response implementation, and (4) institutionalization. This model provided the framework for this study (Figure). Consistent with this model, the first stage, recognition and commitment, occurred when online nursing faculty began a dialogue about perceived differences in faculty-student interaction in traditional classroom and online settings. The faculty made a commitment to explore academic integrity in the online RN-BSN program. This study represents the second stage of this model, response generation. The study examined and described differences in academic integrity between an asynchronous online RN-BSN cohort and a traditional classroom RN-BSN cohort.
Figure. Model of Academic Integrity Institutionalization Based on Gallant and Drinan’s (2008) Model.
Design and Sample
The authors performed a comparative descriptive study of self-reported academic integrity in online and traditional classroom RN-BSN programs. The two programs had the same courses, taught by many of the same faculty. The objectives, textbooks, assignments, and content of the two programs were identical. The primary differences between the two samples were the method of content delivery and the testing environment. The online courses were asynchronous, with no required campus events, and included unproctored online testing. The traditional classroom cohort attended face-to-face classes and predominantly had proctored paper-and-pencil testing. The study sample included RN-BSN students from a private liberal arts university who graduated or attended classes during the 2008–2009 academic year. The study was reviewed and approved by the university institutional review board. Students who met the inclusion criteria were sent an informed consent form by e-mail that explained the purpose of the research and requested their participation. The e-mail consent form explained that participation in the study was voluntary and would not affect their academic standing. It further explained that the survey was anonymous and that the researchers could not identify students who submitted responses. The e-mail contained a link to a secured survey on the Survey Monkey platform.
The instrument used in this study was the Donald McCabe academic integrity survey. McCabe has done extensive work in the area of academic integrity and developed a survey that has been used in numerous university settings (McCabe, 2009; McCabe, Trevino, & Butterfield, 2001). The survey contains questions about where students obtain information on academic policies in their program and how they rank the effectiveness of these policies. Additional Likert scale items explored students’ perception of the frequency of cheating in their program and how they would rank the severity of penalties for cheating. Students were asked to rank the seriousness of different forms of cheating, as well as how often they had participated in different forms of cheating, whether they had witnessed another student cheating, and whether they had ever reported another student for cheating. Because of the unique demographics of the RN-BSN program, the survey was modified slightly, with the approval and assistance of Dr. McCabe, to explore specific characteristics of this student population. Table 1 contains topics omitted from the original survey and topics added for this study. An additional open-ended question was added to the original McCabe survey to explore why RN-BSN students choose either an online or a traditional classroom RN-BSN program.
Table 1: Survey Modification
Statistical analysis was performed using the PASW (formerly SPSS) statistical software program. Descriptive statistics were used to summarize the demographic data and survey responses. Chi-square analysis was computed for dichotomous data, and independent sample t tests, assuming unequal variances, were computed on scaled items, including individual Likert items. The significance level was set at p ≤ .05. Significance levels for Fisher’s exact test were reported when chi-square analysis included low expected cell frequencies (more than 20% of cells with expected frequencies of less than 5).
The traditional classroom cohort consisted of 100 students, and the online cohort consisted of 2,048 students. Forty-four students (44%) from the traditional classroom cohort and 330 students (16%) from the online cohort completed the survey. The traditional cohort students all resided in the same region of the Southeastern United States, whereas the online cohort consisted of students located throughout the United States and internationally.
Table 2 summarizes the demographic characteristics of both samples. A chi-square test of independence was calculated comparing age, marital status, race, gender, grade point average, and plans for graduate school for both the online and traditional classroom samples. A significant relationship was found between age and group membership. Respondents in the online group were older than those in the traditional classroom group (χ2 = 5.32, df = 1, p = .02). Overall, respondents in both groups were predominantly White, female, and married. Many of the respondents in both groups indicated that they wanted to continue their education in graduate school.
Table 2: Demographic Characteristics of the Sample, by Type of Program
RN-BSN students who were enrolled or who graduated in the 2008–2009 academic year were sent e-mail requests to complete the survey. Because the online program had a much larger enrollment than the traditional classroom program, the sample sizes were unequal. In addition to the unequal sample sizes, because self-reported cheating was so low in both groups, data were highly skewed. In addition, few students in either group were in the traditional college age group of 18 to 24 years. Therefore, age and cheating behaviors were transformed into dichotomous variables and nonparametric analysis was used for some comparisons.
Policies and Perceptions
Overall, both groups reported very low levels of cheating and very high standards of academic integrity. Independent samples t test, assuming unequal variance, indicated no significant difference between the two groups with regard to how frequently they thought the following occurred in their program: plagiarism on written assignments [t(51) = 0.514, p = .61]; inappropriately sharing work in group assignments [t(52) = 0.237, p = .24]; or cheating during tests or examinations [t(53) = 1.710, p = .09]. The online students reported a higher mean for understanding campus policies concerning student cheating [t(46) = 3.370, p < .01] as well as for student support of these policies [t(44) = 2.810, p < .01]. Interestingly, even though the two groups reported differences in knowledge of academic integrity policies, there was no difference in how the two groups ranked the severity of penalties for cheating [t(44) = 0.964, p = .34].
Significant differences were found between the groups in their attitudes toward specific behaviors that they considered serious. Online students were more likely than traditional classroom students to identify the following behaviors as serious violations of campus policy: working with other students on assignments that were not intended to be group assignments (χ2 = 19.000, df = 3, p < .01); working with other students on assignments via e-mail or instant messaging (χ2 = 8.250, df = 3, p = .04); obtaining answers to test questions from someone who had already taken the test (χ2 = 21.670, df = 3, p < .01); copying from another student during a test without that student’s knowledge (χ2 = 12.800, df = 3, p < .01); copying another student’s homework (χ2 = 11.700, df = 3, p < .01); and receiving unpermitted help on assignments (χ2 = 10.600, df = 3, p = .01).
There were differences between the groups in how much information they obtained about academic integrity policies from different available sources. The online students indicated that they learned more about academic policies than the traditional classroom students reported learning from orientation (χ2 = 18.200, df = 2, p < .01), the program website (χ2 = 47.700, df = 2, p < .01), or the student handbook (χ2 = 12.500, df = 2, p < .01). There was no difference between the two groups in how much they learned about these policies from faculty or other students.
When asked whether they had participated in specific cheating behaviors, both groups noted very little self-reported cheating. Cheating behaviors were divided into behaviors that require collaboration and behaviors that can be accomplished alone (Tables 3 and 4). A three-dimensional cross tab analysis was computed for each specific cheating behavior by group (online or traditional classroom) and age (40 years and younger and 41 years and older). The traditional classroom group reported more instances of getting test questions from someone who had already taken the test for both participants 40 years and younger (χ2 = 40.000, df = 1, p < .01) and those 41 years and older (χ2 = 15.600, df = 1, p < .01). Both age groups in the traditional classroom cohort also reported more instances of working on an assignment with others (in person) when the instructor asked for individual work: among those 40 years and younger, χ2 = 19.500, df = 1, p < .01; among those 41 years and older, χ2 = 7.827, df = 1, p = .03. However, only the younger students in the traditional classroom group reported significantly more instances of this behavior using electronic methods, such as instant messaging or e-mail (χ2 = 19.500, df = 1, p < .01). The younger age group (40 years and younger) in the traditional cohort also reported significantly more instances of helping someone else cheat on a test (χ2 = 19.600, df = 1, p < .01). The younger students in the traditional classroom group reported more instances of paraphrasing or copying a few sentences from nonelectronic sources, such as books or journals, without appropriate references (χ2 = 6.300, df = 1, p = .01). The online group did not self-report more instances of cheating in any of the behavior categories. Most of the cheating behaviors that were reported at significantly higher rates in the traditional classroom group involved collaborative cheating behaviors (Tables 3 and 4).
Table 3: Percentage of Students Who Have Ever Participated in Collaborative Cheating Behaviors, by Age Group and Type of Program
Table 4: Percentage of Students Who Have Ever Participated in Independent Cheating Behaviors, by Age Group and Type of Program
Choosing an Online Program
An open-ended question asked the students what factors they considered when choosing between a traditional classroom program and an online RN-BSN program. The online students (n = 288) overwhelmingly cited flexibility, convenience, work schedules, family obligations, and lack of travel as their primary reasons for selecting an online program. The traditional classroom cohort (n = 28) listed the lower cost of the face-to face program, interaction with faculty, the motivational component of interacting face-to face with classmates, and being out of school for several years as factors that influenced their decision to attend a traditional classroom-based RN-BSN program.
The reported response rate for the McCabe academic integrity survey is 12% to 18% (McCabe, 2009). Although the online response rate was within this parameter (n = 330, 16%) it was much lower than the response rate for the traditional classroom group (n = 44, 44%). It is not known which factors prevented a large number of online students from participating, but these factors may certainly affect the findings. Despite assurances that faculty would be unable to track responses, students may have been concerned that providing honest answers to several sensitive questions may have exposed them to disciplinary action. Students were assured that all responses were anonymous, but they may have felt intimidated and thus may not have responded honestly. The increased participation from the traditional classroom cohort may be related to a more personal relationship with students and an increased willingness to participate in a faculty-initiated study. Additional limitations include the fact that the sample came from one program and the traditional classroom cohort came from one geographical area. Further limitations concern the unequal sample sizes and skewed data. These conditions limited the types of statistical analysis that could be performed.
Overall, both the online and traditional classroom RN-BSN students self-reported very low levels of cheating and very high standards of academic integrity. Both groups showed higher levels of academic integrity than were reported in previous studies of more traditional undergraduate students. These findings support McCabe’s (2009) postulation regarding the demographic profiles of nursing students and potential differences in various programs. McCabe stated that “students with an RN license and several years of experience may be so thoroughly socialized into the profession that issues of cheating are of less concern than they might be in other programs” (McCabe, 2009, p. 615).
Postlicensure nursing students are, as a group, primarily female, older, and established in clinical practice; they have a unique profile compared with traditional undergraduate students. Further, nursing, like all medical specialties, has a high level of ethical practice inherent in the profession. Postlicensure students not only have the benefit of learning expected standards of ethical behavior in their associate’s degree in nursing program but also practice this behavior daily. Ethical behavior is an important component of nursing practice, and this behavior is supported by nurses’ professional peers. A departure from ethical behavior often results in adverse situations for patients. This may explain why cheating was more prominent in the younger traditional classroom cohort. Future studies should include the number of years of nursing practice to evaluate this connection.
An additional factor to consider in the demographic component of this study is that more than 45% of both samples indicated that they plan to continue their education to pursue a graduate degree. These respondents may be motivated not to cheat so that they can develop the knowledge base and skills necessary to succeed in graduate school.
Although concern has been raised about the potential for breeches in academic integrity in completely online programs, especially with regard to online testing, the results of this study do not support the assumption that there is an increase in cheating in online programs. Higher levels of self-reported cheating were reported by the students in the traditional classroom RN-BSN program. Younger and older students in the traditional classroom group reported more instances of getting test questions from someone who had already taken the test and more instances of working together on assignments intended to be individual work. In addition, younger students in the online group self-reported more instances of cheating by helping others cheat on a test, using e-mail or instant messaging to collaborate on work, and paraphrasing material from written sources without proper referencing. Most of these self-reported cheating behaviors require student interaction. This may explain why they were reported more often in the traditional classroom cohort than in the online cohort. Online students may not have as much interaction with other students in the program and therefore may be less likely to participate in these forms of cheating.
Overall, the findings showed that online RN-BSN nursing students in this program had more awareness of academic integrity policies than the equivalent traditional classroom cohort. One factor that may contribute to this response is the independence that online students must demonstrate to seek out information on websites and in printed materials compared with the verbal dissemination of information that may or may not occur in the traditional classroom setting. Online students may also be aware of contemporary concerns related to cheating in the online environment. This heightened concern about academic integrity may lead to more diligence to uphold and support academic integrity policies. Students may strive to portray high standards of academic integrity to both their faculty and their peers to protect the reputation of their online program and their degree.
As online nursing programs continue to proliferate, nurse educators must thoroughly evaluate academic integrity and outcomes of online nursing programs. Measures to increase awareness of academic integrity policies and to clearly delineate expectations for academic integrity should be included in all nursing programs. Future studies of online RN-BSN programs should be conducted with larger samples from multiple universities and geographic areas. A survey to measure academic integrity specific to the online environment should be developed. Additional studies are needed to evaluate the relationship between collaborative cheating behaviors and the traditional nursing classroom.
- American Association of Colleges of Nursing. (2009). Degree completion programs for registered nurses: RN to master’s and RN to baccalaureate programs. Retrieved from www.aacn.nche.edu/Media/factsheets/DegreeCompletionProg.htm
- Bellack, J. P. (2004). Why plagiarism matters. Journal of Nursing Education, 43(12), 527–528.
- Center for Academic Integrity. (2009). Welcome to the Center for Academic Integrity. Retrieved from www.academicintegrity.org
- Finn, K. & Frone, M. (2004). Academic performance and cheating: Moderating role of school identification and self-efficacy. Journal of Educational Research, 97(3), 115–122. doi:10.3200/JOER.97.3.115-121 [CrossRef]
- Gallant, T. B. & Drinan, P. (2008). Toward a model of academic integrity institutionalization: Informing practice in postsecondary education. Canadian Journal of Higher Education, 38(2), 25–43.
- Harper, M. G. (2006). High tech cheating. Nurse Education Today, 6(6), 672–679. doi:10.1016/j.nedt.2006.07.012 [CrossRef]
- Hart, L. & Morgan, L. (2009). Strategies for online test security. Nurse Educator, 34(6), 249–253. doi:10.1097/NNE.0b013e3181bc743b [CrossRef]
- Hollister, K. & Berenson, M. (2009). Proctored versus unproctored online exams: Studying the impact of exam environment on student performance. Decision Sciences Journal of Innovative Education, 7(1), 271–294. doi:10.1111/j.1540-4609.2008.00220.x [CrossRef]
- Hughes, J. M. & McCabe, D. (2006). Understanding academic misconduct. Canadian Journal of Higher Education, 36(1), 49–63.
- Lanier, M. M. (2006). Academic integrity and distance learning. Journal of Criminal Justice Education, 17(12), 244–261. doi:10.1080/10511250600866166 [CrossRef]
- McCabe, D. (2009). Academic dishonesty in nursing schools: An empirical investigation. Journal of Nursing Education, 48(110), 614–623. doi:10.3928/01484834-20090716-07 [CrossRef]
- McCabe, D. & Trevino, L. (1997). Individual and contextual influences on academic dishonesty: A multicampus investigation. Research in Higher Education, 38(3), 379–396. doi:10.1023/A:1024954224675 [CrossRef]
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- Mullens, A. (2000, December). Cheating to win: Some administrators, faculty and students are taking steps to promote a culture of academic honesty. University Affairs, 41(10), 22–28.
- Rakovski, C. & Levy, E. (2007). Academic dishonesty: Perceptions of business students. College Student Journal, 41(2), 466–481.
|Variables Eliminated From the Original Survey||Variables Added to This Survey|
|Academic class standingPrimary majorParticipation in activities||Age rangePlans to attend graduate schoolMarital statusRaceGrade point averageExpanded list of those who would disapprove of cheating (spouse, coworker, children)Factors considered when choosing between a traditional classroom program and an online program|
Demographic Characteristics of the Sample, by Type of Program
| 40 and younger||100||30.4||21||47.7|
| 41 and older||229||69.4||23||52.3|
| No reply||1||0.2|
| No reply||1||2.3|
| Not married||91||27.9||10||22.7|
|Plans for graduate schoolb|
| Master’s degree in nursing||191||57.8||20||45.7|
| Doctorate of nursing practice||16||5.0||3||6.8|
| No reply||65||19.7||14||31.8|
Percentage of Students Who Have Ever Participated in Collaborative Cheating Behaviors, by Age Group and Type of Program
|Specific Behavior||40 Years and Younger||41 Years and Older|
|Online (%)||Traditional Classroom (%)||Online (%)||Traditional Classroom (%)|
|Getting questions or answers from someone who has already taken a test.||2.0||47.6*||0.8||13.0*|
|Helping someone else cheat on a test.||2.0||28.6*||0||0|
|Copying (by hand or in person) another student’s homework.||1.0||9.5||0||0|
|Working on an assignment with others (in person) when the instructor asked for individual work.||0||19.0*||2.2||13.0*|
|Working on an assignment with others (via e-mail or instant messaging) when the instructor asked for individual work.||0||19.0*||0.4||4.3|
|Using digital technology (such as text messaging) to get unpermitted help from someone during a test or examination.||0||0||0||0|
|Receiving unpermitted help on an assignment.||1.0||4.7||1.3||0|
|Copying (using digital means, such as instant messaging or e-mail) another student’s homework.||0||0||0||0|
|Turning in a paper copied, at least in part, from another student’s paper, regardless of whether the student is currently taking the same course.||0||0||1.3||0|
|Turning in work done by someone else.||0||0||1.3||0|
Percentage of Students Who Have Ever Participated in Independent Cheating Behaviors, by Age Group and Type of Program
|Specific Behavior||40 Years and Younger||41 Years and Older|
|Online (%)||Traditional Classroom (%)||Online (%)||Traditional Classroom (%)|
|Using an electronic/digital device as an unauthorized aid during an examination.||2.0||0||0.5||0|
|Using a false or forged excuse to obtain an extension on a due date or a delay in taking an examination.||8.0||4.8||1.7||0|
|Fabricating or falsifying laboratory data.||2.0||0||0||0|
|Fabricating or falsifying research data.||2.0||0||0.4||0|
|Copying from another student during a test or examination without his or her knowledge.||0||4.8||0.4||4.3|
|Paraphrasing or copying a few sentences from a book, magazine, or journal (not electronic or web-based) without properly referencing the source.||21.0||47.6*||15.8||13.0|
|Turning in a paper from a “paper mill” (a paper written and previously submitted by another student) and claiming it as your own work.||0||0||0||0|
|Paraphrasing or copying a few sentences of material from an electronic source without properly referencing the source.||22.0||38.0||17.8||13.0|
|Submitting a paper you purchased or obtained from a website (such as www.schoolsucks.com) and claiming it as your own work.||0||0||0.4||0|
|Using unpermitted handwritten crib notes (or cheat sheets) during a test or examination.||3.0||0||3.0||0|
|Using electronic crib notes (stored in a personal digital assistant, telephone, or calculator) to cheat on a test or examination.||2.0||0||0||0|
|Copying material, almost word for word, from any written source and turning it in as your own work.||2.0||4.7||0.4||0|
|Cheating on a test in any other way.||7.0||9.5||4.0||8.7|