Abstract
Cheating is an academically dishonest behavior about which there has been a thrust of research. However, it has not been extensively researched in an Iranian context. Therefore, the current study was conducted with 310 Iranian students. A cheating questionnaire was devised and administered to the participants. Certain demographic variables were investigated. Both descriptive and inferential statistics were employed to analyze the obtained data. The results of the descriptive statistics revealed that cheating was common among participants, and most students did not harbor any negative attitude toward cheating or at least were neutral about it. The most common method of cheating was “letting others look at their papers while taking exams.” The most common reason for cheating was “not being ready for the exam.” As for inferential statistics, one-way analysis of variance, an independent t-test, and correlational analyses were used to test the effect and relationship of demographic variables on and between the cheating behaviors of the participants. It was found that none of the two demographic variables of gender and year level had any effect on students’ cheating behaviors. Furthermore, achievement scores and age were not significantly correlated with cheating behavior scores.
Background of the Study
Cheating is an academic dishonesty (Colnerud & Rosander, 2009) that is rampant in university milieu. Apparently, it is taking place at so alarming a rate that it has prompted research worldwide. Studies include, but are not limited to, Canada (Hughes & McCabe, 2006), Australia (Brimble & Stevenson-Clarke, 2005), the United Kingdom (Newstead et al., 1996), Singapore (Lim & See, 2001), central European countries (Magnus et al., 2002), Western Europe (Teixeira & Rocha, 2008), and Tunisia (Hamani et al., 2013).
There have been several studies that investigated cheating as a dependent variable and other demographic variables such as field of study (e.g., Mensah et al., 2016), gender (e.g., Jensen et al., 2002), achievement (e.g., McCabe & Trevino, 1997), year level (e.g., Kayışoğlu & Temel, 2017), and age (e.g., Ahmadi, 2012) as independent variables.
Cheating studies also explored cheating as a dependent variable, which lends itself to subcategories like “reasons for cheating,” “reasons for not cheating,” “methods of cheating,” and “attitudes toward cheating.” Some reasons such as “uselessness of the materials” and “not being ready” have been nominated as the primary reasons for cheating. As for reasons not to cheat, some reasons such as “social stigma” associated with cheating have been the main reasons. As for methods of cheating, some methods are common worldwide, such as “letting others look at test papers.” Some of them are rare, such as “sending someone to the exam hall.” Attitudes toward cheating have also been explored worldwide. It is a truism that if students do not harbor negative attitudes toward cheating, it might mean that they are involved in one way or the other in the act of cheating.
In line with previous studies, this study will consider cheating as a dependent variable with four categories of “reasons for not cheating,” “attitudes toward cheating,” “reasons for cheating,” and “different methods of cheating” and will consider the demographic variables of gender, age, achievement, and year level as independent variables.
Literature Review
Cheating and Demographic Variables
Certain demographic variables have been postulated to affect the cheating behavior of test takers. Some of these variables include, but are not limited to, age, gender, the field of study, marital status, occupational status, and year of entrance to schools or universities.
As for age, Jensen et al. (2002) found that younger students were more inclined to cheat than older students. In a similar vein, Franklyn-Stokes and Newstead (1995) found that students’ cheating was the function of their age. Petrak and Bartolac (2014) conducted a study with health students and found that cheating was moderately prevalent among the 1,088 students with whom their survey was conducted. They also found that senior students were more honest than freshmen. The main motivation for cheating was getting a fair pass on the exams or better scores.
Gender is another variable believed to affect cheating behavior. According to McCabe and Trevino (1997), sex-role socialization has been employed to account for gender differences, arguing in the lines that women are inclined to be socialized to conform to rules. The results of the research findings are indeed inconclusive. Some studies have found that males have a stronger propensity toward cheating than females. Two of these studies are Kobayashi and Fukushima (2012) and Genereux and McLeod (1995). Other studies have found that females have more inclination toward cheating than males (e.g., DePalma et al. (1995). Finally, some studies have pointed to insignificant differences between males and females in terms of cheating (e.g., Ahmadi, 2012). In a study conducted with students of physical education and sports, Kayışoğlu and Temel (2017) found that students had above average attitudes toward cheating and that gender had no effect on altitudinal tendencies of the participants. In a Ghanaian context, Mensah et al. (2016) examined the cheating behaviors of students in a polytechnic. Both descriptive and inferential statistics were employed to analyze the data. In descriptive terms, copying of answers was the most prevalent type of cheating during exams. Gender made a significant difference in that there were more males than females reported to have cheated. Jensen et al. (2002) found that cheating behavior was more prevalent among male students than female ones. They attribute these differences to the propensity of males to take more risks than females.
Friendship effect is also believed to affect cheating behavior of students. In this regard, Chapman et al. (2004) found that cheating is more common among friends than mere acquaintances. In other words, students tend to cheat more in situations in which more friends flock together.
Field of study has also been construed as a potential determinant of cheating behavior. Chapman et al. (2004) found that cheating was more prevalent among marketing majors than their peers in other business-related disciplines. In Mensah et al.’s (2016) study, the field of study played a significant role in that engineering students self-reported more academic dishonesty than hospitality students. Kayışoğlu and Temel (2017) confirmed a relationship between the year of study and attitudes toward cheating. The results of their study also showed that the type of the department where the students studied did not influence their attitudes in significantly different ways.
Another demographic variable that has been postulated to affect cheating is the achievement which is often operationally defined as students’ grade point average. McCabe and Trevino (1997) acknowledge that the research findings are inconsistent in this regard. Low achievers have been found to cheat more than high achievers based on the theoretical rationale that low achievers have “more to gain and less to lose” (McCabe & Trevino, 1997, p. 381).
Finally, Passow et al. (2006) found that cheating varied according to the type of assessment, which were exams and homework in their study. They also found that the belief to relieve stress is likely to lead to cheating on the part of students.
Different Types of Academic Dishonesty
Colnerud and Rosander (2009) maintain that there are different taxonomies of dishonest behavior, three of which are as follows:
-Cheating—for example, using unauthorized materials.
-Unauthorized collaboration—for example, a joint venture on assignments that were meant to be executed individually.
-Plagiarism and fabrication—for example, making use of another person’s text without making reference to the writer and submitting the same papers for two or more courses.
Studies on Cheating in an Iranian Context
Cheating is considered a deplorable act, and there are even “fatwas” or religious decrees about it. For example, one religious figure considers it “haram” or a sin. Some religious figures even consider the degree offered to the person to be “haram” and maintain that the certificate obtained as a result of cheating should be rescinded. According to Ayatollah Fazel Lankarani, “It is legally forbidden” (“Legal Sentence for Cheating in Exams,” 2020).
Secretary of the Central Council of the Disciplinary Committee of the Ministry of Science, Research, and Technology said, if the cheating is proven, a penalty of 25% or suspension will be considered for the student (“How the Disciplinary Committee Deals With Fraudulent Students?,” 2010). Gholami and Shahbazinia (2016) maintain that according to the different issues reflected in the Civil Code, the Commercial Code, and the amendment bill of the Commercial Code adopted in 1968; the Insurance Law; and other similar laws, it is well inferred that the legislature seeks to prohibit fraudulent use of laws by individuals and who have resorted to legitimate means to achieve illegitimate goals.
Studies published in local journals
Bahrami et al. (2015) conducted a study with medical sciences students, and the findings revealed that 45% of students experienced cheating. The authors call for disciplinary actions to be taken to deal with the cheating phenomenon. Khamesan and Amiri (2011) conducted a study in an Iranian university with a questionnaire being their main tool of data collection. They found that boys were involved in cheating more than girls. The most common method for cheating was looking at others’ exam papers. They too call for legislative actions to be taken toward cheating. Ahanchiyan et al. (2016) used a qualitative approach to delineate factors involved in cheating. They came up with the two kinds of internal and external factors related to the act of cheating.
Studies published in international journals
A study by Yekta et al. (2010) conducted in a medical university found that cheating was rampant in their sample. They found that gender was not significantly related to cheating behavior. However, they did find that cheating and attitudes toward cheating differed by the fields of study.
In language-related fields, Ahmadi (2012) conducted a study with students of Teaching English as Foreign Language and found that cheating prevailed among Iranian students, with the most common methods being “talking to neighboring students” and “copying answers” and the most important reasons being “not being ready for the exams” or “difficulty level of the exams.” Ahmadi also investigated the role of demographic variables of the field of study, academic level, and occupational status which affected cheating significantly. Furthermore, he found that age was negatively and significantly related to cheating and attitudes toward cheating.
Cheating on Exams
Diego (2017) conducted a qualitative study and found that cheating was related to social behavior. In other words, students cheated on exams as they wanted to help others. Peer pressure was the driving force behind cheating. Eastman et al. (2008) conducted a study about unethical behavior, in which cheating on exams is an example. They found that cheating on exams is triggered by beliefs about cheating. In other words, if students do not harbor negatives about cheating on exams, they are likely to be involved in cheating. Magnus et al. (2002) conducted a study across the participants of three countries and concluded that cheating differed across the three countries under study. They, too, concluded that cheating is triggered by attitudes about it. Fendler et al. (2018) came up with a design that could deter cheating by seating students randomly in exam halls.
The Rationale of the Study
Iran is a country that strives to achieve excellence in academia. A study is to investigate whether cheating happens in Iranian academic milieu. If it is discovered that Iranian students cheat, attempts should be made to take drastic measures to stop the phenomenon. Maybe punitive measures should be taken.
While there have been studies worldwide regarding cheating as a type of academic dishonesty, there is a paucity of research in an Iranian context. Therefore, the current study endeavors to answer the following research questions:
Method
The Participants
The participants of the current study were 310 students from three state universities in Iran. These students belonged to different fields. All of them were BS students admitted to different fields in the university. Out of 310 students, 245 were males and 65 were females. Most of students (55.9%) were first-year students. The rest of them were second- to fifth-year students. They had enrolled for different courses offered in the language centers of three state universities. These courses were general English and courses like English for Students of Civil and Mechanical Engineering. All in all, 333 students took part in the study. The participants with missing values related to the independent and the dependent variable(s) were excluded from the analyses. Hence, the number 310. Table 1 depicts the nature of the independent and the dependent variable(s). It is to be noted that in the Iranian educational system, students enter universities at the age of 18 and graduate at the age of 22, with BS program lasting for 4 years. There are some exceptional cases, with some staying for 5 to 6 years. There are also students who enter the university at the age of 16 because they are exceptionally good ones.
Frequency and Percentage Distributions for the Demographic Features of Participants.
This study was approved by the ethical committee of Sharif Language Center Ethical Committee. Prior to the study, written informed consent was obtained from the participants.
The Instrument
The instrument used in this study was a questionnaire which was devised based on insights from literature and the particular nature of the university. Iran is a country where most students are obsessed with Islamic teachings. In that direction, we included an item that said cheating was not acceptable according to religious values. The questionnaire consisted of four parts. The first part was related to reasons for not cheating. This part had six items. The next part which had 10 items was related to attitudes toward cheating. The third part which had 17 items was related to reasons for cheating. The last part which embedded 13 items was related to methods of cheating. All in all, the questionnaire had 46 items.
For Sections 3 and 4, we started the sections with the phrase, “if you ever cheated, choose the reasons and the methods from the list below.” The questionnaire was anonymized so that the students could freely comment on the reasons and methods for cheating. We did not explicitly ask them whether they had ever cheated. We thought this could have been obtrusive. The Cronbach’s alpha for all the items was .74, which can be considered satisfactory.
The Persian version of the instrument was administered to the participants on the assumption that the English version might produce insurmountable difficulties for them in terms of language issues. The Persian version was back-translated into English to check for validity. Furthermore, to check for the construct validity of the instrument, principal components analysis was run with four factors suppressing correlations below .3 (see Kline, 1994). Four different and distinct factors were confirmed corresponding to the four parts of the questionnaire (see the appendix).
Data Collection
Data collection took place toward the end of an academic semester (winter, 2018), which would not interfere with classroom routines. The purpose of the research was explained to the teachers who would collect the data and brief the students before they answered the items. Prior to data collection, a meeting was held with all of the colleagues in whose classes the data were collected. The teachers were briefed on how to collect the data and obtain written consent from the students. Some students wrote different methods of cheating that were not mentioned in the questionnaire. All in all, 20 to 30 min were allocated to answering all the 46 items of the questionnaire. Students were told that answering the questionnaire was a voluntary activity. Informed consent was obtained from them.
Data Analysis
The obtained data were analyzed both descriptively and inferentially. As for descriptive statistics, frequencies and percentages were calculated. In terms of inferential statistics, analysis of variance (ANOVA), independent t-test, and Pearson’s product-moment correlations were employed. One-way ANOVA was used to test the effect of the two variables of the field of study and year level on cheating. To test the effect of gender, an independent-samples t-test was used. Finally, to investigate the relationship of achievement and age with cheating behavior, correlational analyses were employed.
Results
Descriptive Statistics
In this section, we will deal with each specific research question based on which results will be presented. The answer to the first research question is appalling. Only 33 out of 310 students indicated that they had never cheated. In other words, almost 90% of the students indicated that they had cheated on exams in one way or another in their lives.
The second research enquired about the reasons for not cheating, whose results are presented in Table 2. In terms of the first item about not cheating which said that “cheating is violating the rights of other students,” 68.7% of the students believed that it was the case. In terms of the second item about cheating which linked cheating to religious beliefs, 53.6% believed that religion had a role in not cheating. About the third item which linked cheating to one’s public face, 59.7% believed that it was the case. About the item linking cheating to fear factor, 36.2% believed that it was true of them. About the item linking cheating to social stigma, 69% believed that it was the case. Apparently, the most obvious reason for not cheating was related to social stigma and violating the rights of the others. Items 1 and 6 include the most important reasons for not cheating.
Descriptive Statistics for the Reasons for Not Cheating.
Note. F = frequency; P = percentage.
The third research question enquired about the attitudes of the students toward cheating. It must be mentioned that we did not directly ask the students whether they cheated or not as some researchers have done in the past (e.g., Ahmadi, 2012). Instead, this attitudinal survey served the good purpose of delving into students’ mindsets about cheating. Only 39.46% (Table 3) agreed that cheating was not right. This number was arrived at by summing all the percentages for “strongly agree and agree” from all the 10 items in the survey and dividing the outcome by 10. This means that 60% of the respondents were either natural about cheating or did not entertain negative attitudes toward cheating. Roughly, 40% of the respondents did not harbor negative attitudes about cheating, implying that it was a normal behavior.
Descriptive Statistics for Attitudes Toward Cheating.
Note. F = frequency; P = percentage.
The results of the attitudinal survey revealed interesting insights into the students’ mindsets about cheating:
First, there seems to be a connection between cheating and the difficulty level of the exam. We conducted small-scale interviews with some students. Most students we talked to believed that the exams were unfairly difficult in this university.
Second, the students in our sample seem to be affected by the fact that “everybody does not. Why shouldn’t I cheat?”
In terms of the fourth research question inquiring about reasons for cheating, the most common reason happened to be “not being ready for the exam,” followed by “uselessness of the materials” and still followed by “getting a better score.” The fourth reason was “bulkiness of the materials.” The fifth reason was “difficulty of the exam.” The sixth reason was “not having time for studying.” The reasons are illustrated in Table 4.
Descriptive Statistics of Reasons for Cheating.
Note. F = frequency; P = percentage.
As for the fifth research question which enquired about the common methods of cheating, it turned out that the most common method was Method 8, which was “letting others look at their papers while taking exams.” The next most common method was “looking at others’ test papers.” The third common method was “talking to neighboring students.” The other methods were not that much frequent. The least common one was “sending another person to the exam hall.” The results are displayed in Table 5.
Descriptive Statistics of Different Methods of Cheating.
Note. F = frequency; P = percentage.
It is to be noted that the students wrote some other methods in the space provided for them, an account of which is provided below:
One student wrote that he could get the questions at a point in time. The others mentioned the following:
Bribing the proctors;
Asking the proctors questions;
Putting the slips of paper inside long hair;
Writing the answers to questions on a handkerchief and pretending to cough and use the handkerchief while actually cheating.
Inferential Statistics
To analyze the data inferentially, ANOVA, an independent t-test, and correlational analyses were employed as parametric tests. It was important to test the assumptions for the demographic variables of gender and year level. Shapiro–Wilk was tested with the scores of all sections of the test as the dependent variable and the demographic variables of gender and year level as independent variables. The data were normally distributed with all the three independent variables.
After it was made sure that the data were normally distributed with all the three independent variables of the study, an independent-samples t-test was conducted for gender and total score which was insignificant (F = 1.251, Sig. = .264, df = 309).
The effect of year level was also tested. A one-way ANOVA was conducted to see whether it had any effect on the total score. The results revealed that the year of entry did not affect the cheating behavior of the participants (F = 1.522, Sig. = .183, df = 5).
Finally, to test the relationship between the two variables of achievement and age with cheating, two correlational analyses were conducted, the results of which showed that age was not significantly related to cheating (r = .065, p = .260) and that achievement scores were not significantly correlated with cheating (r = .015, p = .808).
Discussion
The first research question endeavored to probe the extent of Iranian students’ involvement in cheating behavior. The results are chilling. Ninety percent of students indicated that they were involved in cheating in one way or another at least once in their lives. Only 33 students wrote either directly that they had never cheated or did not answer the two sections of the questionnaire dealing with reasons for cheating and methods of cheating. The results confirm those of previous studies in that cheating is quite rampant in academia (e.g., Sims, 1993). There might be two reasons for this finding in the research: First and foremost, the responses were anonymized, so they felt free to indicate whether they cheated. Second, the data were collected in a language center as opposed to their own departments. They only take a few courses in the language centers. They felt more comfortable with venting out their frustrations. They might have been more conservative in their own departments as they take too many courses in those departments and teachers might have taken a dim view of the fact that they cheated. In fine, the language centers were a safe place for them to take the survey.
As far as the second research question, which enquired about the reasons for not cheating, is concerned, the surprising finding was that social stigma and the rights of the others carried more weight than religious issues. We expected to find a link, albeit a tenuous one, between not cheating and religiosity. Iran is an Islamic country, and religion does play a significant role in people’s lives. It was supposed to serve as a deterring mechanism more than social stigma, but it did not. The item that had the lowest score was Item 4, linking not cheating to fear issue. It was interesting that the fear of being caught does not play that much of a role. It is perhaps the case that in these state universities, the authorities do not take punitive measures in case of cheating.
In terms of the third research question enquiring about the attitudes of the students toward cheating, the findings are surprising. Only 39.46% of the students had a negative attitude toward cheating. The implication might be that they might have been involved in one way or another in the act of cheating. We did not directly ask the students to indicate whether they ever cheated or not, as we thought we might not get honest answers. But the attitudinal survey indirectly probed their viewpoints about cheating.
The fact that “letting others look at their test papers” and “looking at others’ test papers” were the most common methods comes as no surprise because most students are used to these methods which are the most traditional ones. It is also the least risky approach and method because exam halls in these universities are not monitored by cameras. Also, the fact that “sending someone to the exam hall” turned out to be the least common method should not be surprising because it is too risky an undertaking concerning the hazards it has for one’s academic career: Proctors are there to monitor these misdemeanors. The results also confirm those of Ahmadi (2012) who arrived at similar results. Scrimpshire et al. (2017) discuss that letting others look at your papers does imply cheating on your part.
In terms of the reasons for cheating, it is logical to expect that the students cheat because they think some materials are useless and they do not need them that much. One of the courses students pass is general math, which the students surmise is not applied mathematics. There are also similar courses in the university which the students assume serve no good and perhaps immediate purposes. Other common reasons were “not being ready” and “bulkiness of the materials.” We believe that these two reasons are related and that bulkiness of the materials is the reason for their not being ready for the exams. Expectations of teachers are too high regarding these state university students. They bombard them with materials and assignments. “Getting a better score” was also another common reason for cheating on the part of the students. The results of this part of the study are in conformity with those of Ahmadi (2012) who found that students cheated mostly because of not being ready.
The two nominal demographic variables of gender and year of entry were found not to affect the cheating behavior of the students. The same held true for the demographic variables of achievement and age.
The results of the current study run counter to those of Petrak and Bartolac (2014) in that they found that senior students were more honest than the freshman. One reason can be that in the current study, the majority of students were first-year students (almost 60%). The results of the current study do not either lend support to those of Jensen et al (2002) who found that cheating behavior was more prevalent among males than females. According to them, this can be due to the propensity of males to take more risks than females. The interesting finding in this study is that males and females differed in no category out of the four categories of cheating behavior. In the “Results” section, only the total score obtained from the four categories of cheating behavior were reported. We analyzed all the four categories of cheating behavior, and no significant differences were found between the means of males and females in all the four categories. The results of this study are not in line with those of Kayışoğlu and Temel (2017) who found that students’ attitudes changed according to year level. A one-way ANOVA for the effect of the year level was conducted, the results of which showed that attitudes did not differ by year level (F = 1.522, Sig. = .217, df = 5).
Two more independent variables were also investigated in this study: achievement scores and age, both of which were subjected to correlational analyses. A negative and nonsignificant correlation was found between age and cheating on the part of students. The results do not lend support to previous studies like Ahmadi (2012) who found that age was negatively and significantly related to cheating. This discrepancy can be explained by the restricted range of age as an interval variable in this study. All the students in the current study were BS students who did not differ that much in terms of age. Actually close to 90% of students ranged from 18 to 22 years of age. Another variable that was investigated was achievement scores. Achievement scores were operationally defined as any score that the students got in their midterms in courses such as General English and English for Specific Purposes. These courses were offered in the Language Center, and we could check the veracity of the reported scores. These scores are indeed surrogate and do not represent the totality of their achievements. At any rate, the achievement scores did not have a significant correlation with cheating. We expected achievement scores to be negatively correlated with cheating. To shed more light and triangulate the results, we formed two groups of high achievers and low-to-mediocre achievers based on their midterm scores. Anecdotally, students scoring above 25 out of 30 in midterm tests were deemed high achievers. The mean on the cheating variable for high achievers in cheating was 44.41 and for the low-to-mediocre achievers was 45.11, which was insignificant. The results run counter to those of McCabe and Trevino (1997) who found that students with high achievement did not cheat as much as those with low achievement.
Conclusions and Suggestions
Every university should publish its code of ethics on the university homepage. Students should know that they cannot get away with cheating and that there are grave consequences for cheating. Penalties should be unambiguously spelled out to the students (Ma et al., 2013). Cheating is a deplorable act. As indicated in the students’ reasons for cheating, there might be undue stress on the students in such universities, which will eventuate in cheating. Cheating might originate from external forces that are imposed on students (Anderman et al., 1998). In other words, the ends might justify the means. Students might be extrinsically motivated to cheat. Educators have a tough job; they should attempt to inculcate the belief in students that studying should be done for the sake of studying, not for getting good scores and other external reasons.
Footnotes
Appendix
Rotated Component Matrix.
| 1 | 2 | 3 | 4 | |
|---|---|---|---|---|
| Nc1 | .595 | |||
| Nc2 | .518 | |||
| Nc3 | .689 | |||
| Nc4 | .656 | |||
| Nc5 | .645 | |||
| Nc6 | −.558 | |||
| A1 | .815 | |||
| A2 | .808 | |||
| A3 | .724 | |||
| A4 | .668 | |||
| A5 | .706 | |||
| A6 | .825 | |||
| A7 | .708 | |||
| A8 | .789 | |||
| A9 | .839 | |||
| A10 | .739 | |||
| C1 | .512 | |||
| C2 | .413 | |||
| C3 | .431 | |||
| C4 | .402 | |||
| C5 | .39 | |||
| C6 | .443 | |||
| C7 | .434 | |||
| C8 | .517 | |||
| C9 | .574 | |||
| C10 | .432 | |||
| C11 | .456 | |||
| C12 | .561 | |||
| C13 | .462 | |||
| C14 | .431 | |||
| C15 | ||||
| C16 | ||||
| C17 | ||||
| M1 | .432 | |||
| M2 | .444 | |||
| M3 | .432 | |||
| M4 | .456 | |||
| M5 | .451 | |||
| M6 | .59 | |||
| M7 | .475 | |||
| M8 | .58 | |||
| M9 | .563 | |||
| M10 | .467 | |||
| M11 | .418 | |||
| M12 | .39 | |||
| M13 | .591 |
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
