Abstract
Academic dishonesty has recently attracted the attention of scholars worldwide in the aftermath of severe breaches of academic rules of conduct. As today's students are tomorrow's leading academics and professionals, it continues to be of importance to understand the basic explanatory mechanisms of academic dishonesty. The present cross-cultural inquiry explores academic dishonesty through the lens of situational action theory (SAT). Specifically, this paper explores the connection between criminogenic propensity and criminogenic exposure, and its impact on academic misconduct. We analyze self-reported data from a random sample of 378 Iranian students. Multivariate regression results, examining both direct and interactional relationships, demonstrate that the key propensity–environment hypotheses of SAT are generally supported as morality, self-control, and perceived deterrence all play a role in explaining academic misconduct. Specific findings, study limitations, and directions for future research are discussed.
Introduction
Studies of academic dishonesty are not new, and it has been reported that academic dishonesty occurs across a variety of assessments, including assignments, tests, and final exams (e.g., Błachnio et al., 2022; Hodgkinson et al., 2016). According to Chace (2012), three-fourths of students have engaged in some form of academic dishonesty. The question of whether cheating is an individual or collaborative endeavor has also been investigated. Research from Đogaš et al. (2014) suggests that depending on the type of fraudulent behavior, the percentage of students who seek assistance from someone else when cheating ranges from 27% to 89%. More specific to the context of the current study, it has been reported that the percentage of Iranian students who have engaged in academic dishonesty varies from 20% to 97% (e.g., Aliverdinia et al., 2016; Yekta et al., 2010). Additionally, as a result of the recent COVID-19 pandemic, a significant increase has been reported in academic dishonesty among students taking online courses (Ebrahimi et al., 2021). To combat this growing issue, the Iranian Ministry of Science has launched a monitoring system known as IranDoc 1 to help reduce the prevalence of academic dishonesty in Iran's scientific community. While recent efforts have been made to curb academic cheating, its prevalence in Iran—and around the world—continues to be a concern (e.g., Lee et al., 2020; Mohammad Hosseinpur et al., 2018).
This alarming phenomenon has received attention across a variety of disciplines, including psychology (Bandura, 2002), education (Bacon et al., 2020), and criminology (Stogner et al., 2013). Among criminologists, specifically, research examining the etiology of academic dishonesty has often focused on social learning theory (Aliverdinia et al., 2016), self-control theory (Cochran et al., 1998), and deterrence theory (Cochran et al., 1999). These frameworks hone in on concepts related to socialization, criminal propensity, anticipated shame, and the perceived risk of getting caught. However, that is not to say that other theoretical frameworks have not engaged in exploring the etiology of academic dishonesty. Perhaps, one way to overcome the limitation of explaining academic dishonesty through a series of single-theory tests is to apply an integrated theory, such as Wikström’s (2004, 2017) situational action theory (SAT). That is what we do in the present study.
A major challenge in the social sciences is to find an appropriate definition of academic dishonesty, as there are subtle and blatant forms of academic cheating. Academic dishonesty can be defined in many ways, but one recurrent aspect of the definition refers to cheating or plagiarism that gives a student an illegitimate advantage during an assignment or assessment (Bleeker, 2008). Presented this way, the definition of academic dishonesty falls under the broader umbrella of deceit/deception, which has been studied in many species by evolutionary biologists (for an overview, see Trivers, 2011). This study is restricted to the academic dishonesty of students. It seems that studies of academic dishonesty suffer from the same problems that have been identified in general studies of crime causation (Wikström et al., 2012), gang membership (Pauwels & Hardyns, 2016), and violent extremism (Wikström & Bouhana, 2016): conceptual clarity and the absence of an action theory.
The fact that so many perspectives are used raises concerns about what theoretical models are the best fit to explain the phenomenon under scrutiny. As has been noted previously, there are many risk factors for academic dishonesty just as there are many risk factors for juvenile delinquency and troublesome youth group involvement. However, we know that most risk factors are either markers (biological sex, see Zhang et al., 2018), symptoms, or just correlates without causal meaning (Wikström, 2017). Factors such as norms, shame, self-control, and the normative academic climate are, however, more plausible variables to analyze within a causal model. In the present study, we aim to do so by integrating key factors in an overarching general framework.
One contribution to theoretical integration in the explanation of crime has been the development, continual refinement, and testing of Wikström’s (2004, 2017) SAT. Although SAT is a rather recent theory, it has gained the interest of scholars across the world and its tests have generally demonstrated empirical support (e.g., Cochran, 2015; Hirtenlehner & Treiber, 2017; Kabiri et al., 2020; Pauwels et al., 2018). As a general theory of action, it was created to explain a wide scope of rule-breaking behavior. The idea of seeing criminal behavior as a type of rule-breaking, defined by law, is far from new but is sometimes misunderstood (Wikström & Treiber, 2016). By defining crime as moral actions, SAT tries to circumvent the problem of searching for different explanations for different crimes, while overlooking the fact that some of the major causes of crime may be overlapping. SAT generally makes the distinction between direct causes of crime (i.e., causes that help to see crime as an action alternative and choose the action alternative; the perception-choice process), and the factors of social and self-selection (e.g., self-control, perceived deterrence) that affect that perception-choice process. Similarly stated, SAT posits that deviant behavior—including academic dishonesty—can be viewed as the culmination of a propensity–exposure interaction.
The interaction between criminal propensity and criminal exposure has been identified in prior research as a consistent predictor of general criminal behavior (for a meta-review, see Pauwels et al. 2018) as well as academic cheating (Cochran, 2015). This latter study demonstrates some initial evidence for the predictive utility of SAT in explaining academic dishonesty. Moreover, several previous studies in the academic dishonesty literature have shown the importance of psychosocial factors such as low self-control, perceived deterrence, social norms, and the physical environment (e.g., Aliverdinia et al., 2016; Cochran et al., 1998; Hendy & Montargot, 2019). Building on the extant research, this study contributes to the criminological literature by conducting a cross-cultural test on the influence of SAT on academic dishonesty in Iran. More specifically, moderating regression analyses are used to investigate whether two-way and three-way interactions between criminal propensity and exposure to crime affect academic dishonesty among a sample of 378 university students from Rasht, Iran.
Literature Review
Academic Dishonesty
Academic dishonesty is seen as a global problem. The past two decades have witnessed an explosion of research concerning the etiology of plagiarism, cheating on exams and analogous behaviors that go against the rules and norms of schools, universities, and learning institutions. Academic dishonesty can be described as a set of unethical acts violating educational integrity (e.g., Hodgkinson et al., 2016). Cheating on exams or scientific projects impairs the fairness of academic competitiveness.
The importance of investigating academic fraud stems from the fact that a person who cheats in the education environment is more likely to cheat in another social domain. For example, Macale et al. (2017) showed that academically deceitful actions stabilize over time and that students also engage in cheating in higher education. Druică et al. (2019) found that there is a strong relationship between academic cheating and financial fraud. Concerning the prevalent rate of academic cheating behaviors, research has shown that this deviant behavior is reported in a wide range of countries including the USA (Hensley et al., 2013), France (Hendy & Montargot, 2019), Pakistan (Nazir & Aslam, 2010), Australia (Cuadrado et al., 2019), Moldova (Ives & Giukin, 2020), Italy (Macale et al., 2017), China (Zhang et al., 2018), and Iran (Rezanejad & Rezaei, 2013).
This voluminous body of research documents the importance of studying academic cheating, and it highlights the myriad of consequences that can result from academic dishonesty for the individual (e.g., academic probation), the school (e.g., loss of organizational reputation), and the academic community (e.g., loss of legitimacy). This research also uncovers the troubling prevalence of cheating. In Iran, in particular, prior studies have found that the frequency of educational misconduct varies from 17% to 88% (Aliverdinia et al., 2016; Khodaie et al., 2011).
In order to implement policies and strategies to better combat academic dishonesty, it is important to have a firm understanding of its etiology. To that end, prior research has established a variety of key correlates. These include perceived peer dishonesty (Stogner et al., 2013), attitudes toward cheating (Hendy & Montargot, 2019), personality (Cuadrado et al., 2019), morality (Zhang et al., 2018), criminogenic setting (Ives & Giukin, 2020), self-control (Błachnio, 2019), perceived deterrence (Birks et al., 2018), and strain (Stogner et al., 2013). We follow this line of scholarship by testing SAT's applicability in trying to better understand academic dishonesty.
SAT
According to Wikström (2014, p. 75), “People commit acts of crime because they perceive and choose (habitually or after some deliberation) a particular kind of act of crime as an action alternative in response to a specific motivation (a temptation or a provocation).” The theory posits that individuals are essentially rule-guided creatures and that they will express their desires and respond to strains within the context of rule-guided choices. Further, societal rules of conduct tell people what they ought to do or not to do in response to various motivators in particular circumstances. Individuals can either agree or disagree with particular rules, and they can either abide by (or break) particular rules. According to SAT, people are the source of their actions, meaning that people perceive, choose, and execute their actions. However, the causes of behavior are situational, meaning that an individual's particular perception of behavior alternatives, process of choice, and execution of action are guided by the relevant input from the person-environment interaction. Thus, criminal and deviant behavior (i.e., rule-breaking) occur because (a) individuals perceive such behavior as a viable and acceptable action alternative given the circumstances and there is no strong enough deterrent and (b) fail to adhere to their own morals and exercise self-control in circumstances when they are externally pressured to act otherwise.
SAT: The Crime Propensity–Criminogenic Exposure Interaction
Crime propensity is defined as the general tendency of persons to perceive and choose crime as a valid action alternative. This concept is primarily determined by a person's morality and secondarily by a person's ability to exercise self-control (Wikström et al., 2012). Personal moral propensities refer to individual moral values (i.e., how right or wrong a person thinks it is to break a rule stated in law), weighted by key moral emotions of shame, guilt, and anger that guide the individual's action alternatives. SAT argues that it is not one's motives (e.g., self-interest, rationality, altruism), but one's moral values that guide a perception-choice process. 2 If one's moral values are positively orientated towards rule-breaking, this person may come to see crime as a viable alternative. In SAT, self-control is defined as the successful inhibition of a perceived action alternative or the interruption of a course of action that conflicts with an individual's morality (Wikström & Svensson, 2010).
The propensity–exposure interactive hypothesis states that a person's propensity needs to be activated by exposure to a criminogenic setting. A setting is the part of the environment one can perceive with his or her senses. According to SAT, the concept of exposure to criminogenic settings refers to (a) the presence of other persons (e.g., peers who provide situational inducements or activate commitments) and (b) place characteristics (e.g., the absence of deterrent qualities and moral rules that promote—or at least do not prohibit—the commitment of deviant behavior).
SAT: The Interaction Between Morality and Self-Control
According to SAT, self-control is only a relevant factor in offending when an individual actively considers committing a crime as an action alternative, thus having low levels of morality. The question of whether morality and self-control interact in the explanation of offending has been examined in numerous studies to date. A narrative review by Pauwels et al. (2018) supported the morality and self-control interaction hypothesis. However, the review also pointed out that not all studies replicated the original interpretation made in the study by Wikström and Svensson (2010). Some studies reported no interaction effects and others reported various interaction effects (Kammigan, 2023).
New Directions in Testing SAT: From Two-Way Interactions to Three-way Interactions
Contemporary tests of SAT reveal a different approach to the study of main and interactive effects. They often try to disentangle the overall interaction between crime propensity and criminogenic exposure by studying the interactive effects between the key components of crime propensity (personal morality and self-control) and criminogenic exposure (situational morality and perceived deterrence). This trend is more in line with the complex nature of crime causation and has the advantage that unidimensional concepts are used. Indeed, combining different dimensions of key constructs obscures the nature of the interactions that are discussed in SAT. For example, to test the conditional effects of controls (self-control and deterrence), it is necessary to study these concepts on their own and as part of a multidimensional construct.
Prior empirical studies testing SAT's principles of moral correspondence and the principle of conditional controls found mixed support, with some findings suggesting full support for SAT's predictions (Hirtenlehner & Hardie, 2016; Svensson et al., 2017), while other study observations seemed at odds with SAT's predictions, finding only partial support (e.g., Barton-Crosby & Hirtenlehner 2021; Kroneberg & Schultz, 2018). It should be noted that most studies are based on convenience samples of mid-adolescent college students or undergraduates. Moreover, many of the prior studies have relied on questionnaire-based (i.e., not situational-based) aggregated measures of the key constructs, such as deviant behavior (e.g., past offending frequency versus an offending versatility index), self-control (e.g., self-control ability versus state self-control), and deterrence (e.g., generalized perceived deterrence versus specific perceived deterrence).
In response to the inconclusive findings, Hirtenlehner and Leitgöb (2021) argue that a moral conflict is not necessary for rendering controls important and propose an alternative model of a subsidiary relevance of control. These scholars’ position is that both internal and external controls become important as soon as either a weak personal morality or a criminogenic moral context (or both) weaken the moral filter. Indeed, seeing rule-breaking as an action-alternative demands for controls to counteract its attractiveness. Hirtenlehner and Leitgöb (2021) favor a broader conceptualization of the functioning of self-control in reducing rule-breaking that is more in line with the psychological literature. Self-control aims to adjust personal standards; however, these standards need not be one's own moral rules (Hirtenlehner & Leitgöb, 2021).
According to SAT, morality serves as the primary factor influencing rule-breaking, suggesting that self-control becomes pertinent only during the deliberation process of whether to break a rule (Wikström, 2004). Consequently, personal morality functions as a moderating variable in the connection between self-control, exposure to criminogenic elements, and deviant behavior. Research from Barton-Crosby and Hirtenlehner (2021) tested the moderating role of personal morality in their study, examining how it influences the interaction between self-control, provocation, and crime. They hypothesized that the impact of self-control on mitigating provocation varies with an individual's personal morality, thus, forming a three-way interaction. Consistent with the theory, their results demonstrated that strong law-consistent morality strengthened one's moral filter and reduced the likelihood of perceiving crime as a response to provocation, while weak law-consistent morality increased this likelihood.
Based on the premise of SAT, Kafafian et al. (2022) similarly posited that the interaction between self-control and personal morality played a role in influencing delinquency. Specifically, they suggested that the impact of self-control would be more pronounced among individuals with weaker moral rules and less pronounced among those with stronger moral rules. Their findings supported this hypothesis in their sample's Western countries as the effect of moral rules on delinquency was stronger when self-control level was high rather than low (i.e., the effect of self-control on delinquency was more obvious when moral rules were stronger); however, this effect did not appear for the non-Western countries in their sample. Additionally, Kabiri et al. (2024) discovered that personal morality acted as a moderating factor in the relationship between self-control, situational morality, and school bullying. This finding suggested that the influence of self-control on the association between situational morality and school bullying was contingent upon an individual's personal moral values. To elaborate, when individuals possess stronger personal morality, the moderating effect of self-control on the link between situational morality and school bullying becomes more pronounced. Conversely, for those with weaker personal morality, the impact of self-control on this relationship is less significant. This nuanced interaction underscores the intricate interplay between individual moral beliefs, self-control, and the dynamics of situational morality in the context of committing crime like academic dishonesty.
The above research highlights the fact that SAT not only offers valuable insight into the interactive nature of individual decision-making processes but also underscores the pivotal role of personal morality in shaping these dynamics. Within the SAT literature, personal morality has emerged as a more influential factor in determining criminal propensity as compared to self-control, thus, stressing the nuanced interplay between an individual's moral values and the likelihood of engaging in deviant behavior. Furthermore, this literature suggests that personal morality may play a crucial moderating role in shaping the intricate relationship between self-control and criminogenic situational contexts (e.g., situational morality and perceived deterrence). Recognizing and understanding these complex dynamics highlighted by SAT provides a comprehensive framework for exploring and addressing deviant behavior, with a specific emphasis on the central role of personal morality. This nuanced perspective enriches our comprehension of the multifaceted factors influencing individuals’ behavioral choices, and it can ultimately contribute to more effective strategies for crime prevention.
SAT in a Cultural Context
As a comprehensive framework for understanding crime, SAT requires predictive capabilities to explain crime across diverse cultures. Enhancing its efficacy, the theory must demonstrate the ability to anticipate—and account for—variation in the dynamics of deviant behavior across different cultural contexts. To that point, in a study of 28 countries, Kafafian et al. (2022) recommend that the cross-cultural dimension of SAT warrants further exploration. Specifically, in order to provide greater clarify, they suggest that future research offer a more detailed explanation of the specific cultural elements being studied and whether such elements relate to one's criminogenic propensity, criminogenic exposure, or the interaction between the two.
Understanding the demographic and cultural context becomes crucial for grasping a study's broader implications. Kafafian et al.'s (2022) findings demonstrated moderately strong empirical validity for SAT across both Western and non-Western countries. Notably, they identified parenting a partial precursor to individual moral rules and self-control. Additionally, some other SAT-relevant predictors (e.g., deterrence) exhibited consistent potency as crime predictors across diverse cultural contexts. The effect of personal morality, however, demonstrated significant variation between Western and non-Western regions. Moreover, Kafafian et al. (2022) highlighted significant interactions between personal morality, self-control, and various contextual factors (e.g., school disorganization) on delinquency. This nuanced, cross-cultural perspective enhanced their study's findings, and it contributed to a more comprehensive understanding of the applicability of SAT across diverse cultural settings.
In another study, Kokkalera et al. (2020) investigated the cross-cultural applicability of SAT across 13 countries, which were categorized by “contextual morality.” Specifically, the study analyzed whether SAT operated differently in countries with low versus high contextual morality. Their results showed that SAT is a generalizable theory, as the effects of criminal propensity, self-control, and personal morality were consistent across both cultural clusters. Notably, they found higher exposure to criminogenic influences in “high contextual morality” countries, which suggests that delinquent behavior is more prevalent when personal morality conflicts with the broader moral context. Additional studies, which have been carried out in diverse countries, have consistently affirmed the credibility of SAT's theoretical propositions in predicting deviant behavior. Such locations include Germany (Ernst & Gerth, 2023), Belgium (Vanwersch et al., 2024), Austria (Barton-Crosby & Hirtenlehner, 2021), China (Liu et al., 2022), Nigeria (Akinyetun, 2021), India (Kokkalera et al., 2020), South Korea (Song & Lee, 2020), Iran (Kabiri et al., 2024), and Japan (Fujino, 2023). This body of research demonstrates the cross-cultural applicability of SAT, and it provides a cultural context for the current study.
Current Study
According to SAT, deviant behavior, such as academic cheating, is a product of crime propensity and criminogenic setting (Wikström, 2004). Thus, predicting academically fraudulent actions needs an integrative formulation of students’ propensity to crime (i.e., personal morality and self-control) and exposure to criminogenic moral settings (i.e., situational morality and deterrence). Based on theory and prior research (e.g., Hirtenlehner & Hardie, 2016; Svensson et al., 2017; Wikström, 2004), we propose eight hypotheses.
Initially, we predict that academic dishonesty is significantly related to criminal propensity (Hypothesis 1). Cheating is more likely to occur among students with a greater propensity for deviance. Second, we predict that academic dishonesty is significantly related to criminogenic exposure (Hypothesis 2). Cheating should be more prevalent among those experiencing greater exposure to deviance. Third, we predict that the interaction between crime propensity and criminogenic exposure is significantly related to academic dishonesty (Hypothesis 3). Cheating should be more likely among students whose propensity combines with their exposure.
Additionally, we put forth several interactive hypotheses. Specifically, we predict that there is significant two-way interaction terms of personal morality and self-control (Hypothesis 4a), personal morality and situational morality (Hypothesis 4b), and personal morality and deterrence (Hypothesis 4c). We propose that these interactive terms will demonstrate positive relationships with academic dishonesty such that the interaction between propensity and exposure will heighten the likelihood of deviant engagement.
Lastly, we predict that personal morality moderates the effect of self-control on the relationship between situational morality, deterrence, and academic dishonesty. Specifically, we propose that the effect of internal and external controls on deviant behavior can be conditioned based on the level of one's morality. Thus, the interactions between self-control × situational morality (Hypothesis 4d) and between self-control × deterrence differ across levels of personal morality (Hypothesis 4e). The effects of these interaction terms should be stronger when one's personal morality is lower.
Methods
Data and Sample
The present study is based on a cross-sectional analysis of 378 university students who participated in a survey during the spring of 2019. Data was collected from students at the University of Guilan, and in-person surveys were used to collect the data. The participants encompassed a diverse array of academic disciplines including sociology, mathematics, engineering, literature, psychology, law, management, computer science, architecture, and agriculture. When the list of sampled students was determined, the students were contacted and notified that a survey would be administered in the university lounge during a break from class. Researchers explained the purpose of the study, followed informed consent procedures, and asked the students for voluntary participation.
The theoretical population of students from which the sample has been drawn was approximately 18,000 students. We calculated the adequate effect size using G*Power software with power (1–β err prob) set at 0.99 and α err prob = .01, two-tailed. To detect the medium effect size (Effect size f² = 0.15), a total sample of 219 would be needed with four predictors (personal morality, self-control, deterrence, and situational morality). To ensure that we obtained the appropriate sample size, we oversampled to collect the requisite number of questionnaires. Thus, researchers distributed 400 questionnaires, and data from 378 respondents remained after excluding missing data (response rate = 94.5%). Please see Table 1 for sample characteristics.
Sample Characteristics (n = 378).
Dependent Variable
Our dependent variable is an additive index of academic dishonesty, and we measured it using Cochran's (2015) six-item scale. Participants were asked how often they engaged in the following behaviors in the past year: (a) looked at another student's answers during an exam, (b) plagiarized a term paper, (c) had another student take an exam for you, (d) got illicit, advance copies of an exam, (e) lied to a professor about missing an exam, and (f) falsified information on a research paper. Responses were on a five-point Likert scale (1 = never; 5 = always), with higher values representing greater dishonesty. Please see Table 2 for validity and reliability statistics for all scaled variables. 3
Validity and Reliability of Scaled Variables.
Note. Model fit summary: CMIN = 255.73, df = 220, p = .049, CMIN/df = 1.162, CFI = .994, SRMR = .035, RMSEA = .021, PClose = 1.000.
Independent Variables
SAT argues that people are different in terms of their propensity to commit a crime. The law-relevant morals of an individual, and their ability to exercise self-control, are considered the main subcomponents of propensity to crime (Wikström, 2020). Therefore, we created a composite measure for a respondent's propensity to academic dishonesty by multiplying together personal morality and self-control. Using a four-item scale, the respondents’ personal morality evaluation of academic dishonesty was measured. The original items were adopted from the previous work of Cochran (2015). Participants were asked to indicate their agreement with the following statements: (a) I feel that it would be wrong for me to engage in any kind of academic dishonesty for any reason (reverse coded), (b) I think that academic dishonesty is not morally wrong if I do not have enough time to study or do my homework, (c) I feel academic dishonesty would be okay if the professor had not done an adequate job of teaching the course, and (d) I feel academic dishonesty would be acceptable to avoid poor grades. The response options ranged from 1 (completely disagree) to 5 (completely agree). Here, higher values represent lower morality.
To measure self-control, a six-item scale from Wikström et al. (2012) was utilized. Respondents were asked to indicate their level of agreement with the following items: (a) I often act on the spur of the moment without stopping to think, (b) I often try to avoid things that I know will be difficult, (c) I lose my temper pretty easily, (d) When I am really angry, other people better stay away from me, (e) I often take a risk just for the fun of it, and (f) Sometimes I find it exciting to do dangerous things. Responses were coded on a 5-point Likert scale (1 = completely disagree; 5 = completely agree) in which higher values represent lower levels of self-control.
Wikström (2004; 2017) asserts that the criminogeneity of a setting depends on both the situational morality of the environment and the deterrent quality of the setting. We multiplied situational morality and deterrence to create a composite measure of an individual's criminogenic exposure to academic dishonesty. Students with low criminal exposure values spend little time in criminogenic places, while students with high values spend much time in criminogenic school places.
A three-item situational morality variable was used from Shadmanfaat et al. (2020). Respondents answered the following items on a five-point Likert scale (1 = strongly disagree; 5 = strongly agree): (a) People around me whose opinions I value (e.g., my family, friends, colleagues, teachers, etc.) believed that educational cheating is acceptable for passing a course, (b) Most of the people who are important to me believed that academic dishonesty is not wrong to stay in university or to graduate, and (c) Most of my friends believed that educational defrauding is OK if a close friend asks for help. Here, higher values represent lower situational morality.
To capture perceived deterrence, we used a measurement scheme of certainty and severity of educational cheating developed by Cochran (2015). Two items were used to form an indicator of perceived sanction certainty. Respondents were asked to rate their agreement with the following two items: (a) I would get caught by my professors or officials if I engage in any kind of exam cheating and (b) I would get caught by my professors or officials if I engage in any kind of cheating related to homework or scientific projects. Perceived severity was also measured using a two-item scale: (a) It would be a big problem for me if I were caught and formally punished by university officials because I engaged in any kind of exam cheating and (b) It would be a big problem for me if I were caught and formally punished by university officials because I engaged in any kind of cheating for doing my homework or scientific projects. All four items were measured on a five-point Likert scale (1 = completely agree to 5 = completely disagree), and they were combined to create a deterrence variable in which higher values reflect lower ratings of perceived deterrence.
Control Variables
Based on prior research (e.g., Hirtenlehner & Hardie, 2016; Svensson et al., 2017), we control for four covariates in this study. Gender is a dichotomous variable (0 = female; 1 = male). Age is a ratio variable and refers to the respondents’ age at the time of data collection. Education is a four-category ordinal variable representing the students’ enrolled program (associate's degree, bachelor's degree, master's degree, doctoral degree). Lastly, marital status is a dichotomous variable (0 = single; 1 = married).
Analytic Strategy
The analyses proceed in two main steps. First, bivariate correlations are used to examine initial relationships between the independent variables and the dependent variable. Second, a series of thirteen OLS regression models are estimated to investigate the effect of the situational action model on academic dishonesty. 4 These models allow us to assess the direct effects of the independent (and control) variables on academic dishonesty as well as to examine the cadre of moderated relationships specified by SAT.
This study followed prior research which focused on testing the main hypothesis of SAT theory, namely, the interaction between propensity to crime and criminogenic settings. According to Jaccard and Turrisi (2003), a simple (i.e., two-way) interaction occurs when the magnitude of the effect of one independent variable on a dependent variable varies as a function of a second independent variable. In order to improve the testability of the theoretical propositions of SAT, this research utilized a higher-order (i.e., three-way) moderating model. A three-way interaction occurs when the magnitude of the effect of a third independent variable on a dependent variable varies as a function of a preestablished two-way interaction term. However, to obtain the unique effect of the higher-order interaction term, all lower-order (i.e., two-way) interaction terms need to be included so that the interaction coefficient represents a unique effect (see also, Dawson & Richter, 2006; Jaccard & Turrisi, 2003). This modeling strategy examines the influence of personal morality compared to self-control as suggested by Wikström (2004), and such a strategy has only been explored in two previous studies (Hirtenlehner & Treiber, 2017; Kabiri et al., 2024). The higher-order (i.e., three-way) moderating model is implemented here to investigate the interactive effect of personal morality and self-control on academic dishonesty. Specifically, this modeling strategy analyzes the interaction effect of personal morality as a higher-order moderating variable on the interactive relationship between self-control × deterrence on academic dishonesty as well as on the interactive relationship between self-control × situational morality on academic dishonesty. Through this analysis, we can determine whether personal morality has a greater moderating effect than self-control on the propositions of SAT set forth by Wikström (2004).
Results
As shown in Table 3, students’ academic dishonesty is associated with the independent variables derived from SAT. Moreover, the correlations between academic dishonesty and the elements of SAT demonstrate moderately strong relationships (r > .347). Specifically, academic dishonesty is positively correlated with personal morality (r = .434, p < .01), self-control (r = .347, p < .01), situational morality (r = .349, p < .01), and low deterrence (r = .369, p < .01). Recall that higher values reflect lower levels of the SAT concepts; thus, these results provide initial support for the influence of SAT on academic dishonesty.
Zero-Order Correlations among Study Variables of Interest.
*p < .05; **p < .01
Table 4 presents the results of the OLS regression analyses. Model 1 indicates the main model for academic dishonesty, where independent and demographic variables are entered. Findings indicate that personal morality (b = .25, p < .01), self-control (b = .14, p < .01), situational morality (b = .16, p < .05), and deterrence (b = .21, p < .01) have a significant effect on academic dishonesty. This provides evidence that SAT components are influential in explaining cheating. Furthermore, being male (b = .11, p < .01) was positively related to academic dishonesty, while age (b = –.12, p < .05) and education (b = –.11, p < .05) were negatively related to it.
OLS Regression Models Predicting Academic Dishonesty (n = 378).
Note. High = + 1 SD, moderate = mean, low = –1 SD.
*p < .05; **p < .01.
In Models 2 and 3, propensity and exposure are analyzed. Hypothesis 1 was supported as propensity was related to cheating (b = .32, p < .01). Moreover, Hypothesis 2 was supported as exposure was also significantly related to cheating (b = .31, p < .01). Propensity to engage in deviance was then examined as a moderating factor between exposure and academic dishonesty. Based on Model 3, there is an increase of 1% in the predictive power of the main effect when personal morality is included (R2 change = .01, F change = 6.13, p < .05). It was determined that the interaction term of propensity × exposure was significantly related to academic dishonesty (b = .10, p < .05), which lends support to Hypothesis 3. Using slope tests (see Figure 1), it was shown that the relationship between exposure and academic dishonesty was significant when propensity was low (b = .24, p < .01), moderate (b = .35, p < .01), and high (b = .45, p < .01).
Two-way interaction of propensity and exposure on academic dishonesty.
In Model 5, we began to investigate the moderation effect of personal morality. When personal morality is included in Model 5, the predictive power of the main effect increases by 0.1% (R2 change = .001, F change = .05, n.s.). No significant interaction effect was found between personal morality and self-control on academic dishonesty; thus, Hypothesis 4a was not supported. Similarly, in Model 7, no significant interaction effect was found between personal morality and situational morality on academic dishonesty, meaning that Hypothesis 4b was also not supported. Personal morality increased the prediction power of the main model by 0.1%, (R2 change = .001, F change = .18, n.s.). However, in Model 9, the interaction term of personal morality and deterrence did significantly affect academic dishonesty (b = .03, p < .05), which specifies support for Hypothesis 4c. Using slope tests, it was shown that the relationship between deterrence and academic dishonesty was significant when personal morality was low (b = .28, p < .01), moderate (b = .43, p < .01), and high (b = .57, p < .01).
Data provided us with the opportunity to explore two three-way interactions that have relevance in the context of SAT. According to our hypothesis, low morality can further moderate the role of self-control in the relationships between low situational morality, low deterrence, and academic dishonesty. Specifically, a three-way interaction means that there can be two-way interactions such as low self-control × low deterrence—or low self-control × low situational morality—that vary across levels of low morality. Both Models 11 and 13 exhibit higher-order interaction tests.
As expected, Model 11 demonstrated a significant three-way interaction between personal morality, self-control, and situational morality (b = .22, p < .01), providing support for Hypothesis 4d. Adding the three-way interaction term increased the predictive power of the main effect by 4% (R2 change = .04, F change = 21.76, p < .01). Conditional analysis of predictors for low, moderate, and high values of the moderator (see Figure 2) found that the slope of the effect of situational morality on academic dishonesty under the condition of low self-control is significant when personal morality is moderate (b = .03, p < .05) or high (b = .08, p < .01). Also, as expected, Model 13 demonstrated a significant three-way interaction between personal morality, self-control, and deterrence (b = .13, p < .05), providing support for Hypothesis 4e. Adding the three-way interaction term increased the predictive power of the main effect by 1% (R2 change = .01, F change = 6.37, p < .01). Conditional analysis of predictors for low, moderate, and high values of the moderator (see Figure 2) found that the slope of the effect of deterrence on academic dishonesty under the condition of low self-control is significant when personal morality is moderate (b = .03, p < .05) or high (b = .05, p < .01). Overall, these latter findings provide mixed support for the moderated hypotheses (Hypotheses 4a–e).
Three-way interactions of SAT variables on academic dishonesty.
Discussion
Academic dishonesty is a universal ethical dilemma. Studies have shown that academic cheating is a prevalent problem and have uncovered several individual differences in academic dishonesty by applying different theoretical frameworks. One of the promising contemporary theories in illuminating why students engage in various types of academic dishonesty is SAT.
While SAT has attracted the attention of an increasing number of criminologists in explaining deviant behavior, our study is one of the first attempts to test the applicability of this theoretical framework in the realm of academic fraud. Moreover, SAT has mainly been tested in European and American contexts, with some noteworthy exceptions (Kokkalera et al., 2020). Thus, this study adds to a welcomed trend of testing theories cross-culturally. Since the original data were collected in Iran, the findings contribute to the evaluation of key propositions of SAT in different contexts. In our examination of SAT, we found that students’ academic dishonesty is an outcome of both propensity to academic dishonesty and exposure to moral settings that are conducive to academic cheating—as well as the interaction between the two. These results are consistent with both theory and prior research (e.g., Cochran, 2015, 2016; Ernst & Gerth, 2023).
In the context of Iran, previous research indicates that academic fraud is prevalent (e.g., Ebrahimi et al., 2021; Mohammad Hosseinpur et al., 2018; Yekta et al., 2010). Research has shown that unauthorized sharing of exams (87%), copying each other's answers (80%), and pointing particular fingers to indicate the correct answer (70%), are the most common forms of cheating (e.g., Aliverdinia & Salehnejad, 2013; Fealy et al., 2014). As a matter of criminogenic context, Iranian scholars note that the majority of students have conveyed that their classmates and friends do not view academic cheating as a deviant behavior (Yekta et al., 2010). Likewise, inadequate monitoring policies, as well as a disparity between benefits and costs of academic dishonesty, are among the factors that contribute to academic fraud (Aliverdinia et al., 2016; Aliverdinia & Salehnejad, 2013).
We further scrutinized the nature of the key moderating relationships that have been tested in SAT by exploring both two-way and three-way interactions. Although prior research has documented a moderating effect of personal morality in the relationship between self-control and offending (Pauwels, 2012; Wikström & Treiber, 2009), the result of our data analysis revealed no such interactive relationship. Moreover, we did not find support for the interactive relationship between personal morality and situational morality on academic dishonesty. Both of these were contrary to our expectations. However, we did find a moderating effect between personal morality and deterrence on academic cheating, which supported our hypothesis. Recent research by Bahrami et al. (2015) indicated that approximately 30% of students cited personal morality and beliefs as the most important factor in preventing cheating. This illustrates the important role that individual morality plays in mitigating the effect of a perceived level of deterrence on academic dishonesty.
Among the three-way interactions, we found support for both of our hypotheses. Specifically, our data showed significant interactive relationships on academic dishonesty among personal morality × self-control × situational morality as well as among personal morality × self-control × deterrence. More precisely, our analyses revealed that the effect of situational morality on academic dishonesty under the condition of low self-control is significant when personal morality is moderate or high, and that the effect of deterrence on academic dishonesty under the condition of low self-control is significant when personal morality is also moderate or high. In recent studies conducted in Iran, the importance of personal morality has been emphasized (Aliverdinia & Salehnejad, 2013; Mohammad Hosseinpur et al., 2018). It has been argued that law-abiding morals and values hinder students from engaging in academic fraud regardless of the degree to which a setting might be criminogenic (Aliverdinia & Salehnejad, 2013). Although we found a few mixed results, our findings generally support the overall premises offered by SAT.
Implications for Policy and Practice
A successful pattern of academic dishonesty reduction emerges from policies and interventions that increase students’ awareness of academic cheating as unacceptable behavior and develop their abilities to respond effectively to environmental provocation in academic settings (e.g., Wikström & Treiber, 2017). Such a strategy is based on the premise that policies and interventions that effectively change actors’ perceptions and selection processes are necessary for crime prevention. In the context of SAT, this encompasses two, broad intervention techniques. First, to decrease criminal propensity—moral capacities and self-control abilities—psychosocial processes of moral education and cognitive nurturing are crucial. Second, situational provocations, such as opportunities for academic dishonesty and situational morality toward academic cheating, must be dealt with in an efficient social-ecological manner.
Concerning the development of moral capabilities and self-control, Wikström (2017) asserts that in the majority of criminogenic environments, there is little impact of environment-related provocations on individuals with low criminal propensities. The criminogenic setting, therefore, has a very limited effect on students’ perceptions of academic cheating as an alternative action when criminal propensity decreases. As per the theory, moral training is the best practice for enhancing moral capacity and cognitive training is the best method for strengthening individuals’ ability to exercise self-control (Wikström & Treiber, 2016). There are three main mechanisms that contribute to the moral training process: (a) ethical guidelines; (b) observation; and (c) trial and error (Wikström & Treiber, 2017). Through personal communication with ethics educators or media consumption, ethical guidelines can be learned. Observation involves watching how others behave, as well as the consequences of certain actions in different situations. Particularly at an early age, much of this can be traced back to the role of effective parenting, in which primary caregivers need to be able to monitor their child's behavior, recognize deviant behavior, and punish such behavior (e.g., Gottfredson & Hirschi, 1990). In many ways, this is similar to authoritative parenting, which combines emotional warmth with firmness while maintaining an open dialogue with the child (Baumrind, 1996). Lastly, trial and error involves one's own experiences, as well as others’ reactions and behavioral consequences.
The three processes mentioned above lead to the development of social norms/rules and the institution of formal and informal consequences for violating these laws. Thus, one of the most significant ways to prevent academic cheating is to promote law-related ethics and provide opportunities for students to observe and practice ethical behaviors. In its capacity as an effective social institution, the family and universities can play a significant role in internalizing moral values. In the case of students, parents and teachers are the most effective moral educators. It is their role to create an ethical context, and their efforts could serve to reduce the amount of academic dishonesty among students. Therefore, encouraging parents and teachers to become actively involved in moral training as well as monitoring students’ behavior and thoughts will be critical to preventing academic dishonesty. The following steps are suggested by Narvaez and Lapsley (2009) in developing moral identity as part of an effective moral-based strategy: (a) children should be raised with caring relationships by adults; (b) adults are responsible for creating an environment that encourages excellence in accomplishment and ethical character; (c) it is the responsibility of adults to develop ethical skills in a variety of activities (including curricular and extracurricular) by focusing on ethical sensitivity, judgment, focus, and actions; (d) parents encourage their children to be self-authorized and self-regulatory, and (e) adults collaborate in building communities that provide support and relationships across institutions for the purpose of fostering resilience (Narvaez & Lapsley, 2009).
The next dimension of cognitive development relates to the experiential processes that impact neurocognitive function in a direct and positive manner (Wikström & Treiber, 2016). Cognitive functions that influence the ability to exercise self-control are executive functions; specifically, those associated with abstract thinking, problem-solving, cognitive flexibility, and goal-directed behaviors (Wikström & Treiber, 2017). At a time when codes of ethics cannot guide behavior, these cognitive functions have become increasingly important for comparing options and making decisions (Wikström & Treiber, 2017). In order to enhance the ability of people to exercise self-control, the exercise of executive capabilities should be encouraged. Self-control ability can best be fostered by giving students opportunities to trigger, calculate, and retain action-relevant information (e.g., through working memory activities or cognitive fluency tasks), and/or suppress conflicting action processes (e.g., through tasks that require inhibition). Enhancing executive functions, which enhance the ability to exercise self-control, may also be effective in preventing people from developing a criminal behavior. Moreover, cognitive nurturing can enhance a person's ability to understand, internalize, and apply shared rules of conduct. A similar claim is made by Wikström and Treiber (2017) that family and school play an important role in cognitive development. These organizations serve two purposes: (a) They provide opportunities for students to improve their executive functioning skills; and (b) They influence how students interact and respond to those opportunities.
Psychological interventions should be used to overcome deficits related to cognitive and executive dysfunction in early childhood. Others have suggested that authorities should implement training programs aimed at promoting restraint and ethical behavior (Kabiri et al., 2020). A primary prevention and intervention approach should be employed in order to achieve the best results (e.g., Piquero et al., 2016). The development of self-control over time has been shown to be possible in recent studies (e.g., Muraven, 2010). This research shows how, similar to muscles in the body, a person's level of self-control can be strengthened by repeated exercise. To that end, children could benefit from programs (e.g., Promoting Alternative Thinking Strategies, Syracuse Family Development program, Incredible Years program) that seek to teach them (a) how to recognize problem situations and react in an appropriate manner, (b) self-control and anger management skills, (c) how to recognize one's feelings and emotions, (d) how build a positive self-image, and (e) how to solve problems (Lab, 2023).
The second, broad intervention effort centers on environmentally-focused policies and practices. More specifically, to combat academic dishonesty educational institutions should consider the guidance of situational crime prevention (e.g., Hodgkinson et al., 2016). Based on the work of Clarke (1995), situational crime prevention promotes effective crime reduction through 25 techniques within five main categories: (a) increase the effort, (b) increase the risks, (c) reduce the rewards, (d) reduce provocations, and (e) remove excuses. According to Clarke, situational factors can stimulate crime by providing increased opportunity for crime. Thus, the reduction of crime requires the reduction of opportunity.
Hodgkinson et al. (2016) suggest that schools can effectively alter the criminogenic situation by employing such techniques. For example, schools can adopt target hardening by keeping exams under lock and key, extend guardianship by employing additional exam proctors, assist natural surveillance by not allowing students to wear hats in the classroom, deflect offenders by utilizing alternate seating arrangements, conceal targets by avoiding the re-use of exams, avoid disputes by giving clear guidance on academic misconduct, and alert conscience by having students sign “no plagiarism” declarations. Each of these prevention techniques is designed to deter a potential offender by altering one's rational calculus of the costs and benefits of the misbehavior. Toward that end, several prior studies have confirmed the importance of situational prevention techniques in reducing academic dishonesty (e.g., Baird & Clare, 2017; Freiburger et al., 2017; Ogilvie & Stewart, 2010).
Study Limitations and Directions for Future Research
Despite the promising results, there are a few study limitations that should be acknowledged. First, although a random sampling procedure was used, we gathered the data from a single university in Iran. Therefore, the generalizability of the findings should be viewed with caution. Future research should attempt to replicate our results through the use of more diverse samples in order to increase external validity. Second, this study utilized cross-sectional data, which hinders causal interpretations. Future research should collect longitudinal data in an effort to examine the causality of these situational action relationships as well as to explore trends in academic dishonesty over time. Third, our examination of a situational theory was tested with nonsituational data (see e.g., Hardie, 2020). While tests of SAT deal with interactions, one should remember that the theory is concerned with spatio-temporal convergence. We tried to overcome this problem by measuring all concepts with reference to academic settings. However, future studies of the relationship between SAT and academic cheating may want to overcome this problem by using vignettes (i.e., randomized scenarios) in which the moral propensity of the context—and its deterrent qualities—are more directly measured. Fourth, our measure of personal morality is somewhat limited in capturing one's moral filter. When measuring personal morality, future research should take into account specific relevant moral emotions (e.g., anticipated guilt, anticipated shame, moral anger). Fifth, this study was limited in its inclusion of control variables and can suffer from omitted variable bias. While we were able to control for certain demographic variables (e.g., age, education, marital status), we recommend that future studies include a more comprehensive set of control variables (e.g., socio-economic status, race) to further tease out the effects of the predictor variables.
Conclusion
The current cross-cultural study was able to demonstrate the efficacy of Wikström's SAT as a viable model to explain academic dishonesty among a sample of college students from Iran. Specifically, the results indicated that personal morality, self-control, deterrence, and situational morality all had predictive utility in explaining students’ academic cheating. Further results demonstrated important moderated relationships among the situational action variables. The findings suggest that the interaction between criminogenic propensity and criminogenic exposure is important in the context of academic dishonesty. Building on a growing body of scholarship, the current study offers further insight into why students engage in cheating, and the findings offer practical implications that can be implemented in an attempt to reduce such deviant behavior.
Footnotes
Acknowledgments
The authors would like to express their appreciation to the journal editor and to the anonymous reviewers for their comments and suggestions on an earlier draft of this manuscript. This version has been considerably improved because of their efforts.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
