Academic misconduct: An examination of its association with the dark triad and antisocial behavior

Understanding Academic Dishonesty in University Settings: The Interplay of Dark Triad Traits and Moral Disengagement

Understanding the correlates of academic dishonesty is crucial for designing effective preventive interventions, as is the investigation of moderating factors that could affect these interactions. Despite increased interest in the Dark Triad personality traits and their potential link with unethical behavior, there is limited evidence regarding the moderating role of moral disengagement in the relationship. This study aimed to investigate academic dishonesty among Greek university students, its relationship with the Dark Triad, and the moderating role of moral disengagement, using gender as a covariate. Overall, 587 students attending Greek public Universities voluntarily completed an anonymous self-report questionnaire assessing the constructs under investigation. Results showed that male students had higher scores in unauthorized collaboration, plagiarism, Dark Triad, and moral disengagement. Moderation analysis indicated that moral disengagement had an effect in the relationship of psychopathy with unauthorized collaboration, especially among men. Overall, the findings of this study highlight the importance of psychopathy and moral disengagement in the prediction of academic dishonesty and have the potential to make a significant contribution to its prevention, particularly in Greek universities where relative initiatives are lacking.

Cheating in childhood: Exploring the link between parental reports of problem behaviors and dishonesty on simulated academic tests

This study investigated the relationship between parental reports of children's behavioral problems and their cheating behaviors on simulated academic tests, addressing a significant gap in understanding early childhood academic cheating and its potential links to broader behavioral issues. We hypothesized that children's early problem behaviors would be predictive of their academic cheating. To test these hypotheses, children aged 4 to 12 years took part in six unmonitored academic tests that measured their cheating behaviors while their parents completed the Child Behavior Checklist and the Strengths and Difficulties Questionnaire elsewhere. Separate hierarchical linear regressions revealed that children's problem behaviors, as reported by parents, overall significantly predict children's cheating behaviors even after accounting for demographic variables such as age, gender, ethnicity, and parental religiosity. Specifically, the Conduct Problems subscale of the Strengths and Difficulties Questionnaire showed a significant and unique association with children's cheating behaviors above and beyond the common contributions of all predictors. However, the Child Behavior Checklist scores and the scores on the other Strengths and Difficulties subscales were not significantly or uniquely related to cheating. These findings offer new insight into simulated childhood academic cheating and its relation to problem behaviors observed by parents.

Gender-based differences in the impact of Dark Triad traits on academic dishonesty: The mediating role of moral disengagement in college students

This study explores whether gender differences influence the components of the Dark Triad of personality and moral disengagement on the manifestations of dishonest academic behavior in Peruvian university students. Moreover, it evaluates how moral disengagement mediates the effect that the Dark Triad components have on academic dishonesty. The participants were 591 university students, aged between 18 and 40 years (women = 71.7 %; Mage = 21.5; SDage = 3.60), to whom the Dirty Dozen Dark Triad, the Propensity to Morally Disengage Scale, and the Scale of Academic Dishonesty, which has 3 dimensions (cheating on exams, plagiarism, and falsification) were applied. The results reveal that only Machiavellianism has a significant and consistent influence on all dimensions of academic dishonesty, in both men and women, while psychopathy influences the dimension of plagiarism in both men and women and falsification only in men. In addition, moral disengagement affects falsification in both groups, cheating on exams only in the men's group, and plagiarism in the women's group. Finally, the mediating role of moral disengagement between the effect of the Dark Triad and the manifestations of academic dishonesty was not demonstrated.

HEXACO, the Dark Triad, and Chat GPT: Who is willing to commit academic cheating?

The rise in popularity of Chat GPT, an advanced language model that uses deep learning techniques to simulate human-like conversation, has raised concerns about its potential misuse, particularly in academic contexts. The present study (N = 283) explored the relationship between personality traits and the intention to use chatbot-generated texts for academic cheating. Among the HEXACO and Dark Triad traits, Honesty-Humility, Conscientiousness, Openness to Experience (all negative), Machiavellianism, narcissism, and psychopathy (all positive) were significant predictor variables. A multiple regression analysis showed that Honesty-Humility had the most robust association with the intention to use chatbot-generated texts for academic cheating. Further analyses on the facet level revealed that the fairness facet of Honesty-Humility was the most predictive, suggesting that individuals high in Honesty-Humility refrain from using chatbot-generated texts for academic cheating as they prioritize fairness over their own interests. Promoting Honesty-Humility and its fairness facet can be a valuable approach to promoting ethical behavior in academic and other contexts.

Student Perceptions of Academic Integrity: A Qualitative Study of Understanding, Consequences, and Impact

Background

Academic integrity (AI) is of increasing importance in higher education. At the same time, students are becoming more consumer-oriented and more inclined to appeal against, or complain about, a penalty imposed for a breach of AI. This combination of factors places pressure on institutions of higher education to handle alleged breaches of AI in a way acceptable to students that motivates them to continue to engage with their studies.

Method

Students (n = 8) were interviewed to discover their perceptions of the process for dealing with breaches of AI. All students were based in one university in a very diverse area of London which has many first-generation students from non-traditional academic backgrounds.

Results

Students reported strong emotional reactions featuring high levels of anxiety and stress. Some found the process to be threatening and demotivating and questioned continuation on their course of study, while others used more adaptive coping strategies. Students also went to great pains to make it clear that their own, and their friends', breaches of AI were unintentional, while expressing the view that other people were deliberately cheating and should be penalised.Key recommendations include: support for students to re-engage after the intervention; support for students to develop effective self-regulatory learning strategies and time management; provision of specific examples to clarify what is, and is not, acceptable academic practice; recognition of the strong emotions likely to be invoked, especially if accompanied by declarations of unintentionality.

Taking the chance!-Interindividual differences in rule-breaking

While some individuals tend to follow norms, others, in the face of tempting but forbidden options, tend to commit rule-breaking when this action is beneficial for themselves. Previous studies have neglected such interindividual differences in rule-breaking. The present study fills this gap by investigating cognitive characteristics of individuals who commit spontaneous deliberative rule-breaking (rule-breakers) versus rule-followers. We developed a computerised task, in which 133 participants were incentivised to sometimes violate set rules which would-if followed-lead to a loss. While 52% of participants tended to break rules to obtain a benefit, 48% tended to follow rules even if this behaviour led to loss. Although rule-breakers experienced significantly more cognitive conflict (measured via response times and mouse movement trajectories) than rule-followers, they also obtained higher payoffs. In rule-breakers, cognitive conflict was more pronounced when violating the rules than when following them, and mainly during action planning. This conflict increased with frequent, recurrent, and early rule-breaking. Our results were in line with the Decision-Implementation-Mandatory switch-Inhibition model and thus extend the application of this model to the interindividual differences in rule-breaking. Furthermore, personality traits such as extroversion, disagreeableness, risk propensity, high impulsiveness seem to play a role in the appreciation of behaviours and cognitive characteristics of rule-followers and rule-breakers. This study opens the path towards the understanding of the cognitive characteristics of the interindividual differences in responses towards rules, and especially in spontaneous deliberative rule-breaking.

Machiavellian Medical Students Report More Academic Misconduct: A Cocktail Fuelled by Psychological and Contextual Factors

Purpose

Maladaptive personality traits and some psychological functioning indicators have been linked to academic misbehaviour; yet their role is still poorly explored in medical students. This study aims to assess associations of academic misconduct with dark personality traits and psychological well-being.

Methods

Five hundred and ninety-one medical students attending the first, third and fifth-year at one Portuguese medical school replied to the Dark Triad Dirty Dozen, Ryff’s Psychological Well-Being Scales and an original Academic Misconduct Questionnaire, using a cross-sectional design. Multiple linear regression was performed to assess associations.

Results

Fifth-year medical students who scored higher in Machiavellianism and psychological well-being and perceived greater peer fraud and lower penalty for cheating reported more academic misconduct. The explanatory power of the model was 16.6%. Machiavellianism showed the strongest associations with cheating, while sex and age were not significant predictors.

Conclusion

This study offers relevant insights into how maladaptive personalities influence academic misconduct in medical students, and how this relationship is moulded by psychological and contextual factors. These findings can help guide institutional actions to foster academic integrity in future physicians.

Suspicious activity recognition for monitoring cheating in exams

Video processing is getting special attention from research and industries. The existence of smart surveillance cameras with high processing power has opened the for making it conceivable to design intelligent visual surveillance systems. Know a day it is very possible to assure invigilators safety during the examination period. This work aims to distinguish the suspicious activities of students during the exam for surveillance examination halls. For this, a 63 layers deep CNN model is suggested and named "L4-BranchedActionNet". The suggested CNN structure is centered on the alteration of VGG-16 with added four blanched. The developed framework is initially turned into a pre-trained framework by using the SoftMax function to train it on the CUI-EXAM dataset. The dataset for detecting suspicious activity is subsequently sent to this pre-trained algorithm for feature extraction. Feature subset optimization is applied to the deep features that have been obtained. These extracted features are first entropy coded, and then an ant colony system (ACS) is used to optimize the entropy-based coded features. The configured features are then input into a variety of classification models based on SVM and KNN. With a performance of 0.9299 in terms of accuracy, the cubic SVM gets the greatest efficiency scores. The suggested model was further tested on the CIFAR-100 dataset, and it was shown to be accurate to the tune of 0.89796. The result indicates the suggested frameworks soundness.

Academic dishonesty among university students: The roles of the psychopathy, motivation, and self-efficacy

Academic dishonesty is a common problem at universities around the world, leading to undesirable consequences for both students and the education system. To effectively address this problem, it is necessary to identify specific predispositions that promote cheating. In Polish undergraduate students (N = 390), we examined the role of psychopathy, achievement goals, and self-efficacy as predictors of academic dishonesty. We found that the disinhibition aspect of psychopathy and mastery-goal orientation predicted the frequency of students' academic dishonesty and mastery-goal orientation mediated the relationship between the disinhibition and meanness aspects of psychopathy and dishonesty. Furthermore, general self-efficacy moderated the indirect effect of disinhibition on academic dishonesty through mastery-goal orientation. The practical implications of the study include the identification of risk factors and potential mechanisms leading to students' dishonest behavior that can be used to plan personalized interventions to prevent or deal with academic dishonesty.