Form Of Cheating Research Articles

Understanding the benefits and pitfalls of artificial intelligence

About half of people who use artificial intelligence (AI) don’t want anyone else to know. That's because they’re worried about seeming replaceable in their jobs, especially if they work in academia. Or they’re concerned that AI use might not be permitted or that it qualifies as some form of cheating, according to Beth Ziesenis, owner of yournerdybestfriend.com.

Understanding the benefits and pitfalls of artificial intelligence

About half of the people who use artificial intelligence (AI) don’t want anyone else to know they use it. That's because they’re worried about seeming replaceable in their jobs, especially if they work in academia. Or they’re concerned that AI use might not be permitted or that it qualifies as some form of cheating, according to Beth Ziesenis, owner of yournerdybestfriend.com.

Did Facebook Cheat?: A Test Case of Antitrust Ethics

Citing corporate concentration and lax enforcement since the Reagan era, the Biden administration has declared a new era of aggressive antitrust prosecution, bringing antimonopoly actions against tech giants such as Meta, Google, and Amazon. But what’s so bad about monopoly or corporate concentration? The standard answer appeals to economic consequences, such as higher prices or deadweight losses. This paper offers a different framework. It argues monopolizing can be a form of cheating, which is a wrong that attaches to means, not just ends; an athlete who cheats but loses still does wrong. In particular, this paper argues that certain market-controlling strategies constitute a form of cheating I call ‘structural cheating,’ best illustrated by the metaphor of creating an unlevel playing field: rather than compete fairly on merits such as product quality and price, a firm that acquires rivals biases the market in its favor, thereby entrenching a dominant position that effectively forces would-be competitors to compete uphill. By framing (alleged) antitrust violations as cheating, while using the FTC’s lawsuit against Facebook (now Meta) as a test case, this paper provides a needed corrective to those citing market success as evidence of merit or skill. A further upshot is the structural cheating account better explains the distinctively problematic features of social media market concentration than Heath’s Market Failures Approach. More generally, this paper provides a normative lens for analyzing fair market competition and shows why it’s not only winning or losing that counts in capitalism, but how one plays the game.

Why we should view the decision of medical trainees to cheat as the product of a person-by-situation interaction.

Cheating during medical training is a delicate subject matter with varying opinions on the prevalence, causes and gravity of cheating during training. In this article, the authors suggest that the decision to cheat is best viewed as the product of a person-by-situation interaction rather than indicating inherent dishonesty and/or extrinsic motivation in those who participate in cheating. This framework can explain why individuals who would typically default to honesty may participate in cheating if there is perceived justification for cheating and where situational variables, such as ease of cheating, rewards for cheating and perceived risk associated with cheating, make the decision to cheat appear rational. They discuss why the impression that there is a culture of cheating can provide perceived justification for medical trainees to cheat if they have the opportunity. They then describe how aspects of medical training and assessment may enable or hinder cheating by trainees. Consistent with the person-by-situation interaction framework, they contend that our response to cheating should include interventions directed at both the person who cheated and situational variables that enabled cheating. Recognising that some forms of cheating may be widespread, difficult to detect and contentious (such as the creation and use of exam reconstructs), their proposal for dealing with suspected and pervasive cheating is to identify and target enabling variables such that the decision to cheat becomes less rational. Their hope is that in so doing, we can gradually nudge trainees and the culture of medical training towards honesty.

Should Machine Translation have a role in language classrooms or not?

Presentation: https://www.pechakucha.com/presentations/sotel-2023-neil-cowie-and-keiko-sakui-machine-translation
 Machine translation (MT) of languages has been around nearly 30 years but the importance of its role in language learning has grown exponentially in recent years. This paper summarizes recent research on teacher and learner attitudes to MT, and suggests ways that MT can be used in language classrooms.
 Studies in the 2010s (Pym, 2013) suggest that teachers were against the use of MT because of its poor quality. However, the level of MT dramatically improved from 2016 when Google Translate adopted a neural-network system. As a result, teachers’ attitudes shifted to more acceptance of MT. Even so, teacher views about MT tend to fall into two camps: those who feel it is a form of cheating (Carré et al., 2022) and those who see it as an appropriate teaching tool. The former take the general approach of “detect, react and prevent”, whilst the latter wish to “integrate and educate” (Jolley & Maimone, 2022).
 Research has shown that students use MT in different ways according to their level. More advanced students tend to check words and phrases rather than translating a whole report. They understand the limits of MT but at the same time they believe it can help learn a language (Godwin-Jones, 2022; Jolley & Maimone, 2022). Research suggests that training in the use of MT can increase chances for such students to reflect on their language learning (Pellet & Myers, 2022) and that they can become aware of and correct MT errors (Zhang & Torres-Hostench, 2022). On the other hand, lower level students use MT differently as they may lack confidence in their language abilities (Organ, 2019). There are studies that claim lower level students can be linguistically overwhelmed in trying to notice and compare their own translations with MT; therefore, they do not correct the output of MT and submit it as their own work (Lee, 2022: Niño, 2020).
 In general, the accuracy of MT has improved so quickly that many teachers who previously dismissed MT as poor can no longer ascertain whether their students have actually used it or not (Jolley & Maimone, 2022). This creates doubt in how to assess student work fairly. Furthermore, as teachers vary in their attitudes towards the use of MT for learning, students can be very confused as to whether they are allowed to use MT in different teachers’ classes; and, if they are allowed, in what ways can they do so appropriately. In order to overcome this uncertainty and confusion, it is suggested that, after Reinders (2022), institutions, students and teachers become partners in exploring MT to find the best way to use it for learning. This will vary according to each educational context, particularly concerning student level, but it is vital to create commonly accepted guidelines, approaches and practices so that MT can be best used for language learning and not just as a tool to complete tasks with little or no educational meaning. 
 References
 
 Carré, A., Kenny, D., Rossi, C., Sánchez-Gijón, P. & Torres-Hostench, O. (2022). Machine translation for
 language learners. In D. Kenny (Ed.), Machine translation for everyone: Empowering users in the age of 
 artificial intelligence (pp. 187–207). Language Science Press. Doi: 10.5281/zenodo.6760024
 Godwin-Jones, R. (2022). Partnering with AI: Intelligent writing assistance and instructed language learning.
 Language Learning & Technology, 26(2), 5–24. https://doi.org/10125/73474
 Jolley, J. & Maimone, L. (2022). Thirty years of machine translation in language teaching and learning: A
 review of the literature. L2 Journal, 14(1). Doi: 10.5070/L214151760
 Lee, S.-M. (2022). Different effects of machine translation on L2 revisions across students’ L2 writing
 proficiency levels. Language Learning & Technology, 26(1), 1–21. https://hdl.handle.net/10125/73490
 Niño, A. (2020). Exploring the use of online machine translation for independent language learning. Research in 
 Learning Technology 28, 2402. https://dx.doi.org/10.25304/rlt.v28.2402
 Organ, A. (2019, July 5). L’éléphant dans la salle / la pièce / le salon? Student use of Google Translate for L2 
 production: Student and staff attitudes, and implications for university policy. [Conference presentation
 abstract]. Translation Technology in Education – Facilitator or Risk? University of Nottingham, UK.
 https://www.nottingham.ac.uk/conference/fac-arts/clas/translation -technology-ineducation%E2%80%93 
 facilitator-or-risk/videos/conference-videos.aspx
 Pellet, S. & Myers, L. (2022). What’s wrong with “What is your name?” > “Quel est votre nom?”: Teaching
 responsible use of MT through discursive competence and metalanguage awareness. L2 Journal, 14(1). Doi:
 10.5070/L214151739
 Pym, A. (2013). Translation skill-sets in a machine-translation age. Translators’ Journal, 58(3), 487–503. Doi:
 0.7202/1025047ar
 Reinders, H. (Host) (2022, September 7). A conversation with Jim Ranalli and Volker Hegelheimer [Audio
 Podcast Episode]. In Voices from LLT. https://www.lltjournal.org/media/voices-from-llt/
 Zhang, H., & Torres-Hostench, O. (2022). Training in machine translation post-editing for foreign language
 students. Language Learning & Technology, 26(1), 1–17. http://hdl.handle.net/10125/73466

How to use academic and digital fingerprints to catch and eliminate contract cheating during online multiple-choice examinations: a case study

Over four semesters of a large introductory statistics course the authors found students were engaging in contract cheating on Chegg.com during multiple choice examinations. In this paper we describe our methodology for identifying, addressing and eventually eliminating cheating. We successfully identified 23 out of 25 students using a combination of unique academic and digital fingerprints, and identified students who used virtual private networks (VPNs) to protect their online identity. There were two forms of cheating – posting questions and waiting for responses from tutors, and looking for questions that had already been solved. We found that 165 questions from these examinations were posted by 10 different students, but that the most common form of cheating was searching for answers that had already been posted. This paper discusses these patterns of Chegg usage, the consequences of not catching cheating early on, and how students reacted to being caught. Also provided are R and Python code that readers may use to identify cheating students in their own courses.

Ensuring integrity in online exams with AI anti-cheat system

The COVID-19 pandemic has compelled radical and innovative reforms and Education and academia have been identified as sectors most adversely affected by the pandemic. Disrupting the age-old classroom setup, the pandemic has forced educational institutions such as schools and universities to implement 'online classes.' However, the evaluation aspect of education remains to be desired. Many automatic online exam proctoring systems have been proposed for online examinations during this COVID-19 pandemic, but they have certain limitations, including fewer and inaccurate functionalities. In this paper, a smart exam monitoring system is presented that addresses many of the problems with past systems, aiming to help institutions prevent malpractices during exams. This smart exam monitoring system leverages advanced AI algorithms to monitor online exams in a more precise and comprehensive manner. It can detect various forms of cheating, such as screen sharing and unauthorized resource access, while also ensuring a fair evaluation process. By integrating cutting-edge technology into the education sector, the aim is to uphold the integrity of online examinations and adapt to the challenges posed by the ongoing COVID-19 pandemic.

A straightforward graphical/statistical approach to help substantiate cheating on multiple-choice examinations.

Academic dishonesty is prevalent in universities in the form of cheating on examinations, with the problem being much greater in classes that have a large number of students that require close seating arrangements for in-class exams. The scenario described below was experienced during an in-class exam that included the possibility of an Honor Code violation between two students that was observed independently by three different faculty proctors. Herein we detail an objective, statistical approach taken to maintain exam and academic integrity that is compelling and transparent to students and the University Honor Council. Using the established error-similarity analysis for multiple-choice exams, it was determined that the number of identical incorrect answers found on the exams of the two individuals in question was sufficiently greater than the number expected by chance (probability of P < 0.00001). The number of total identical incorrect answers found on the remaining exams (across 65 students, n = 89 comparisons) was plotted as function of the number of total incorrect answers found on these exams (incorrect answers ranged from 1 to 22) and clearly supported that there was an Honor Code violation between the two students in question. The techniques used herein established, beyond a reasonable doubt, that a form of cheating had occurred between these students. However, caution must be taken as further investigation is requisite to establish whether the Honor Code violation was unidirectional (one student copying off the other) or bidirectional (collusion between the two students) in nature.NEW & NOTEWORTHY Academic dishonesty is prevalent in universities, especially on examinations with a large number of students in close seating arrangements. Cheating on a multiple-choice exam was suspected by observations from proctors of the examination. Application of error-similarity analysis associated with identical incorrect answers demonstrated that the probability of cheating was confirmed (P < 0.00001) between two examinees. Further comparisons with the remaining exams provided graphic evidence that a violation of the University's Honor Code had occurred.

Integrity of nursing students in Israel: An exploratory study

AimResearch regarding the relationship between academic year and age and academic integrity is ambiguous; and at times confounded by a conflation of the terms “age” and “academic year.” This research aims to disentangle age from academic year and to assess the possible impact of those two factors on academic integrity. BackgroundThere is a growing concern regarding the lack of academic integrity among nursing students. The lack of academic integrity not only undermines the ability of academic institutions to accurately assess the professional training of nursing students, but also poses a danger to those who may ultimately depend on these nurses for treatment. DesignCross-sectional analysis of self-report measures of nursing students. MethodsIn the Fall of 2020, 143 nursing students at a faith-based academic institution in Israel completed an online, anonymous questionnaire addressing academic integrity and background demographics of respondents (i.e. age, academic year, sex). ResultsNo general trends regarding dishonesty and academic year or age emerged, though advanced students reported being less honest on work-based presentations. Also, differences emerged in self-acknowledged frequency of the different forms of cheating. Cheating on exams is the least frequent of all the forms of cheating, while enabling others to cheat was the most frequent type. ConclusionsWe hypothesized that academic dishonesty would decrease with both age and academic year. No such overall trend emerged when all cheating items are considered as an unweighted ‘cheating index.’ However, there were differences among different types of cheating. Cheating on exams is the least frequent of all the forms of cheating, while enabling others to cheat is engaged in most frequently and presumably perceived to be the most benign. Enabling others may be related to the communal nature of Israeli society and further amplified by the homogenous nature of the student body. Also, it is suggested that differences between cheating on familiar methods of evaluation (e.g. tests) and unfamiliar methods, which the students only experience as they advance in their degree (e.g. case studies) is a function of their gradual exposure to these novel methods. It is suggested that further research regarding this matter is warranted. Finally, the possible importance of the findings for those interested in advancing academic integrity are discussed, with a focus on how cultural matters and the novelty of forms of evaluation should be addressed to advance academic integrity among student as they advance in their studies.

From past lies to current misconduct: The long shadow of China's Great Leap Forward

Using hand-collected data on yield over-reporting during China's Great Leap Forward (GLF) period, we find that GLF over-reporting in a chairperson's province of origin strongly predicts corporate financial misconduct today. Evidence from a variety of identification strategies establishes a causal relationship. We also extend our analyses to other aspects of corporate misconduct and local dishonest behaviors. We show that GLF over-reporting has shifted social norms toward a present-day tolerance for dishonesty. Our findings suggest that wrongdoings by local government officials in the past can lead to adverse effects on people's future behavior in the form of cheating.

Ethical judgments of esports spectators regarding cheating in competition

Esports contests at the highest levels frequently involve millions of dollars in prize money and spectatorship numbers in six or seven figures. Given these opportunities for financial success and public visibility, players have found ways to cheat in esports competitions. We draw on over one thousand qualitative survey responses from esports viewers to examine how spectators perceive cheating, both “cheating to win” (attempting to secure an illegitimate victory) or “cheating to lose” (profit or advancement is secured by throwing a match). We show that spectators hold complex views ranking different forms of cheating, displaying varying levels of understanding of the esports ecosystem, and conceptualising cheating as often more a matter of rule breaking than ethical transgression. We conclude that esports viewers’ perspectives are heavily informed by their own play, and the opacity of certain elements of professionalised esports, with implications for the long-term sustainability of esports as a cultural form.

Automated Cheating Detection based on Video Surveillance in the Examination Classes

A major issue in the field of education is exam malpractice and other forms of academic dishonesty, where efforts made towards the assessment of students are undercut. In order to address this menace, a cheating detection system has been proposed in this study. The system can detect cheating in real-time. The proposed system uses video surveillance to monitor the activities of the student during exams, especially abnormal behavior. The development of the system involved the use of three different techniques, with different functions. The first technique helps in determining the direction of the students’ heads when they move from their initial direction, which is the exam script. Some form of cheating involves students peeping at the exam scripts of other people writing the same exam. Whenever the system observes a deviation that exceeds the set threshold, it classifies the behavior as abnormal. The second technique works with the movement of the student’s iris. It detects when a student’s iris moves in a different direction to copy answers from written documents like mobile phones, books, hands, summary papers. The third technique is used in identifying the contact between a student’s hands and face, as well as that between different students for shared abnormal behavior detection between students, such as sharing of incriminating materials. When any of these is detected, an automatic alarm alerts the authority about the abnormal behavior that has been detected, thereby minimizing the error rate that can occur as a result of manual monitoring.

PENGARUH PENGALAMAN KERJA, SKEPTISME PROFESIONAL, DAN TIPE KEPRIBADIAN TERHADAP KEMAMPUAN AUDITOR DALAM PENGUNGKAPAN KECURANGAN (FRAUD)

This study aims to examine and analyze work experience, professional skepticism and personality types on the auditor's ability to disclose fraud. The type of data used is quantitative data with primary data sources. The population in this study were auditors who worked at the Public Accounting Firm (PAF) in Central Jakarta and South Jakarta. The statistical tool used to test this hypothesis is multiple regression with IBM SPSS Statistics 25. The data were obtained by distributing questionnaires to respondents and the data were processed as many as 138 questionnaires. These results indicate that of the 3 hypotheses, all data are supported by data. Based on the hypothesis test, the results show that work experience and professional skepticism have a positive effect on the ability of auditors to disclose fraud because high work experience causes auditors to be faster in assessing the risk of fraud and with high skepticism the auditor will seek more evidence to prove that the financial statements are free from all forms of cheating. Meanwhile, personality type has a negative effect on the ability of auditors to disclose fraud because each executive auditor is required in his profession to carry out his duties professionally.

A wall that speaks: A critical discourse analysis of the Graffiti Writings of Generation Z

This critical discourse analysis aimed to elucidate the different ideologies of the graffiti- writings of the generation Z students of New Bataan National High School, Davao de Oro, Philippines. From the analyzed linguistic corpora, the results revealed that the graffiti writings of high school students convey impermissible, very sensitive, grubby and bigoted expression of thoughts and feelings as graffitist. Eight major functions of the graffiti-writings were identified: expressing personal feelings, expressing resentment, expressing general insult, expressing sexual ideas, expressing self-glorification, quoting cartoon expression, and even a form of cheating. There were five themes extracted from the gathered linguistic corpora, these are:, sexual derogation, self-glorification, profanity and cursing. The result of this study is deemed significant for those practitioners of linguistics, education and language pedagogy.

STUDENTS’ ACADEMIC DISHONESTY IN DOING THE TASKS DURING ONLINE LEARNING AT VOCATIONAL SCHOOL

This research is motivated by academic dishonesty committed by students in doing the tasks in e-learning while studying online at Pariaman Vocational High School. Participants in this study were students of class XI in Vocational High School using the purposive sampling method, totaling 58 students. The data were collected by researchers by observing student tasks documents in e-learning by grouping the types of academic dishonesty carried out by students. The researcher found 31 students who did academic dishonesty in doing the tasks during online learning. The results of this study indicate that academic fraud has the potential to occur in online learning in doing the tasks through e-learning in the form of cheating, plagiarism, deception, and fabrication.Keywords : Academic dishonesty, e-learning, online learning, tasks

Students’ Reasoning About Whether to Report When Others Cheat: Conflict, Confusion, and Consequences

Nearly all students believe academic cheating is wrong, yet few students say they would report witnessed acts of cheating. To explain this apparent tension, the present research examined college students’ reasoning about whether to report plagiarism or other forms of cheating. Study 1 examined students’ conflicts when deciding whether to report cheating. Most students gave reasons against reporting a peer (e.g., social and physical consequences, a lack of responsibility to report) as well as reasons in favor of reporting (e.g., concerns about welfare, justice, and fairness). Study 2 provided experimental confirmation that the contextual factors referenced by Study 1 participants in fact influenced decisions about whether to report cheating. Overall, the findings indicate that students often decide against reporting peers’ acts of cheating, though not due to a lack of concern about integrity. Rather, students may refrain from reporting because of conflicting concerns, lack of information about school policy, and perceived better alternatives to reporting.

Cheating in chess: a call for an integrated disciplinary regulation

This article examines recent regulation in the sport of chess with a focus on cheating. On the one hand, disciplinary law in chess could be considered relatively underdeveloped compared with other sports. On the other hand, however, this kind of ‘underdevelopment’ might be appropriate since chess governing bodies have not yet introduced interventionist rules. These two interacting perspectives shape the aim and the objectives of legal research designed to protect the chess community from cheating by suggesting adequate disciplinary measures. The analysis focuses mainly on two forms of cheating: computer-assisted cheating and match-fixing. The broad concept of cheating and relatively young legal regulation in an under-researched sport call for interdisciplinary analysis, therefore, knowledge of sports law, human rights as well as criminology is applied.

Cognitive enhancing drug use by students in the context of neoliberalism: cheating? Or, a legitimate expression of competitive entrepreneurialism?

A recurrent theme regarding drug policy and the use of cognitive enhancing drugs (CEDs) by students in higher education (HE), concerns the potential introduction of policy to prohibit the use of CEDs. One of the arguments put forward to support a prohibitive policy framework, is that the use of CEDs by students in HE is a form of academic misconduct; that the use of CEDs constitutes cheating. Now, given that it is widely documented that the use of CEDs by students in HE has been growing steadily over the past decade or more, there is surprisingly, a dearth of in-depth discussion on the topic of whether their use represents academic misconduct and is a form of cheating. Therefore, this commentary will summarise some examples of literature dedicated to the topic, before discussing whether the use of CEDs by students in HE constitutes cheating, when framed contextually, around neoliberalism and the key characteristics of competition and entrepreneurialism. The commentary will propose a potentially useful argument that, given the neoliberal context and those key characteristics, (HE) students could in theory, legitimise their use of CEDs. Consequently, students using CEDs for the purpose of hypothetically increasing academic excellence, would not consider their use of CEDs as a form of academic misconduct, of cheating. Thus, this paper, would in principle, support and endorse a legal, regulatory approach to CED policy and in addition, recommends that individual HE institutions do not prohibit the use of CEDs by students on the grounds of academic misconduct, but instead, advance harm reduction initiatives around their use.

VARANJE U AKADEMSKOM OKRUŽENJU - ULOGA MRAČNIH OSOBINA LIČNOSTI, STAVOVA O VARANJU I MORALNOG RASUĐIVANJA

Cilj ovog istraživanja bio je ispitati doprinos mračnih osobina ličnosti, moralnog rasuđivanja i stavova prema varanju čestini varanja u akademskom okruženju. U istraživanju su sudjelovali studenti tri fakulteta u Osijeku (N = 331). Korišteni su Test moralnog rasuđivanja, Kratka skala mračne trijade, Upitnik sadističkih tendencija, te modificirana Skala varanja u školi. Utvrđene su rodne razlike u iskazanoj čestini lakših oblika varanja, pri čemu su muškarci bili skloniji ovoj vrsti varanja. Značajnim prediktorima lakših oblika varanja pokazali su se psihopatija i pozitivni stavovi prema lakšim oblicima varanja, a značajnim prediktorima težih oblika varanja vrsta fakulteta, sadizam te stavovi prema težim oblicima varanja. Stavovi prema lakšim, odnosno težim oblicima varanja pokazali su se najsnažnijim prediktorima i lakših i težih oblika varanja u akademskom okruženju.

A Study on Academic Dishonesty and Moral Reasoning

Academic dishonesty in the form of cheating and plagiarism among university students has been a prevalent issue. This study investigates the role of moral reasoning as a moderator of fraud risk factors (Fraud Triangle - pressure, opportunity, and rationalization) on academic dishonesty. The data were collected through a survey of 178 undergraduate accounting students in one public university in Indonesia. The result of the partial least squares structural equation modeling analysis revealed that pressure, opportunity, and rationalization directly and positively affected academic dishonesty. The structural model was also examined across two groups based on the level of moral reasoning (Group 1: individuals with low moral reasoning; Group 2: individuals with high moral reasoning). The results showed that the pressure, opportunity, rationalization – academic dishonesty model remained invariant between the groups, a new finding contributed to the literature on academic dishonesty and the moderating effects of moral reasoning. The results of the study also suggest that university should uphold academic integrity by creating an environment where academic dishonesty is unacceptable and reduce the opportunity to commit dishonest acts because everybody might commit such acts regardless of their morality.