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Abstract Students are increasingly relying on contract cheating (CC), a phenomenon in which a third party completes the assignment, quiz, or homework for students in exchange for a fee. Using an exploratory qualitative method and underpinned by critical theory and social responsibility theory, this study explored the perceptions of faculty members regarding CC in the United Arab Emirates’ (UAE’s) higher education institutions. In particular, this study addressed how faculty members perceive and deal with CC in contexts where policies towards the practice are absent from higher institution honour codes. Using thematic analysis, the results showed that CC arouses the indignation of faculty and staff to the violation of individual and religious rights. Also, they believe they have a sense of responsibility towards students and the community. The results also showed that faculty members’ hesitation in reporting CC incidents was due to their perceived lack of support from higher administration institutions and the lack of clear procedures in ethical manuals. This paper concludes with practical recommendations for faculty and staff, managers, department heads and decision makers to mitigate this phenomenon proactively.

The notable increase in retraction papers has attracted considerable attention from diverse stakeholders. Various sources are now offering information related to research integrity, including concerns voiced on social media, disclosed lists of paper mills, and retraction notices accessible through journal websites. However, despite the availability of such resources, there remains a lack of a unified platform to consolidate this information, thereby hindering efficient searching and cross-referencing. Thus, it is imperative to develop a comprehensive platform for retracted papers and related concerns. This article aims to introduce “Amend,” a platform designed to integrate information on research integrity from diverse sources.

Research integrity is now one of the most important issues in the governance of science and technology (S&T) ethics in China. Many research results have been produced in the academic circle on this topic. A series of regulations and normative documents has been issued by government authorities, and numerous measures have been taken by universities and scientific research institutions. Despite this notable progress, the problems of research integrity have not been eradicated. Incidents such as rejections of papers by journals due to plagiarism and falsification of research results happen from time to time. Also, the awareness of research integrity among some S&T personnel and students has yet to be strengthened. The new challenge for research integrity in the new era is that of being able to locate the deep-seated causes of research-integrity problems and find effective ways to solve them. Exploring the causes of and countermeasures against those problems from the perspective of the culture of science is a research field that deserves greater attention. [ABSTRACT FROM AUTHOR]

Students are increasingly relying on contract cheating (CC), a phenomenon in which a third party completes the assignment, quiz, or homework for students in exchange for a fee. Using an exploratory qualitative method and underpinned by critical theory and social responsibility theory, this study explored the perceptions of faculty members regarding CC in the United Arab Emirates' (UAE's) higher education institutions. In particular, this study addressed how faculty members perceive and deal with CC in contexts where policies towards the practice are absent from higher institution honour codes. Using thematic analysis, the results showed that CC arouses the indignation of faculty and staff to the violation of individual and religious rights. Also, they believe they have a sense of responsibility towards students and the community. The results also showed that faculty members' hesitation in reporting CC incidents was due to their perceived lack of support from higher administration institutions and the lack of clear procedures in ethical manuals. This paper concludes with practical recommendations for faculty and staff, managers, department heads and decision makers to mitigate this phenomenon proactively. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Theory & Practice in Education (JTPE) / Eğitimde Kuram ve Uygulama is the property of Journal of Theory & Practice in Education and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As elsewhere in the world, academic misconduct is a serious problem in Aotearoa. Yet, beyond the occasional newspaper headline, we know relatively little about the extent of the problem here or the factors associated with it. Consequently, our educational leaders and practitioners are left under-informed as they seek to address the problem and promote academic integrity. To help provide the knowledge and insights needed to craft good policy and best practice, the Research on Academic Integrity in New Zealand (RAINZ) Project—a research collaboration involving eight tertiary institutions—was founded in 2021. In the second semester of 2022, the RAINZ Project launched the first-ever nationwide survey of undergraduate students' perceptions, attitudes, and behaviours related to academic integrity. Results from this survey, which was completed by undergraduates (N = 4493), indicate that most students (approximately two-thirds) reported engaging in at least one form of academic misconduct in the past year. As hypothesised, students' perceptions (of the institutional climate and peer norms) and moral attitudes (related to cheating) were significantly associated with their engagement in academic misconduct. Details of these results as well as their implications for policy and practice are discussed. [ABSTRACT FROM AUTHOR]

Long characterized as a primary form of academic misconduct and a major threat to academic integrity, the issue of plagiarism has been extensively researched from multiple perspectives, including students' and academic staff's perceptions and attitudes concerning plagiarism, measures for detecting and deterring plagiarism and their effectiveness, and the higher education sector's response to plagiarism. Yet knowledge remains patchy regarding this last strand of research. With the aim of bridging this research gap, we examine and compare the plagiarism management policies adopted by a selection of universities in mainland China and Hong Kong, two contexts that have been influenced by different academic traditions. Analysis reveals both similarities and divergences in these universities' communication of plagiarism-related information, mechanism for plagiarism detection, provision of academic guidance and support for avoiding plagiarism, and competing discourses on plagiarism underpinning their mixed approaches to the problem. Implications for institutional policymaking and academic integrity education are discussed. [ABSTRACT FROM AUTHOR]

Academic integrity refers to the concept of ensuring moral standards and ethics in academia. The commitment and demonstration of moral values like honesty, trust and fair dealing in academic settings and contexts are the fundamentals of academic integrity. The International Center of Academic Integrity (ICAI) sets out five values to define academic integrity including honesty, trust, fairness, respect, responsibility, and courage. This is a fact that higher levels of academic integrity consequently lead towards better academic standards and refinement of academic quality at higher education institutions (HEIs). The paper entails a qualitative approach and is based upon the past pertinent studies as well as the personal experiences of the authors in academia to discuss and evaluate the academic integrity in the context of Pakistani HEIs. The actions and practices which violate academic integrity constitute academic misconduct and adamic dishonesty. The malpractices may be done at the end of students, faculty or institutional authorities and HEIs administration. This paper discusses the problems and issues which undermine the academic integrity in HEIs encompassing the major issues including plagiarism, cheating in exams, contract cheating, collusion, facilitation and deceit among others. The paper also proposes the ways to address the issues of academic misconduct by suggesting measures and recommendations to curb the aspects of academic dishonesty by the students, faculty members and HEIs administrative staff. [ABSTRACT FROM AUTHOR]

In recent years, cheating in exams has been reported to be a serious issue in many countries. Some believe the problem to be more severe, due to the development of modern technologies. But academic dishonesty is not a new phenomenon. This article is going to look into the cheating methods used in the world’s first examination system in Imperial China and the means devised to prevent these malpractices. These are compared with examples of exam cheating observed in contemporary societies and the measures that institutions take to safeguard test and certificate validity. Cheating practices in Imperial exams are described on the basis of the available literature and the preserved artefacts. The state of the problem of cheating by contemporary students has been assembled, based on research articles. Despite all the changes that have occurred in educational systems over the years, cheating methods have not in essence changed significantly.

Recent advancements in chatbots have provided students and academics with a new mode of how knowledge can be sourced and composed. Within a very short space of time, students and academics have flocked to use ChatGPT and other Generative Artificial Intelligence (GAI) platforms owing to their capable responses. Additionally, apart from the generative chatbots (such as ChatGPT and Gemini), AI writing tools for paraphrasing, summarising, and co-writing have also become capable and increasingly prevalent to such a degree that the public is spoilt for choice. Having conducted tests on popular chatbots and AI writing tools, it became clear that while programs like Turnitin are developing new algorithms to detect plagiarism and AI-generated content, the initial findings from this study suggest that this may be an increasingly difficult task. These tests were published on YouTube, and within a few weeks, the evidence garnered tens of thousands of views as students and educators seemed uncertain about the strengths, weaknesses, and legalities of these AI tools. What is clear is that we have passed the tipping point, and AI assistance is no longer just a grammar fixer. The implications of this are concerning and far-reaching, as plagiarism is already a significant problem in universities. This position paper reports on tests conducted using Turnitin software and AI writing tools such as ChatGPT and QuillBot. These real-world tests support the paper’s position that it is becoming increasingly difficult to determine what constitutes original work in a world of GAI. The aim of this article is to provide evidence that educators who rely on similarity checking and AI detectors in their current form may inadvertently be supporting plagiarism rather than reducing it. A new method of academic plagiarism detection is proposed, utilizing large language models to generate and track ideas, thereby serving as an idea database. The proposed method focuses on the "understanding" of the work rather than on text similarity.

Abstract Background Despite global interest in the interface of Algorithmically-driven writing tools (ADWTs) and academic integrity, empirical data considering educators' perspectives on the challenges, benefits, and policies of ADWTs use remain scarce. Aim This study responds to calls for empirical investigation concerning the affordances and encumbrances of ADWTs, and their implications for academic integrity. Methods Using a cross-sectional survey research design, we recruited through snowball sampling 100 graduate students and faculty members representing ten disciplines. Participants completed an online survey on perceptions, practices, and policies in the utilization of ADWTs in education. The Technology Acceptance Model (TAM) helped us understand the factors influencing the acceptance and use of ADWTs. Results The study found that teacher respondents highly value the diverse ways ADWTs can support their educational goals (perceived usefulness). However, they must overcome their barrier threshold such as limited access to these tools (perception of external control), a perceived lack of knowledge on their use (computer self-efficacy), and concerns about ADWTs' impact on academic integrity, creativity, and more (output quality). Conclusion AI technologies are making headway in more educational institutions because of their proven and potential benefits for teaching, learning, assessment, and research. However, AI in education, particularly ADWTs, demands critical awareness of ethical protocols and entails collaboration and empowerment of all stakeholders by introducing innovations that showcase human intelligence over AI or partnership with AI.

Background Plagiarism remains poorly understood among post-graduate dental students (PGDSs) in North Africa. Data on the level of understanding of plagiarism (UP) in this population is lacking. This study assessed UP of Tunisian PGDSs'. Methods A cross-sectional pilot study was conducted at the Faculty of Dental Medicine of Monastir, involving 147 PGDSs registered in 2022. Students were recruited via email invitations and convenience sampling at a medical congress. A French survey with 11 questions on UP, offering three-choice answers (yes/no/maybe) was administered. Each correct answer received one point, and a total UP score below six indicated a low-level of UP. Results The mean±SD UP score of the 106 students who accepted to participate in the study was 4.7±2.2, indicating a low-level of UP. The majority of PGDSs (81.13%) demonstrated a low-level of UP. A comparison between subjective and objective assessments of UP revealed that a significant percentage of PGDSs underestimated their understanding (81.13% vs. 62.26%, respectively). The two groups of PGDSs with low (n=86) and acceptable/excellent (n=20) UP showed comparable characteristics in terms of age, sex, discipline, post-graduate-level, experience-level, graduation-status, and survey-response modality. Conclusion This study highlights a lack of awareness of UP among North African PGDSs, emphasizing the need for further efforts to enhance awareness and promote better UP in this population.

This quantitative study is designed to determine the impact of online proctoring software in graduate courses. The researchers compared the final grades of two groups of online graduate students who were taught by professors who had online exams before and after the university implemented proctoring software. Essentially the only difference between the groups was the use and nonuse of proctoring software. The overall sample in this study were 426 students in six different online graduate nursing courses at a medium-sized, public university in the United States. The findings showed the implementation of online proctoring software had a statistically significant impact on the students’ course grade when all the graduate courses were regressed together. The authors also regressed the data using independent human capital variables (i.e. male/female, full/part-time status, and cumulative GPA). Student cumulative GPA also proved statistically significant for the group of graduate nursing courses. [ABSTRACT FROM AUTHOR]

The global surge in academic misconduct during the COVID-19 pandemic, exacerbated by remote teaching and online assessment, necessitates a comprehensive understanding of the multidimensional aspects and stakeholders' perspectives associated with this issue. This paper addresses the prevalent use of answer-providing sites and other types of academic misconduct, underscoring the challenge of detecting all or most of the student misconduct. Exploring factors such as faculty inexperience in remote teaching and assessment, the paper advocates for proactive measures to preserve integrity in education. Emphasizing the need for a culture of integrity beyond traditional classrooms, the paper reviews existing models, then details steps to create a framework using the International Labour Organization (ILO)'s TREE training method. It presents the IEPAR framework (Inspiration, Education, Pedagogical considerations, Assessment design, Response and Restorative practice), and assesses its effectiveness. Incorporating faculty feedback, the paper concludes with evidence-based findings, positioning the IEPAR framework as a robust approach for addressing academic misconduct and fostering a culture of academic integrity in higher education through responsible training of all stakeholders. [ABSTRACT FROM AUTHOR]

The past decade has seen extensive research carried out on the systematic causes of research misconduct. Simultaneously, less attention has been paid to the variation in academic misconduct between research fields, as most empirical studies focus on one particular discipline. We propose that academic discipline is one of several systematic factors that might contribute to academic misbehavior. Drawing on a neo-institutional approach, we argue that in the developing countries, the norm of textual originality has not drawn equal support across different research fields depending on its level of internationalization. Using plagiarism detection software, we analyzed 2,405 doctoral dissertations randomly selected from all dissertations defended in Russia between 2007 and 2015. We measured the globalization of each academic discipline by calculating the share of publications indexed in the global citation database in relation to overall output. Our results showed that, with an average share of detected borrowings of over 19%, the incidence of plagiarism in Russia is remarkably higher than in Western countries. Overall, disciplines closely follow the pattern of higher globalization associated with a lower percentage of borrowed text. We also found that plagiarism is less prevalent at research-oriented institutions supporting global ethical standards. Our findings suggest that it might be misleading to measure the prevalence of academic misconduct in developing countries without paying attention to variations at the disciplinary level. [ABSTRACT FROM AUTHOR]

Academic misconduct is unethical behavior in academic work. To sustain integrity culture and mitigating unethical conducts among higher education institutions community, the academic misconduct detection must be done at an earlier stage. Thus, this study attempted to provide a new empirical contribution with the analysis of binary classification performances metrics to describe the ability of machine learning in predicting academic misconduct. Four machine learning algorithms have been used namely generalized linear model (GLM), logistic regression (LR), decision tree (DT), and random forest (RF). Beside performances comparison, this paper presents the analysis of academic misconduct factors that were constructed based on demography and fraud triangle theory (FTT). The findings showed that all the four machine learning algorithms have obtained good ability in the prediction models with the accuracy at above 80% and below 20% of the classification errors. Rationalization from the FTT attributes has shown as the most important factor in GLM, LR, and DT. In RF, opportunity of FTT attributes have become the most important. Compared to FTT attributes, demography attributes were not providing much benefits to all the machine learning models but remain applicable at very low weight correlations. [ABSTRACT FROM AUTHOR]

In this paper, the authors review extant natural language processing models in the context of undergraduate mechanical engineering education. These models have advanced to a stage where it has become increasingly more difficult to discern computer vs. human-produced material, and as a result, have understandably raised questions about their impact on academic integrity. As part of our review, we perform two sets of tests with OpenAI's natural language processing model (1) using GPT-3 to generate text for a mechanical engineering laboratory report and (2) using Codex to generate code for an automation and control systems laboratory. Our results show that natural language processing is a potentially powerful assistive technology for engineering students. However, it is a technology that must be used with care, given its potential to enable cheating and plagiarism behaviours given how the technology challenges traditional assessment practices and traditional notions of authorship. [ABSTRACT FROM AUTHOR]

The article discusses the prevalence of academic cheating in universities, particularly during the COVID-19 pandemic. It highlights how online learning and assessment methods have made cheating easier and more common. The authors propose a "moral developmental" approach to studying cheating, focusing on perceptions of cheating, evaluations of cheating acts, and action selection based on moral judgments. They argue that the gap between moral judgment and action is narrower than previously assumed, primarily due to the exclusion of non-cognitive factors in the relationship between judgment and action. However, they acknowledge that concepts such as moral self and moral identity remain relevant in understanding the connection between moral judgment and action. [Extracted from the article]

Copyright of Synesis is the property of Synesis and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract It is well known that students intentionally and unintentionally commit academic misconduct, but how can universities prevent academic misconduct and foster a culture of academic integrity? Based on a literature synthesis, an actionable Model for Preventing Academic Misconduct is presented. The model’s basic premise is that students’ voluntary participation in individual courses or academic integrity modules will have far less impact on preventing academic misconduct than required faculty or university-wide programming in core courses. In validating the model, the steps taken by the School of Business at a Canadian university to prevent academic misconduct are examined. Two online tutorials were created and implemented as required modules in the School of Business introductory core courses. Actual academic misconduct incidents recorded by the University from 2016 to 2021, a three-year pre-intervention period and a two-year post-intervention period partly covering the COVID-19 outbreak, are used to gauge the model’s effectiveness in preventing academic misconduct. The findings are discussed through a Social Learning Theory lens: the high-level implementation gives rise to a culture of academic integrity propelled by the establishment of common knowledge.

Abstract In this article I explore the concept of postplagiarism, loosely defined as an era in human society and culture in which advanced technologies such as artificial intelligence and neurotechnology, including brain-computer interfaces (BCIs), become a normal part of life, including how we teach, learn, communicate, and interact on a daily basis. Ethics and integrity are intensely important in the postplagiarism era when technology cannot be decoupled from everyday life. I argue that it might be reasonable to assume that when commercialized neuro-educational technology is readily available in a form that is implantable/ingestible/embeddable and invisible then academic integrity arms race will be over, as detection will be an exercise in futility. In a postplagiarism era, humans are compelled to grapple with questions about ethics and integrity for a socially just world at a time when advanced technology cannot be unbundled from education or everyday life. I conclude with a call to action for transdisciplinary research to better understand ethical implications of advanced technologies in education, emphasizing that such research can be considered pre-emptive, rather than speculative. The ethical implications of ubiquitous artificial intelligence and neurotechnology (e.g., BCIs) in education are important at a global scale as we prepare today’s students for academic and lifelong success.

Abstract This paper connects the problem of artificial intelligence (AI)-facilitated academic misconduct with crime-prevention based recommendations about the prevention of academic misconduct in more traditional forms. Given that academic misconduct is not a new phenomenon, there are lessons to learn from established information relating to misconduct perpetration and frameworks for prevention. The relevance of existing crime prevention frameworks for addressing AI-facilitated academic misconduct are discussed and the paper concludes by outlining some ideas for future research relating to preventing AI-facilitated misconduct and monitoring student attitudes and behaviours with respect to this type of behaviour.

Academic misconduct is ubiquitous, a fortiori during crisis periods. The present research examines undergraduates’ learning motivation, based on Self-Determination Theory and personality traits factors, according to the Big Five Factor Model, affecting academic misconduct across different time spans: Before, during, and after a life-changing event. Using online questionnaires, we measured the level of academic misconduct, learning motivation, and personality traits of 1090 social sciences students during five different time spans pre-COVID-19, during COVID-19 (before and after vaccination), and after COVID-19 (post and long post). The results showed significant differences in students’ self-reported academic misconduct levels among the different periods and similar misconduct levels in pre-COVID-19 and long post-COVID-19. Additionally, the findings exhibited that external motivation significantly increases academic misconduct and that two out of five personality traits (agreeableness and emotional stability) reduce their occurrences. We conclude that higher education preparedness for academic integrity during an emergency is still a desideratum and that ethical concerns should not be abandoned but rather be fully addressed during emergency periods. This could be addressed by instructors allocating tasks during emergency groups involving students with pro-social personalities (agreeableness and emotional stability) and intrinsic motivation to serve as social agents in deterring academic misconduct.