Academic Dishonesty Research Articles

Amend: an integrated platform of retracted papers and concerned papers

Abstract Purpose 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. Design/methodology/approach The Amend platform consolidates concerns and lists of problematic articles sourced from social media platforms (e.g., PubPeer, For Better Science), retraction notices from journal websites, and citation databases (e.g., Web of Science, CrossRef). Moreover, Amend includes investigation and punishment announcements released by administrative agencies (e.g., NSFC, MOE, MOST, CAS). Each related paper is marked and can be traced back to its information source via a provided link. Furthermore, the Amend database incorporates various attributes of retracted articles, including citation topics, funding details, open access status, and more. The reasons for retraction are identified and classified as either academic misconduct or honest errors, with detailed subcategories provided for further clarity. Findings Within the Amend platform, a total of 32,515 retracted papers indexed in SCI, SSCI, and ESCI between 1980 and 2023 were identified. Of these, 26,620 (81.87%) were associated with academic misconduct. The retraction rate stands at 6.64 per 10,000 articles. Notably, the retraction rate for non-gold open access articles significantly differs from that for gold open access articles, with this disparity progressively widening over the years. Furthermore, the reasons for retractions have shifted from traditional individual behaviors like falsification, fabrication, plagiarism, and duplication to more organized large-scale fraudulent practices, including Paper Mills, Fake Peer-review, and Artificial Intelligence Generated Content (AIGC). Research limitations The Amend platform may not fully capture all retracted and concerning papers, thereby impacting its comprehensiveness. Additionally, inaccuracies in retraction notices may lead to errors in tagged reasons. Practical implications Amend provides an integrated platform for stakeholders to enhance monitoring, analysis, and research on academic misconduct issues. Ultimately, the Amend database can contribute to upholding scientific integrity. Originality/value This study introduces a globally integrated platform for retracted and concerning papers, along with a preliminary analysis of the evolutionary trends in retracted papers.

Some Teaching Tips for Overcoming Challenges and conducting an Effective Online Assessment in Algerian Universities

In response to the corona virus COVID-19 pandemic, Algerian university rapidly moved from traditional to online assessment. Assessing EFL students in an online environment without preparation leads to several challenges for teachers and students. The lack or limited technical skills, slow and unreliable internet connectivity, teachers’ different levels in online language assessment literacy, differences in students’ levels in digital literacy, problems in grading and feedback, academic dishonesty and misconduct, are the main challenges. The objective of this research is to explore challenges hindering the process of online assessment at university, and providing suggestions and some teaching tips for the sake of overcoming these barriers and establishing effective online assessment. There is an urgent need to develop teachers’ online language assessment literacy. The attendance of specialized language assessment and testing conferences is beneficial for teachers. Developing students’ digital literacy is fundamental in enhancing online assessment. One of the basic roles attributed to the language teacher is raising students’ awareness of the unethical acts such as e cheating and plagiarism. Teachers need to receive in-service training focusing on online language assessment literacy. Online assessment in Algerian universities is still in its first steps, the above-mentioned challenges should be surmounted for the sake of putting remote assessment in its right path

Overcoming Online Assessment Challenges in Time of a New Normal: Case Study of Belhadj Bouchaib University

When the COVID-19 pandemic started, higher education, like all other industries, was affected. Institutions around the globe have experienced an almost sudden shift to online learning in an effort to slow the spread of the disease. Online learning was a panacea for continuing education during the pandemic, especially in higher education institutions. Conducting assessments online during this time of a new normal poses tremendous challenges for teachers and learners owing to lack of preparation superimposed with the inherent flaws of online assessment. The current study scrutinizes the challenges of online assessment during COVID-19 incident in the Algerian higher education institutions taking Belhadj Bouchaib University as a case study. Online questionnaires were prepared and administered to50participants. The study focused on the challenges of online assessment in general and academic misconduct in particular. The findings disclosed that the predominant challenges labelled in online assessment were academic misconduct, infrastructure, coverage of learning outcomes, and commitment of students to submit assignments. To attenuate academic misconduct, onlinepresentation was found to be the best approach. Preparing different questions to each student was also found to be a good alternative to control academic honesty breaches. Integrating different assessment methods; for example, report submission with online presentation, aids to reduce academic misconduct since the instructor would have an opportunity to confirm whether the submitted work is the student’s own work or not.

Motivational Perspectives on Student Cheating Behaviour: Toward an Integrated Model of Academic Dishonesty

Motivational Perspectives on Student Cheating Behaviour: Toward an Integrated Model of Academic Dishonesty

Minimizing Social Desirability in Questionnaires of Non-Cognitive Measurements

Data obtained through questionnaires sometimes respond to the items presented by social norms, so sometimes they do not suit themselves. High social desirability (SD) in non-cognitive measurements will cause item bias. Several ways are used to reduce item bias, including freeing respondents from not writing their names or being anonymous, explaining to the participants to respond to each statement honestly, as they are or according to themselves, and responding to the questionnaire online or offline. This research aims to prove that several methods can minimize the possibility of item bias SD and academic dishonesty (AD). The research was carried out with an experimental study using a factorial design. There were 309 respondents who were willing to be involved in this research. Data analysis was carried out using multivariate ANOVA. The research results show differences for all variables, Self-Deceptive Enhancement (SDE), Impression Management (IM), and AD in the anonymous group. There are differences in AD in the groups that provide a complete explanation and do not explain, and there is an interaction between the average AD based on the anonymous and explanation group.

Minimizing Social Desirability in Questionnaires of Non-Cognitive Measurements

Data obtained through questionnaires sometimes respond to the items presented by social norms, so sometimes they do not suit themselves. High social desirability (SD) in non-cognitive measurements will cause item bias. Several ways are used to reduce item bias, including freeing respondents from not writing their names or being anonymous, explaining to the participants to respond to each statement honestly, as they are or according to themselves, and responding to the questionnaire online or offline. This research aims to prove that several methods can minimize the possibility of item bias SD and academic dishonesty (AD). The research was carried out with an experimental study using a factorial design. There were 309 respondents who were willing to be involved in this research. Data analysis was carried out using multivariate ANOVA. The research results show differences for all variables, Self-Deceptive Enhancement (SDE), Impression Management (IM), and AD in the anonymous group. There are differences in AD in the groups that provide a complete explanation and do not explain, and there is an interaction between the average AD based on the anonymous and explanation group.

Instructor perceptions and reported practices around informal peer collaboration on homework among engineering students

ABSTRACT While team learning within engineering classrooms has been studied, minimal work has been done examining out-of-classroom collaboration to complete individual deliverables. However, such informal peer collaboration (IPC) is common among engineering undergraduates, and some evidence exists that low levels of IPC are associated with poorer learning outcomes. We aimed to explore beliefs, perceptions and actions toward IPC among engineering science instructors. We used a descriptive phenomenological approach to explore the instructors’ experiences of IPC. Data from semi-structured interviews was analysed using inductive thematic analysis. Instructors identified positive (e.g. gaining confidence) and negative (e.g. overconfidence) outcomes of IPC. They believed that students used IPC for a range of needs and identified factors (e.g. language spoken) influencing IPC groupings. Most instructors only defined academic misconduct in syllabi, despite using implicit strategies (e.g. withholding solutions) to promote/inhibit IPC. Specific IPC policies were rarely connected to instructors’ understanding of student motivations. Instructors view IPC as unavoidable and recognise that IPC may meet student needs while increasing or bypassing learning. Despite both using IPC as students and observing students now, instructors showed limited understanding of who participates. IPC may be an opportunity to increase learning among students; further research on barriers and pedagogy is warranted.

The drivers of academic cheating in online learning among Filipino undergraduate students

ABSTRACT The susceptibility of online learning to cheating behavior remains a contentious and unresolved issue. A cross-sectional explanatory research design was utilized to test the hypothesized factors influencing academic cheating in online learning. Our study involved 562 participants, selected through a non-probability sampling technique, who were surveyed using online questionnaires designed to measure the identified factors. We tested the hypotheses by utilizing path analysis through the partial least square regression approach within the SMART-PLS software. The demographics such as gender and age of the students, along with the roles of teachers and school administration significantly influenced the students’ instances of self-reported academic cheating. The students’ attitude toward academic cheating emerged as an important factor in predicting cheating behaviors. The paper concludes with recommendations for future research explorations into other potential factors that may contribute to academic dishonesty in online learning.

ChatGPT and the Crisis of Academic Honesty

ChatGPT is one of the conversational AI tools that changed and still change the human life in different aspects wherein the academic and the scientific aspects seem to be affected more seriously. This paper, therefore, is an attempt to delve into some minutes of this influence in these two sensitive aspects. And this can be achieved through pinpoint its aggressions that are mainly caused by its capacities and limitations as far as scientific communication and studies are concerned. On its surface face, this AL seems to enrich scientific texts with clarity and coherence, to have a role in generation of new ideas and research methods, along with the dangers it creates to the honesty of academic efforts. The study, therefore, seems grim and pessimistic in this respect contrary to the immense praise and acceptance it receives at the universal level. It tries to call for a stricter human censorship over academic and scientific works to draw them away, as much as possible, from the injuries of this AI application. And to support this caution, it shows some of ChatGPT features and restrictions that turn it dangerous in the academic fields. And to be objective and accurate, the study refers to some of its positive aspects like its ability to help in creating coherence and clarity to scientific articles, research methods, and use in fighting plagiarism. As thus, the study highlights an urgent need for a necessary methods, restrictions, and strategies that can ensure a safe use of ChatGPT's advantages and avoiding its weaknesses whenever it is used in scientific writing.

Religiusitas sebagai Homologizer Moderasi dalam Hubungan antara Dimensi Fraud Diamond dan Kecurangan Akademik pada Perkuliahan Daring (Studi Kasus Mahasiswa Akuntansi)

Acts of dishonesty are often committed by students, especially in online lectures, in order to get a high grade point average (IP). The achievement index is an indicator of success during education and to provide wider job opportunities. Education is all learning experiences that take place and affect the joints of life and affect one's behaviour in life. Accounting students are future accountants, accountants must comply with the accountant's code of ethics and avoid cheating. Academic fraud committed by accounting students is a behaviour that, if often carried out, has an impact on cheating to commit dishonesty in the world of work. The study aims to analyse the direct and indirect effects of the dimensions of the fraud diamond consisting of opportunity, opportunity, rationalisation and ability on academic fraud where religiosity as a moderating variable on the indirect relationship between the dimensions of the fraud diamond and academic fraud. The research population was accounting students in the class of 2019 and 2020 and still active in 2023, totalling 317 at a State University in Jambi City. Sample selection using proposive sampling and obtained a sample of 287. Data analysis using PLS. The results found that the dimensions of the fraud diamond: directly affect academic fraud in online lectures, and indirectly religiosity is not able to provide a strong influence on the relationship between the dimensions of the fraud diamond and academic fraud in online lectures. The research novelty is religiosity as a moderating homologizer, seen from religiosity does not interact or is unable to influence the relationship between the dimensions of the fraud diamond variable and the academic fraud variable in online lectures.

Understanding academic dishonesty during the thesis-writing process: A case study of students majoring in tourism and hospitality

Academic dishonesty is a pervasive problem in Chinese higher education, with both motivational and contextual factors influencing students’ behavior. This study integrates self-determination theory (SDT) and the motivation-opportunity-ability (MOA) model to investigate why students engage in academic dishonesty during thesis writing and their decision-making processes. SDT emphasizes intrinsic motivation and the satisfaction of basic psychological needs, including competence, autonomy, and relatedness. The MOA model posits that behaviors result from the interaction of motivation, ability, and opportunity. Through qualitative interviews with students majoring in tourism and hospitality, this research demonstrates that students with lower levels of self-determination (i.e., lack of autonomy, lack of competence, and lack of relatedness) show a limited willingness to complete thesis tasks in a moral manner. Moderated by ability frustration and opportunity frustration, the motivation to be dishonest leads to actual immoral behavior. This study sheds light on the complex factors driving academic dishonesty and offers insights for addressing this issue in higher education.

Secondary School Students’ Intention to Cheat and Willingness to Report Academic Cheating Incidents: Evidence from Eastern Ethiopia

The growing recognition of academic dishonesty as a major cross-cultural problem urges educators and researchers to examine various aspects of the issue. This qualitative case study examined secondary school students’ intention to cheat and willingness to report observed academic cheating incidents. The participants comprised 20 students randomly selected from public and private secondary schools. Data were collected using semi-structured interviews. We found that the participants had strong intentions to engage in academic cheating activities. They indicated that their desire to cheat was caused by observing their classmates’ cheating activities. Moreover, most of the participants were tolerant of academic misconduct. They preferred not to report observed academic cheating incidents. It is recommended that schools must work on students’ minds in such a way that it helps them to value academic integrity and honesty.

Academic Fraud and Remote Evaluation of Accounting Students: An Application of the Fraud Triangle

AbstractThe pandemic has altered accounting education with the widespread adoption of remote evaluation platforms. We apply the lens of the fraud triangle to consider how the adoption of remote evaluation influences accounting students’ ethical values by measuring the incidence of cheating behavior as well as capturing their perceptions of their opportunity to cheat and their rationalization of cheating behavior. Consistent with prior research, our results show that cheating is higher in the online environment compared to remote evaluation, although the use of proctoring software in online evaluation appears to mitigate but not eliminate students’ the unethical behavior. However, cheating was not reduced when students attest to an honor code during the beginning of an exam. Nonetheless, we find that the use of both proctoring software and honor codes reduces students’ perceptions of opportunity and rationalization of cheating behavior. It follows that the remote evaluation environment may unintentionally be negatively influencing the ethicality of students and future accounting professionals by promoting cheating behavior and, by so doing, negatively influencing the development of unethical values of accounting students and future accounting professionals. Educators should consider the use of appropriate educational interventions to reduce the incidence and opportunities for unethical behavior and, by so doing, help promote the development of ethical values in future accounting professionals. Further implications for teaching and the accounting profession are discussed.

Interplay of rationality and morality in using ChatGPT for academic misconduct

ABSTRACT ChatGPT’s capability to generate original content on any topic represents a concern for academic institutions, since students can plagiarise the AI-created content with a low probability of being caught. While prior research on academic misconduct emphasized the combined effects of perceived costs and benefits in explaining students’ decisions to cheat, the low detectability of ChatGPT-based plagiarism significantly reduces the cost of being caught, making rational choice theory less powerful in explaining academic misconduct in the AI era. Considering the effects of both rational decision-making and moral considerations, this study shows that individuals experiencing moral disengagement are more likely to engage in ChatGPT-based plagiarism. Other significant predictors include perceived benefits, punishment severity, and informal sanctions. Furthermore, moral disengagement enhances the effects of formal sanctions on ChatGPT-based plagiarism. The results have implications for professors, academic administrators, and plagiarism detection software designers to enforce academic integrity in the ChatGPT era.

A Comparative Study of the Accuracy of Turn-It-In’s Artificial Intelligence Detector in CTU Doctoral Assignments

As access to artificial intelligence becomes mainstream in college paper writing, universities must find concrete methods of verifying work submitted as a student’s original content was not significantly developed using AI. In response to these potential academic integrity issues, plagiarism detectors, like TurnItIn, have developed artificial intelligence detectors that provide the percentage of a student submission identified as written by a computer. TurnItIn (TII) claims a 98% confidence level concerning its accuracy. In this study, 48 papers were randomly selected from the Colorado Technical University’s Doctoral Studies courses. These papers were written before the public release of ChatGPT 3.5. Papers were scored for similarity and AI-generated content through TII. These same papers were then edited for grammar and clarity using ChatGPT, and the similarity and AI-generated content scores were recalculated through TII. Wilcoxon Ranked-Sum tests were conducted to determine if a statistical difference occurred between the original and updated similarity and AI-generated content scores. The results demonstrate that TII’s confidence level may not be as accurate as claimed and that the detection of AI-generated content requires further testing before being used to determine if an act of academic dishonesty took place.

Exploring Educational Frontiers: Innovating with Chat-GPT while Upholding Traditional Values

This study investigates the impact of Chat-GPT on education, with a focus on personalized tutoring and academic support. While Chat-GPT offers numerous benefits, there is a risk of misuse for academic dishonesty. Therefore, this research aims to explore how educators can use Chat-GPT to promote academic integrity and encourage critical thinking. To accomplish this, the study utilizes both quantitative and qualitative approaches, beginning with a literature review. Interviews with instructors, students, and industry professionals provide different perspectives and reveal practical challenges. Additionally, performance indicators are used to compare Chat-GPT with traditional teaching methods. Initial tests demonstrate potential, but ongoing development requires educators to balance the advantages and risks, address concerns about academic honesty, and foster critical thinking skills in students.

Theory of Planned Behavior as an Antecedent in Predicting Fraudulent Intentions of Academic Accountants and Non-Academic Accountants

Purpose: Individual behavior is a representation of what is believed. Likewise, an accountant intends to commit financial statement fraud. Related to predicting individual behavior to do or not to do something action can use the Theory of planned behavior (TPB). This research examines three main variables in TPB, attitude, subjective norms, and perceived behavioural control on academic and non-academic accountants' fraud intentions through the Theory of Planned Behavior (TPB) variables.Method: This research is quantitative, with primary data obtained from questionnaires sourced from respondents. Respondents were academic and non-academic accountants. The research sample was selected using a purposive sampling method with specific criteria. The partial least squares (PLS) method was used to analyze the data.Findings: The findings suggest that attitudes and subjective norms significantly positively affect the intention to commit financial statements fraud in academic and non-academic accountants, while perceived behavioural control does not significantly affect the intention to commit fraud in financial reporting.Originality/Value : Research that examines the intentions of academic accountants and non-academic accountants in committing financial statement fraud and studied using the theory of planned behavior is the first to be conducted.

EXAMINING EXEMPLAR ELEMENTS OF SELECTED MALAYSIAN HIGHER EDUCATION INSTITUTIONS’ ACADEMIC INTEGRITY POLICY: DOCUMENT ANALYSIS BASED EVIDENCE

Background and Purpose: This study examined the comprehensiveness and sufficiency of academic integrity (AI) policies of selected Malaysian higher education institutions. The investigation of eight public and private universities’ AI policies were guided by the five core elements of exemplar AI policy framework developed by Bretag, Mahmud, Wallace, Walker, James, Green, East, McGowan and Partridge (2011).
 
 Methodology: This qualitative method research focused on document analysis of purposively selected eight AI policies. The five core elements that guided the document analysis are access, approach, responsibility, detail and support. The data collected from document analysis was analysed via NVivo 11 software.
 
 Findings: Public universities are educative based and private universities practice punitive approach. All universities provide access of the AI documents to the university community and public, implement ad hoc basis education, awareness campaigns and modules to support the AI agenda and encourage responsibility among the staff and students to curb academic dishonesty. As for detail, universities differ in terms of amount and type of information provided in the documents.
 
 Contributions: The findings will provide universities evidence to make their existing AI policies more robust and comprehensive.
 
 Keywords: Academic integrity policy, core elements of exemplar, document analysis, Malaysian higher education institutions.
 
 Cite as: Manjet, K., & Phan, J. K. J. (2024). Examining exemplar elements of selected Malaysian higher education institutions’ academic integrity policy: Document analysis based evidence. Journal of Nusantara Studies, 9(1), 269-293. http://dx.doi.org/10.24200/jonus.vol9iss1pp269-293

An investigation into the online language teaching and assessment practices during COVID-19

Due to a growing number of casualties, company and school closures, and a lack of social connections, the COVID-19 pandemic has resulted in a number of unanticipated challenges. As a result, to cope with these challenges online education served as a great way for bridging the distances through digital tools. With the purpose of an effective and quality online learning, all stakeholders involving active implementers of educational programs, namely teachers and students in addition to administrators should be aware of its benefits and drawbacks. To this end, the current study attempts to uncover the perspectives of ELT instructors about online language teaching and assessment through a qualitative research design. The results showed that online language assessment and teaching was considered as inevitable by all participants, thus making it necessary to employ efficient methods for designing and administering online assessment, and interpreting the scores. On the contrary, a long list of challenges and problems were noted by the respondents including academic misconduct, difficulty of proctoring, open to manipulation, validity and reliability concerns. The study ends with practical implications for teacher training programs and further research ideas.

CHEAT DETECTION IN ONLINE EXAMINATIONS USING ARTIFICIAL INTELLIGENCE

With increasing use of ICT and technical advancements in the education sector, distant and online education as well as examinations are being carried out frequently. However, online examination, as a method of assessment offers the risk of an unmonitored setting where students have full access to external resources. Online-proctored exams are the most efficient way for educational institutions to ensure academic honesty and ethics to counteract this. Typically, proctoring requires human assistance in the form of online proctors who remotely monitor students' performance. Yet, due to the rising demand for personnel and the intrusive nature of human proctoring, it is imperative to explore other areas. To tackle this pressing issue, this research work aims to devise a novel architecture that, through the development of a robust and automated Artificial Intelligence system, enables students to take exams remotely and reduces proctor involvement. The method overcomes the shortcomings of the previous automated proctoring system by combining important components of online exam cheating detection with cost-effective and efficient hardware. By proposing a Hybrid of FaceNet Model, Lucas Kanade Algorithm, and Active Appearance Model for Face Detection and Activity Monitoring of the student, the proposed system extracts semantic indicators to evaluate whether an applicant is cheating in an online examination. The proposed Cheat Detection system's experimental results measured via an F-score of 0.94 demonstrate its efficacy, and promising performance compared to the standard baseline techniques.