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Many philosophers have argued that large language models (LLMs) subvert the traditional undergraduate philosophy paper. For the enthusiastic, LLMs merely subvert the traditional idea that students ought to write philosophy papers "entirely on their own." For the more pessimistic, LLMs merely facilitate plagiarism. We believe that these controversies neglect a more basic crisis. We argue that, because one can, with minimal philosophical effort, use LLMs to produce outputs that at least "look like" good papers, many students will complete paper assignments in a way that fails to develop their philosophical abilities. We argue that this problem exists even if students can produce better papers with AI and even if instructors can detect AI-generated content with decent reliability. But LLMs also create a pedagogical opportunity. We propose that instructors shift the emphasis of their assignments from philosophy papers to "LLM dialogues": philosophical conversations between the student and an LLM. We describe our experience with using these types of assignments over the past several semesters. We argue that, far from undermining quality philosophical instruction, LLMs allow us to teach philosophy more effectively than was possible before. [ABSTRACT FROM AUTHOR]

Many instructors see the use of LLMs like ChatGPT on course assignments as a straightforward case of cheating, and try hard to prevent their students from doing so by including new warnings of consequences on their syllabi, turning to iffy plagiarism detectors, or scheduling exams to occur in-class. And the use of LLMs probably is cheating, given the sorts of assignments we are used to giving and the sorts of skills we take ourselves to be instilling in our students. But despite legitimate ethical and pedagogical concerns, the case that LLMs should never be used in academic contexts is quite difficult to see. Many primary and secondary schools are cutting back their writing instruction in an effort to teach to the test; at the same time, many high-end knowledge workers are already quietly expected to leverage their productivity with LLMs. To prepare students for an ever-changing world, we probably do have to teach them at least a little bit about writing with ChatGPT. [ABSTRACT FROM AUTHOR]

Introduction: The output of scholarly publications in scientific literature has increased exponentially in recent years. This increase in literature has been accompanied by an increase in retractions. Although some of these may be attributed to publishing errors, many are the result of unsavory research practices. The purposes of this study were to identify the number of retracted articles in nursing and reasons for the retractions, analyze the retraction notices, and determine the length of time for an article in nursing to be retracted. Design: This was an exploratory study. Methods: A search of PubMed/MEDLINE, the Cumulative Index to Nursing and Allied Health Literature, and Retraction Watch databases was conducted to identify retracted articles in nursing and their retraction notices. Results: Between 1997 and 2022, 123 articles published in the nursing literature were retracted. Ten different reasons for retraction were used to categorize these articles with one‐third of the retractions (n = 37, 30.1%) not specifying a reason. Sixty‐eight percent (n = 77) were retracted because of an actual or a potential ethical concern: duplicate publication, data issues, plagiarism, authorship issues, and copyright. Conclusion: Nurses rely on nursing‐specific scholarly literature as evidence for clinical decisions. The findings demonstrated that retractions are increasing within published nursing literature. In addition, it was evident that retraction notices do not prevent previously published work from being cited. This study addressed a gap in knowledge about article retractions specific to nursing. [ABSTRACT FROM AUTHOR]

AbstractThis essay concerns the pervasive “problem” of plagiarism in student writing, arguing against the easy adoption of technological policing “solutions” that may themselves contribute to an erosion of authentic learning and knowledge production. The paper critically examines the key tool, or weapon, in the war against plagiarism, namely the educational software Turnitin, and some of the discontent that has arisen in consequence of its widespread adoption in academic institutions. The second part of the essay examines practices of literary plagiarism, using the example of Shakespeare and Coetzee to question notions of originality. Both writers, one from the Renaissance, the other from contemporary literature, will serve as illustrative bookends for the English literary canon as a whole, exemplifying the close relationship between copying and creativity. These ideas are applied to the concept of a “knowledge commons,” which is indispensable to the idea of a good university, and which is being crowded out by inflated discourses of plagiarism and an overreach of plagiarism policing in the academy. Lastly, the essay briefly offers a few practical and pedagogic observations. [ABSTRACT FROM AUTHOR]

Doubts arise about the originality of a document when noticing a change in its writing style. This evidence to plagiarism has made the intrinsic approach for detecting plagiarism uncover the plagiarized passages through the analysis of the writing style for the suspicious document where a reference corpus to compare with is absent. The proposed work aims at discovering the deviations in document writing style through applying several steps: Firstly, the entire document is segmented into disjointed segments wherein each corresponds to a paragraph in the original document. For the entire document and for each segment, center vectors comprising average tf - idf weight of their word n - grams are constructed. Second, the degree of closeness is calculated through applying Cosine similarity to measure for each segment, the deviation of its center vector from the center vector of the entire document. Additionally, word n-gram length will be investigated to show its effect on the proposed system performance wherein, center vectors are computed considering word n-grams for different values of n (n= 1, 2, and 3). Performance evaluation of the proposed method was accomplished through the use of Precision, Recall, F-measure, Granularity, and Plagdet as evaluation measures. Moreover, PAN-PC-09 and PAN-PC-11 were used for detecting intrinsic plagiarism as evaluation corpora. It is shown that the proposed approach has achieved results that are comparable to the state-of-the-art methods. Positive impact was observed through discovering deviations in document writing style by computing weight vectors dissimilarity rather than calculating the difference between the word n-grams that exist in segments and their corresponding word n-grams in the suspicious document. Furthermore, when considering the length of word n-gram, better results were recorded for system performance when word bi-grams was used compared to word uni-grams and word tri-grams. [ABSTRACT FROM AUTHOR]

Good academic practice is more than the avoidance of clear-cut cheating. It also involves navigation of the gray zones between cheating and good practice. The existing literature has left students' understanding of gray zone practices largely unexplored. To begin filling in this gap, we present results from a questionnaire study involving N = 1639 undergraduate students from seven European countries representing all major disciplines. We show that large numbers of these students are unable to identify gray area issues and lack sensitivity to the context dependence of these. We also show that a considerable proportion of students have a poor understanding of concepts like plagiarism and falsification, not only in gray zone scenarios, but also in cases of relatively clear-cut cheating. Our results are similar across the faculties and countries of study, and even for students who have attended academic integrity training. We discuss the implications of this for academic integrity training. [ABSTRACT FROM AUTHOR]

The use of artificial intelligence in academia is a hot topic in the education field. ChatGPT is an AI tool that offers a range of benefits, including increased student engagement, collaboration, and accessibility. However, is also raises concerns regarding academic honesty and plagiarism. This paper examines the opportunities and challenges of using ChatGPT in higher education, and discusses the potential risks and rewards of these tools. The paper also considers the difficulties of detecting and preventing academic dishonesty, and suggests strategies that universities can adopt to ensure ethical and responsible use of these tools. These strategies include developing policies and procedures, providing training and support, and using various methods to detect and prevent cheating. The paper concludes that while the use of AI in higher education presents both opportunities and challenges, universities can effectively address these concerns by taking a proactive and ethical approach to the use of these tools. [ABSTRACT FROM AUTHOR]

The authors, a chemistry professor and a librarian, used a qualitative survey to assess student perceptions of a Wikipedia editing assignment that they included in a large upper-level biochemistry course. The assignment was initially intended as a public-facing alternative to a short research paper, emphasizing information literacy and scientific literacy. The goal of the survey was to use the results to enhance the assignment. The results of the survey and research for the literature review inspired a novel approach to the assignment using the perspective of metaliteracy. This approach encourages students to think critically about their role as scholars in a participatory environment. [ABSTRACT FROM AUTHOR]

This essay approaches the familiar subject of memory in Shelley through examining his exceptional gift for retentive memorization, a gift not unique to him, but also conspicuously possessed by Byron. A few instances, mostly taken from the Shelley circle and the poet Henry Kirke White, demonstrate the encouragement given to the development of a retentive memory during the Romantic period, and the admiration that it attracted, but also the apprehensiveness lest it become an end in itself. Examples follow of memory feats performed by Byron and Shelley independently and interactively, focusing on the effect upon Shelley's political poetry of 1819 of hearing Byron read the early part of Don Juan to him in the autumn of 1818, including portions that Shelley could not have reread in the interval. The question arises: did Shelley worry that his memory was a burden, tempting him into unwitting plagiarism? His draft revisions indicate that he sometimes might have done. [ABSTRACT FROM AUTHOR]

The purpose of this study was to map the distribution of publications on plagiarism among higher educational institutions in sub-Saharan Africa (SSA). Studies reviewed were based on 171 plagiarism related publications within a decade (2012–2022). Findings revealed that most plagiarism related articles were published in 2016. Additionally, a majority of the studies (53) were from Nigeria and Ghana (23). Most of the articles focused on students' and faculty's awareness of plagiarism, and institutional prevention of plagiarism, but were rather marginal on challenges involved in preventing plagiarism, as well as effects of plagiarism. Dominant forms of plagiarism were self-plagiarism, branded plagiarism and commission plagiarism. However, major causes of plagiarism comprised easy access to digital information and resources; poor supervision of students; pressure on academics to publish for promotion; and insufficient skills development regarding ethical academic writing. Additionally, plagiarism preventive software and policies on plagiarism were the main ways of preventing plagiarism. Finally, in fighting plagiarism, higher educational institutions in SSA encountered challenges such as lack of well-trained academic experts to detect and report plagiarism cases; reluctance on the part of technical administrative staff to investigate works for traces of plagiarism; and low plagiarism detection skills from project supervisors. Based on the findings, recommendations are made to stakeholders for future research, policy and practice. [ABSTRACT FROM AUTHOR]

Research on precarity in higher education has focused on how academics themselves experience this, but less is known about how staff precarity affects teaching and learning. This extended literature review explores how precarious working conditions affect practices aimed at supporting students' writing, such as teaching discipline-specific writing, providing feedback on drafts, and giving guidance about plagiarism and the use of AI. The most significant factors in academic malpractice relate to the quality of teaching and learning, but little time is spent inducting students into the norms of disciplinary knowledge creation, and this is exacerbated by precarious working conditions for subject lecturers. Teaching academic writing often falls to sessional tutors, who lack time or disciplinary knowledge to deal with malpractice. These manifestations of precarity, affecting both casualised subject lecturers and academic support tutors, likely mean fewer opportunities for students to develop their writing skills and engage with knowledge in meaningful ways. [ABSTRACT FROM AUTHOR]

The introduction of ChatGPT 3.5 in November 2022 ignited a sensation in the academic community, leaving many astounded by its capabilities. This new release more closely emulates human responses than its predecessors. Among its remarkable capabilities, it can answer questions, catalog items in MARC21, recommend reading lists, and make suggestions on a wide array of topics. To assess ChatGPT’s efficacy in aiding library users, the authors of this paper conducted an experiment comparing ChatGPT’s performance with that of librarians in answering reference questions. Thirty questions were randomly selected from the transaction log of the reference inquiries between June 1, 2023 to July 31, 2023 at the Rider University Libraries. These queries constituted 34% of the total user questions during this two-month period. The authors compared the answers by ChatGPT and those by reference librarians for their accuracy, relevance, and friendliness. The findings indicate that reference librarians markedly outperformed their robotic counterpart. An evident issue arises from ChatGPT’s deficiency in understanding local policies and practices. This consequently hinders its ability to provide satisfactory answers in those areas. OpenAI posits that ChatGPT’s proficiency can be enhanced through targeted fine-tuning using locally specific information. At the moment, ChatGPT remains a great tool for librarians. [ABSTRACT FROM AUTHOR]

Plagiarism adversely affects contributions to knowledge and the goal of instilling the skill of academic writing. Thus, most institutions of higher learning strive to develop mechanisms to help students understand the importance of academic integrity and reasons why they should avoid plagiarism. In many of these institutions, libraries/librarians play an integral role in academic integrity instruction as it is incorporated into information literacy instruction. This study examined students' understanding of plagiarism and the influence of Turnitin anti-plagiarism software on academic writing. The study used the survey research design. Using stratified and simple random sampling methods, questionnaires were administered to 175 students. Findings from the study revealed that efforts made by the university through seminars have influenced the perception of students on the concept of plagiarism and acts which constitute plagiarism. Though respondents agree with the fact that the use of Turnitin software influences academic writing positively, knowledge about the existence and usage of this software is low since the total number of students who had no idea about the university's subscription to the software was higher than those who did. Additionally, many of the respondents had difficulty understanding originality reports generated by the software and most were not aware of the existence of the university's policy on plagiarism. The study recommends for the library to intensify training on the usage and interpretation of similarity reports that are generated by the software as well as making the university's policy on plagiarism more visible or otherwise lose the capital and efforts invested in producing graduates who can contribute to knowledge and scholarship ethically. [ABSTRACT FROM AUTHOR]

The author talks about the inevitability of plagiarism. He discusses the accusations of research misconduct against Stanford and Harvard universities' presidents which brought their tenures to early ends, three dynamics that work against peer review as a plagiarism safeguard, and an overview of the articles in the issue.

Retracted publications are the scholarly articles that have been withdrawn from publication by authors or journals due to errors, misconduct, or ethical concerns. The present study aims to identify and analyse retracted papers by Indian authors. The data was extracted from the Scopus and also checked from the Retraction Watch database along with the journal's website. The extracted data was analysed using MS Excel, Jamovi, and SPSS-21. The study examined the year-wise retraction rate, reasons for retraction, authorship patterns, time lag for retraction, and impact on citations after retraction. The results showed that while the number of retracted publications per year increased over time, the rate of retraction per 10K publications remained constant. Duplicate publication and plagiarism were the most common reasons for retraction. Approximately one-third of the publications were retracted within six months, and the retraction time decreased over the years, especially in open-access journals. The average number of citations per paper per year before and after retraction were nearly similar. This study could assist librarians and researchers in understanding retractions, avoiding their use, and being cautious when referencing them. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Two opposed views of the history of Gothic fiction claim that a) the genre went into decline and 'died' in the early nineteenth century, and b) it has gone from strength to strength into the twenty-first century. This article defends a third hypothesis: that Gothic neither died nor endured but transformed into other genres to which the term 'Gothic' can apply analogically at best. Leaning on formal criteria (the codes or compositional conventions of eighteenth-century Gothic) it then offers a comparison between two short narratives thirty-three years apart, which, while being essentially 'the same' text, yet can be shown to belong to different genres. The article then projects the notion of language drift onto literary evolution to suggest that a form of genre drift accounts for this seeming oddity. [ABSTRACT FROM AUTHOR]

This article explores the complex relationship between the translingual turn and French literary prize-winners by focusing on a recent Goncourt laureate, Mohamed Mbougar Sarr, and his plurivocal poetics of translingualism in La plus secrète mémoire des hommes (2021). Through an examination of the text and its contexts, intertexts and paratexts, it demonstrates how the author draws on past, present and future representations of translingual lives and works to denounce the French literary system and undermine its monolingual perspectives and editorial judgements, such as plagiarism. It shows how the interconnected network of references to other Black and/or African literary prize-winners functions as a support for the author's translingual poetics, with various voices emerging through biographèmes, letters, messages and journal entries in the text. In conclusion, it confirms the connections between the translingual turn and French literary prize-winners, tracing how translingualism was introduced in the early twentieth century, firmly established around the turn of the millennium, then reinforced and renewed by Mbougar Sarr's writing and experiences in 2021 and beyond. [ABSTRACT FROM AUTHOR]

This brief commentary explores the opportunities and challenges presented by the increasing prevalence of artificial intelligence in the field of psychology in South Africa. Artificial intelligence has the potential to revolutionise teaching and learning, research, content production, and professional services, but it also presents some challenges to academic and professional psychology in South Africa. While some generative artificial intelligence can produce written work, such as assignments, literature reviews, and theses, they currently cannot replace human reasoning and the critical thinking abilities required to argue a particular point (at this stage). Artificial intelligence chatbots can also act as teaching assistants and even provide complex psychological interventions such as cognitive-behavioural therapy. In research and publication, artificial intelligence can increase efficiency and provide new insights and perspectives by detecting patterns and relationships that may have been overlooked by human researchers. However, the use of artificial intelligence raises ethical concerns, particularly around ownership and authorship of artificial intelligence–generated content, potential biases, and errors. The commentary concludes that as artificial intelligence technology continues to evolve, and with the human–artificial intelligence partnership continuing to unfold, it is important to recognise the risks associated with its use in academic writing and ensure that psychology students develop appropriate research skills. [ABSTRACT FROM AUTHOR]

The article focuses on addressing ethical concerns related to the potential use of personalized large language models (LLMs) for academic idea and prose generation. Concerns raised include issues of bias, conformity, lowered standards, and the potential negative effects on academic publishing. It authors advocate for a co-creation model where humans play a role in crafting, curating, and communicating the material generated by LLMs to ensure responsible use.

At the end of the Eighteenth-Century, the printer Isidoro Hernández Pacheco requested to reprint an old astrological prognostication by Diego Torres Villarroel. The Council of Castile censor delivered an overwhelming denial, showing the change of politics towards almanacs, widely tolerated until 1767. Actually, Pacheco intended to print a plagiarism, attributing to Torres a mocking prognostication by Francisco Robles. We study this case in its various ramifications, including posthumous reception of Torres Villarroel' work. [ABSTRACT FROM AUTHOR]

The main purpose of this study was to translate the Plagiarism Attitude Scale into Turkish and validate it for use in Turkish settings, in order to better understand research integrity attitudes and awareness of the Turkish academic and student community, while also contributing an instrument for research in this area. The research was designed and conducted with 483 participants. In the process of adapting the scale to Turkish, language, content, and construct validity analyses were performed. Following the completion of the validity phase, the reliability of the scale was examined using Cronbach's alpha coefficient and the split-half method. The results indicate that the scale's language and content validity are deemed sufficient. According to the findings of the research, the Plagiarism Attitude Scale, in its adapted Turkish version, is considered a valid and reliable tool. The use of this Turkish scale will assist local researchers in sharing their unique perspectives and help the international community better understand research ethics concerns in Türkiye. Additionally, this scale will serve as a valuable resource for planning educational programs. [ABSTRACT FROM AUTHOR]

In order to address the rising concerns about undergraduates' plagiarism in academic writing practices, a blended learning scenario (a combination of face-to-face learning with online learning) was designed and the effectiveness of it was tested. Results indicated that the students became more capable of distinguishing plagiarism cases in different scenarios, and their writing performance significantly improved by engaging in the blended learning scenario, i.e. the extent of plagiarism substantially decreased and writing quality greatly increased. Furthermore, the students mostly provided positive feedback towards the learning intervention. This study contributes to existing literature on instructional solutions to plagiarism issues by focusing on how students' understandings of plagiarism and source use can be achieved during their writing in a blended learning scenario. [ABSTRACT FROM AUTHOR]

The article presents conversations between feminists women about epistemic and physical harm, epistemic injustice, gendered-based violence and joy in academia. Topics discussed include plagiarism in academic research, academics capitalizing on the free labor of junior colleagues, curriculum on research methodologies that reproduce a patriarchal order in the academia, link between the production of knowledge and sexual power, bullying and institutional abuse, and mistrust in senior academics.

Key points: Academia is undergoing transformation with rapid technological advancements, global collaboration, and the rise of AI.Maintaining research integrity is paramount in the face of new challenges and opportunities.The peer review process, vital for research integrity, is strained due to the high volume of academic papers.Cactus Communication's (CACTUS) global survey during Peer Review Week 2022 gathered insights from 685 participants on research integrity and peer review.Survey participants emphasized the importance of peer review in detecting various issues, including plagiarism and questionable research practices.Actions taken in response to integrity concerns varied, with some participants seeking guidance from colleagues or informing journal editors.Digital innovations, especially AI‐driven tools, promise to revolutionize peer review processes, from manuscript screening to reviewer selection and evaluation.AI tools like Chat GPT can aid authors in improving writing quality and assist reviewers in generating detailed feedback.Concerns about data privacy and the need for a balance between human expertise and AI assistance are raised in the context of peer review.AI plagiarism detection tool scan complement human efforts, providing an additional layer of scrutiny.Increased digital innovation allows for flexible review formats, international collaboration, and heightened transparency in the review process.The integration of AI into peer review holds the potential to enhance efficiency and objectivity but raises concerns about bias and transparency.Guidelines, bias mitigation measures, accountability mechanisms, and ongoing training are essential for the responsible use of AI in peer review.Encouraging peer review systems to embrace innovation and ethical AI is crucial for adapting to changing dynamics while upholding core principles of research integrity. [ABSTRACT FROM AUTHOR]

This study investigates the effectiveness of library user education programmes in enhancing students' awareness and understanding of seven types of plagiarism. The focus was on three distinct groups of students: undergraduates at two different levels (level I and level III) and postgraduates. The methodology employed a structured questionnaire to collect data via a survey approach before and after the library instruction sessions. To facilitate data collection, an online survey was created using Google Forms, streamlining the process of reaching out to participants. Results demonstrate that the library user education programs significantly contributed to the enhancement of students' comprehension of plagiarism. Notably, Word-for-Word and Mosaic plagiarism were well comprehended across all student groups, indicating the effectiveness of the educational interventions for these types. While the majority of plagiarism types indicate considerable improvement following the instructional sessions, the study highlights the importance of tailored approaches for addressing challenging areas. Educators are encouraged to prioritize comprehensive and targeted strategies to maximize the outcomes of plagiarism and referencing in education. [ABSTRACT FROM AUTHOR]

This paper investigates retracted articles indexed in the Scientific Electronic Library Online (SciELO) Brazil, using bibliometric techniques to identify the characteristics of these retractions and relevant citation trends. All records of retracted articles from the first record in October 2004 to April 2022 were included. Sixty-seven retractions and 870 citations pre- and post-retraction were analyzed. Results indicate a change of scenario that began in 2015, with recurrences of retracted articles allegedly produced by paper mills. The prevalence of retractions derived from professional misconduct in health research and the frequency of post-retraction citations in health sciences raise concerns in the chain of stakeholders, public health, and scientific development. [ABSTRACT FROM AUTHOR]

The rapid advancement of artificial intelligence (AI) has given rise to sophisticated language models that excel in understanding and generating human-like text. With the capacity to process vast amounts of information, these models effectively tackle problems across diverse domains. In this paper, we present a comparative analysis of prominent AI language models—ChatGPT and Google Bard—focusing on their ability to solve undergraduate finance problems. We find that GPT-4 significantly outperforms Bard-1.0, excelling in easy problems but struggling with complex ones. The results suggest that it is crucial to handle AI with care in order to uphold academic integrity. [ABSTRACT FROM AUTHOR]

Document similarity recognition is one of the most important problems in natural language processing. This paper proposes a plagiarism comparison mechanism called JCF. Initially, the TF–IDF scheme is applied to build a bag of words as the representation of the common features of all documents. Then, the plagiarism comparison is carried out in a coarse-grained manner, which speeds up the similarity comparison. Finally, the most similar documents can then be compared in detail based on a fine-grained approach. In addition, the JCF detects plagiarism at both syntax level and semantic-like level. To prevent the distortion of similarity comparison, this paper further develops a similarity restoration approach such that the proposed JCF can obtain both advantages of quickness and accuracy. Performance studies confirm that the proposed JCF outperforms existing studies in terms of precision, recall and F1 score. [ABSTRACT FROM AUTHOR]

This article aims to reveal and examine Oulipo's engagement with China. While individual members like Michèle Métail and Raymond Queneau have seemingly contributed to the group's affinity for China on a superficial level, a deeper analysis of the two Oulipism tendencies suggests this interest is fundamentally impersonal and detached. The essence of Oulipism means the group can never be fascinated by any single influence, even while remaining open to Chinese inspiration. Thus, Oulipo harbors what can be characterized as a disinterested interest in China—intrigued by its potential without becoming enthralled by it. [ABSTRACT FROM AUTHOR]

In April 2023, a Training Workshop on mixed methods in Health Education and Research was held at the University of Aveiro. In this training, a problem was posed about what plagiarism and/or self- plagiarism is, and we found very few correct answers regarding the definition of these concepts. This led us to question what is really known about this topic and where we can find concrete examples of plagiarism and self-plagiarism that have gone unnoticed in society. To carry out this study, a bibliometric and systematic review of the literature was carried out, between the years 2014 and 2022, in the International databases WOS and SCOPUS with the use of the keywords "Plagiarism", "Scientific" and "Education", using VOSViewer Software. As a result of this search, 40 documents with the greatest impact on education were selected, analyzing the content of their summaries and conclusions through CAQDAS NVivo. Among the conclusions obtained, we observe that there is a real need to make known: various recurrent instances of plagiarism and self-plagiarism that occur in academic environments of higher education and analytical models that shed light on the moments prone to these behaviours, offering concrete recommendations to prevent them. his persistence. As a limitation, since this is an exploratory study, the results obtained were not compared with other databases, such as ERIC. Finally, to obtain more significant data in the future, we intend to expand this research by conducting interviews and focus groups with different students and education professionals, to compare the information compiled with new, broader searches that include other databases. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is a disruptive technology that has revolutionized various industries, including the field of research writing. Using AI-based tools in research writing brings a new level of efficiency, accuracy, and productivity to the process, allowing researchers to tap into alternative perspectives and generate fresh insights that can boost the quality of research work. In this article, we discuss the current trends and the potential benefits of open Artificial Intelligence (AI-) based tools for research writing, focusing on AI tools. In addition, we also discuss the impact of collaborative writing with AI on productivity, highlighting the benefits of AI tools in the research writing process. The current trends show that AI tools enable researchers to perform complex data analysis, generate personalized content, and identify patterns that can aid decision-making. Therefore, it is imperative for researchers to embrace AI tools, learn how to use them effectively and harness their potential to achieve better research outcomes. [ABSTRACT FROM AUTHOR]

University faculty immediately had many questions and concerns in response to the public proliferation of generative artificial intelligence programs leveraging large language models to generate complex text responses to simple prompts. Librarians at the University of South Florida (USF) pooled their skills, existing relationships with faculty and professional staff across campus to provide information that answered common questions raised by those faculty on generative artificial intelligence usage within research related topics. Faculty concern regarding the worry of plagiarism, how to instruct students to use the new tools and how to discern the reliability of information generated by artificial intelligence tools were placed at the forefront. By augmenting existing tutorials and instruction sessions, and creating a new information resource, the library was able to build a timely foundation to support future efforts to address the changing information needs of faculty and students using generative artificial intelligence programs and tools. [ABSTRACT FROM AUTHOR]

This study presents an exploration into the application of the artificial intelligence chatbot ChatGPT 3.5 in the context of two Hispanic literature survey courses at the University of Delaware during the spring 2023 semester. The introduction of ChatGPT into these learning environments aimed to address two key challenges in teaching Spanish and Latin American literature: falling enrollment rates and rising instances of plagiarism. ChatGPT’s role was twopronged: it served as a component of in-class discussions and a resource for final papers. A total of twenty-one students participated in a follow-up survey designed to gauge their perceptions of ChatGPT as an innovative learning tool. The outcome revealed mixed, yet promising, responses to the use of AI technology in a literature classroom. The data suggest that the ongoing incorporation of cutting-edge tools like ChatGPT into literature courses holds the potential to captivate a diverse group of students and increase enrollment. In addition, the data collected, along with the professor’s analysis of final papers, indicate that ChatGPT can be effective in curbing plagiarism. Responsible AI utilization is becoming increasingly vital in various job markets, and integrating such skills into curricula from STEM to Humanities is crucial for our students’ future career success. [ABSTRACT FROM AUTHOR]

The artificial intelligence (AI) tool ChatGPT, which is based on a large language model (LLM), is gaining popularity in academic institutions, notably in the medical field. This article provides a brief overview of the capabilities of ChatGPT for medical writing and its implications for academic integrity. It provides a list of AI generative tools, common use of AI generative tools for medical writing, and provides a list of AI generative text detection tools. It also provides recommendations for policymakers, information professionals, and medical faculty for the constructive use of AI generative tools and related technology. It also highlights the role of health sciences librarians and educators in protecting students from generating text through ChatGPT in their academic work. [ABSTRACT FROM AUTHOR]

Plagiarism is one of the oldest defects that appeared in poetry, and this phenomenon of plagiarism was not limited to an era or a nation; this research examines Arabic poetry in Vehbi's collection (deceased 1224 AH/1809 AD) to determine its originality and free from plagiarism. The Arabic poetry contained in Vehbi's collection is mostly attributed to contemporary poets, namely doctor Naṣīr al-Dīn al-Iṣfahānī (deceased 1191 AH/1777 AD), the poet Hātef al-Isfahānī (deceased 1198 AH/1784 AD), and the Iraqi poet Kāzim al-Uzrī (1143-1213 AH/ 1730-1798 AD). These poems shared by Vehbi and the doctor Naṣīr al-Dīn al-Iṣfahānī, the poet Hātef al-Isfahānī and the ethnic poet Kāzim al-Uzrī formed most of his Arabic poetry. The number of common verses that we have been able to identify between Vehbi and the mentioned Poets has reached about 248 verses. Some of these verses are completely identical, and some are quite similar. The poems attributed to both Vehbi and Naṣīr al-Dīn al-Iṣfahānī constitute most of these poems, as the number of verses shared between them reached 214 verses, which means more than two-thirds of Vehbi's Arabic poetry. There is a strong possibility that during his embassy to Sultan Karīm Khān Zand, Vehbi met with his doctor Naṣīr al-Dīn al-Iṣfahānī, or saw the doctor's poems and correspondence with the poet Hātef al-Isfahānī, because Vehbi was sent to Sultan Karīm Khān as a messenger from the Ottoman Sultan and stayed in Shiraz for a while. It is natural that he met with senior state dignitaries and palace officials there, including the Sultan's doctor Naṣīr al-Dīn al-Iṣfahānī, who was close to the sultan or saw his poetry. It is also possible that in Baghdad, which he visited after returning from Shiraz, he met the Iraqi poet Kāzim al-Uzrī or got acquainted with his poetry. Especially that Kāzim al-Uzrī was connected with the Wali of Baghdad and its senior statesmen, and he organized praises for them. There is no doubt that plagiarism has occurred in the poems shared between Vehbi and other poets, which constitute almost 83% of Vehbi's Arabic poetry. These shared poems must have been written by Vehbi and plagiarized by the rest of the poets, or they must have been composed by other poets and plagiarized by Vehbi. It is most likely that Vehbi was the one who plagiarized these poems, changed some of them and made poems from them that he presented to senior statesmen for the following reasons: 1-Vehbi presented his collection to Sultan Selim III after he sat on the throne in 1203 AH/ 1789 AD. Twelve years before this date, the doctor Naṣīr al-Dīn al-Iṣfahānī had died. Also, five years before this date, the poet Hātef al-Isfahānī had died. If we assume that most of his Arabic poems were published for the first time at that time, it is impossible that they were plagiarized by Naṣīr al-Dīn al-Iṣfahānī and an Hātef al-Isfahānī. On the other hand, there is nothing to confirm that he composed these poems before his trip to Iran and Iraq, but it is definitely proven that Vehbi composed a section of his Arabic poems after returning from his embassy so that he could return to his work in the judiciary after he was removed from it, and we mention an example of the poem in which he praised Sheikh al-Islam Muhammad Sharif Effendi, who became Sheikh of Islam in the year (1192 AH/1778 AD), that is in the period after Vehbi returned from his embassy. Therefore, Naṣīr al-Dīn al-Iṣfahānī could not have plagiarized the poems of Vehbi contained in the mentioned poem because he died in (1191 AH/1777 AD), which was a year before Vehbi presented his poem to Shaykh al-Islām. 2-the poems contained in Vehbi's collection are disjointed, confused, full of errors and lack thematic unity and logical order of the verses, which often leads to the absence of meaning. As for the poems of the rest of the poets, they are interconnected and consistent with the purposes or occasions for which they were written, and their verses are arranged in a logical order that does not disturb the meaning. 3- The poems attributed to both Vehbi and Naṣīr al-Dīn al-Iṣfahānī include many vocabulary related to medicine and philosophy, and there is no doubt that the doctor and the one who works in philosophy is more capable than others of employing and using these terms in his poetry. After referring to the important dates in this regard and studying the common poetry, the research showed that Vehbi had plagiarized the poems of these poets, and made some amendments to them. The research also showed that the amendments made by Vehbi to the poetry of the poets whose poems he plagiarized led to errors and the absence of meaning in some cases. [ABSTRACT FROM AUTHOR]

Generative Artificial Intelligence (AI) based on large language models such as ChatGPT, DALL·E 2, Midjourney, Stable Diffusion, JukeBox, and MusicLM can produce text, images, and music that are indistinguishable from human-authored works. The training data for these large language models consists predominantly of copyrighted works. This Article explores how generative AI fits within fair use rulings established in relation to previous generations of copy-reliant technology, including software reverse engineering, automated plagiarism detection systems, and the text-data mining at the heart of the landmark HathiTrust and Google Books cases. Although there is no machine learning exception to the principle of nonexpressive use, the largeness of likelihood models suggest that they are capable of memorizing and reconstituting works in the training data, something that is incompatible with nonexpressive use. At the moment, memorization is an edge case. For the most part, the link between the training data and the output of generative AI is attenuated by a process of decomposition, abstraction, and remix. Generally, pseudo-expression generated by large language models does not infringe copyright because these models "learn" latent features and associations within the training data; they do not memorize snippets of original expression from individual works. However, this Article identifies situations in the context of text-to-image models where memorization of the training data is more likely. The computer science literature suggests that memorization is more likely when models are trained on many duplicates of the same work, images are associated with unique text descriptions, and the ratio of the size of the model to the training data is relatively large. This Article shows how these problems are accentuated in the context of copyrightable characters and proposes a set of guidelines for "Copyright Safety for Generative AI" to reduce the risk of copyright infringement. [ABSTRACT FROM AUTHOR]

In programming education, the result of plagiarism detection is a crucial criterion for assessing whether or not students can pass course exams. Recently, the prevalent methods for detecting student plagiarism have been proposed by analyzing source code. These methods extract features (such as token, abstract syntax tree and control flow graph) from the source code, examine the similarity of codes using various similarity detection methods, and then perform plagiarism detection based on a predefined plagiarism threshold. However, these previous methods for plagiarism detection have some problems. First, they are less effective in detecting code modification related to structure. Second, they require a considerable number of training data, which demand high computing time and space. Third, they cannot determine whether students plagiarize in time. We propose a novel plagiarism detection method by analyzing the behavioral features of students during the coding process. Specifically, we extract five behavioral features based on students' programming habits. Then, we use a feature ranking-based suspiciousness algorithm to obtain the possibility of student plagiarism. Based on our proposed method, we develop the Online Integrated Programming Platform. To evaluate the accuracy of our method, we conduct a series of experiments. Final experimental results indicate that our method achieves promising results with Accuracy, Precision, Recall and F 1 values of 0.95, 0.90, 0.95 and 0.92, respectively. Finally, we also analyze the correlation between whether students plagiarized and their regular and final grades, which can further verify the effectiveness of our proposed method. [ABSTRACT FROM AUTHOR]

What is the relation between plagiarism and embarrassment? What unspoken rules dictate our responses to improper literary behaviour? Addressing these questions against the backdrop of South African author Willem Anker’s substantial ‘borrowings’ from Samuel Beckett, this article proposes three alternative avatars – the catfish, hacker, and emperor – to displace Martial’s archetypal plagiarius or enslaver. The catfish is an impostor, an appropriator and aggregator of identities who aims to seduce. The hacker is a digital bandit whose daring encroachments are as much admired as feared. And the emperor is that cipher either clothed by common consent or stripped at the cost of our own exposure. Whatever their vices, these figures have the virtue of nudging discussion of plagiarism away from rights and ownership towards identity, trust and exposure. Where the enslaver tends to ringfence the wronged and the wrong-doer, the alternative avatars open towards the reader. They ask us to consider our role in constituting, condoning or condemning acts of literary deceit, to mark the connections between our moral judgements and our affective responses, and, ultimately, to reflect on our position as hypocrites lecteurs when confronted with plagiarism. [ABSTRACT FROM AUTHOR]

Among the malpractices that undermine research integrity, plagiarism is a major threat given its frequency and evolving presentations. Plagiarism implies the intentional grabbing of texts, ideas, images, or data belonging to others and without crediting them. However, the different and even masked forms of plagiarism often difficult a clear identification. Currently, the many kinds of fraud and plagiarism account for most retractions in traditional and open access journals. Further, the rate of retracted articles is higher in the Latin American databases LILACS and Scielo than in PubMed and Web of Science. This difference has been related to the typical laxity of our culture and the lack of English writing skills of non-Anglophone researchers. These features explain the conflict experienced by Latin American students in USA where they face a stricter culture regarding academic and scientific plagiarism. In the internet era, the ease of accessing scientific literature has increased the temptation to plagiarize but this ethical breach has been countered by antiplagiarism software. Now, the so-called "paraphragiarism" prompted by paraphrasing tools exceeds the infamous "copy-paste". For instance, the innovative ChatGPT can be used for plagiarizing and paraphragiarizing. Moreover, its inclusion as coauthor in scientific papers has been banned by prestigious journals and the International Committee of Medical Journal Editors because such chatbot cannot meet the required public responsibility criterium. To avoid plagiarism, it is enough to always give due credit in the proper way. Lastly, I question the ill-fated and now prevailing conjunction of blind faith in progress and zero skepticism that prevents us from foreseeing the negative consequences of technological advances. [ABSTRACT FROM AUTHOR]

The article discusses the impact of generative artificial intelligence tools, particularly large language models like ChatGPT, on scholarly publishing, highlighting the need for transparent disclosure when authors use generative AI and the role of editors and reviewers in maintaining responsible scholarly work in the context of AI technology. The authors present a set of preliminary recommendations to address the ethical and practical challenges of generative AI in scholarly publishing.

As we stand on the cusp of the 30th anniversary of the International Journal of Industrial Engineering: Theory, Applications and Practice (we call it "the Journal"), it is a moment to celebrate its remarkable journey and acknowledge the vital roles played by its authors and reviewers. From its inception, the Journal has evolved into a leading international journal renowned for its commitment to publishing high-quality research that has significantly impacted the field of industrial and manufacturing engineering. The Journal's scope encompasses a broad spectrum of industrial engineering disciplines. This comprehensive approach ensures that the Journal remains at the forefront of industrial engineering research and continues to serve as a valuable resource for both scholars and practitioners in the field. [ABSTRACT FROM AUTHOR]

Automatic detection of concealed plagiarism in the form of paraphrases is a difficult task, and finding a successful unsupervised approach for paraphrase detection is necessary as a precondition to change that. This comparative study identified the most efficient methods for unsupervised paraphrased document detection using similarity measures alone or combined with Deep Learning (DL) models. It proved the hypothesis that some DL models are more successful than the best statistically‐based methods in that task. Many experiments were carried out, and their results were compared. The text similarities between documents are obtained from 60 different methods using five paraphrase corpora, including the new one made by authors, as an important original contribution. Some DL models achieved significantly better results than those obtained by the best statistical methods, especially pre‐trained transformer‐based language models with average values of Accuracy and F1 of 85.8% and 88.3%, respectively, with top values of 99.9% and 98.4% for Accuracy and F1 on some corpora. These results are even better than those of supervised and combined approaches. Therefore, here presented results prove that detecting concealed plagiarism becomes an attainable goal. This study highlighted those language models with the best overall results for paraphrase detection as best suited for further research. The study also discussed the choice of similarity/distance measure paired with embeddings produced by DL models and some advantages of using cosine similarity as the fastest measure. For 60 different methods, complexity has been defined in O notation. Times needed for their implementation have also been presented. The article's results and conclusions are a firm base for future semantic similarity, paraphrasing, and plagiarism detection studies, clearly marking state‐of‐the‐art tools and methods. [ABSTRACT FROM AUTHOR]