Use Of Plagiarism Detection Software Research Articles

Instilling the need for academic honesty into Hong Kong university students: how well are we doing?

ABSTRACT All public-funded Hong Kong universities have explicit practices to promote integrity and prevent students’ academic dishonesty. Using the Behaviour Change Wheel as a conceptual framework, three common practices were analysed in the present study, namely, enforcement of policies to penalize dishonest acts, use of plagiarism detection software, and mandatory attendance at academic honesty workshops. Qualitative data were collected from 50 students (in 14 focus groups) and individual interviews with 18 faculty members from eight publicly-funded universities in Hong Kong. Content analyses reveal that, although the students and faculty staff endorsed punishment as an effective intervention to reduce motivation to cheat, they also believed it would not enhance motivation for honest behaviours. Plagiarism detection software might reduce opportunities to plagiarize, but students with dishonest motivations will only turn to harder-to-trace means to cheat. While demonstrating good concepts of academic honesty, a sign that academic honesty education was working, the students attributed dishonest motivation to insufficient capability to perform academic tasks, which they described as a common problem. Both students and staff opined that the solution lies in more responsive learning support and pedagogical enhancement, but that it is constrained by university policies.

Knowledge, Attitudes, and Practices of Plagiarism as Reported by Participants Completing the AuthorAID MOOC on Research Writing.

To explore the knowledge, attitudes and practices regarding plagiarism in a large culturally diverse sample of researchers who participated in the AuthorAID MOOC on Research Writing. An online survey was designed and delivered through Google Forms to the participants in the AuthorAID MOOC on Research Writing during April to June 2017. A total of 765 participants completed the survey (response rate 47.8%), and 746 responses were included in the analysis. Almost all participants (97.6%) reported knowledge of the term "plagiarism", and 89.1% of them understand the meaning of the term before joining the course. Most participants reported that their university does not provide access to plagiarism detection software (82.0%), and 35% participants admitted they had been involved in plagiarism during their education. Overall attitudes toward plagiarism (65.3 ± 10.93) indicated low acceptance of plagiarism. Moreover, low scores were reported for approval attitude (25.22 ± 5.63), disapproval attitude (11.78 ± 3.64), and knowledge of subjective norms (20.63 ± 5.22). The most common reason for plagiarizing was lack of time (16.1%), and the most common consequence was the perception that "those who plagiarize are not respected or seen positively" (71.4%). Developing country researchers appear to be familiar with the concept of plagiarism, but knowledge among the participants surveyed here was incomplete. Knowledge about plagiarism and awareness of its harmfulness must be improved, because there is an obvious relationship between attitudes toward plagiarism and knowledge, reasons and consequences. The use of plagiarism-detection software can raise awareness about plagiarism.

Writing for Academic Journals in the Digital Era

The use of digital technologies has transformed the processes of writing for academic journals and the dissemination and preservation of academic work. It has also made the measurement of the impact of publications in academic journals easier and this information more accessible to authors. In this article I discuss some of the ways in which digital technologies have changed writing for academic journals as well as how digital technologies are being used in the submission and review of journal articles. This includes ways in which academic work can be stored and shared, the use of citation management tools, and the sharing of research materials once an article has been accepted for publication. I also give an overview of how digital technologies are being used in the review of journal articles including the use of plagiarism detection software. Issues in online publishing are outlined as is the development of open-access journals and the rise of predatory publishers. Social media and journal publishing and the use of multimodality in research article writing are also discussed.

An Evaluation of an Extended Intervention to Reduce Plagiarism in Bachelor of Nursing Students.

Pre- and postintervention surveys of first-year nursing students were undertaken to establish the students' knowledge of plagiarism following implementation of an online library-based Academic Integrity Module and the use of plagiarism detection software. Knowledge and understanding of plagiarism improved, but students' ability to paraphrase remained poor. Students entering postsecondary educational institutions require ongoing support and learning opportunities to improve their skills in paraphrasing and referencing to avoid plagiarism.

Knowing and avoiding plagiarism during scientific writing.

Plagiarism has become more common in both dental and medical communities. Most of the writers do not know that plagiarism is a serious problem. Plagiarism can range from simple dishonesty (minor copy paste/any discrepancy) to a more serious problem (major discrepancy/duplication of manuscript) when the authors do cut-copy-paste from the original source without giving adequate credit to the main source. When we search databases like PubMed/MedLine there is a lot of information regarding plagiarism. However, it is still a current topic of interest to all the researchers to know how to avoid plagiarism. It's time to every young researcher to know ethical guidelines while writing any scientific publications. By using one's own ideas, we can write the paper completely without looking at the original source. Specific words from the source can be added by using quotations and citing them which can help in not only supporting your work and amplifying ideas but also avoids plagiarism. It is compulsory to all the authors, reviewers and editors of all the scientific journals to know about the plagiarism and how to avoid it by following ethical guidelines and use of plagiarism detection software while scientific writing.

Faculty Perceptions of Student Self Plagiarism: An Exploratory Multi-university Study

The purpose of this research study was to evaluate faculty perceptions regarding student self-plagiarism or recycling of student papers. Although there is a plethora of information on plagiarism and faculty who self-plagiarize in publications, there is very little research on how faculty members perceive students re-using all or part of a previously completed assignment in a second assignment. With the wide use of plagiarism detection software, this issue becomes even more crucial. A population of 340 faculty members from two private universities at three different sites was surveyed in Fall 2012 semester regarding their perceptions of student self-plagiarism. A total of 89 faculty responded for a return rate of 26.2 %. Overall, institutional policies on self-plagiarism did not exist and faculty did not clearly understand the concept and believed their students did not either. Although faculty agreed students need to be educated on self-plagiarism, faculty assumed students had previously been educated on plagiarism as well as self-plagiarism; only 13 % ensured students understood this concept.

The Instructional Challenges of Student Plagiarism

The focus of this article is university teachers’ and students’ views of plagiarism, plagiarism detection, and the use of plagiarism detection software as learning support. The data were collected from teachers and students who participated in a pilot project to test plagiarism detection software at a major university in Finland. The data were analysed through factor analysis, T-tests and inductive content analysis. Three distinct reasons for plagiarism were identified: intentional, unintentional and contextual. The teachers did not utilise plagiarism detection to support student learning to any great extent. We discuss the pedagogical implications and suggest that the contextual reasons for plagiarism require focus primarily on study strategies, whereas the intentional reasons require profound discussion about attitudes and conceptions of good learning and university-level study habits.

Returning students’ right to access, choice and notice: a proposed code of ethics for instructors using Turnitin

This paper identifies the ethical issues associated with college instructors' use of plagiarism detection software (PDS), specifically the Turnitin program. It addresses the pros and cons of using such software in higher education, arguing that its use is justified on the basis that it increases institutional trust, and demonstrating that two common criticisms of such software are not universally valid. An analysis of the legal issues surrounding Turnitin, however, indicates that the way it is designed and operates raises some ethical issues because it denies students notice, access and choice about the treatment of their personal information. The paper concludes with a set of guidelines for instructors using Turnitin in the classroom.

Automatic Student Plagiarism Detection: Future Perspectives

The availability and use of computers in teaching has seen an increase in the rate of plagiarism among students because of the wide availability of electronic texts online. While computer tools that have appeared in recent years are capable of detecting simple forms of plagiarism, such as copy-paste, a number of recent research studies devoted to evaluation and comparison of plagiarism detection tools revealed that these contain limitations in detecting complex forms of plagiarism such as extensive paraphrasing and use of technical tricks, such as replacing original characters with similar-looking characters from foreign alphabets. This article investigates limitations in automatic detection of student plagiarism and proposes ways on how these issues could be tackled in future systems by applying various natural language processing and information retrieval technologies. A classification of types of plagiarism is presented, and an analysis is provided of the most promising technologies that have the potential of dealing with the limitations of current state-of-the-art systems. Furthermore, the article concludes with a discussion on legal and ethical issues related to the use of plagiarism detection software. The article, hence, provides a “roadmap” for developing the next generation of plagiarism detection systems.

A Consideration of the Use of Plagiarism Tools for Automated Student Assessment

In this paper, the authors evaluate the flexibility and richness of two well-established text analysis plagiarism tools, through a consideration of the use of plagiarism detection software as a mechanism for the automated assessment of student-created narrative in a virtual learning environment (VLE). The authors are currently engaged in a project creating a prototype VLE, using technologies for multilevel and multiplayer games, based on the inherent support such an environment would provide for constructivist learning, engagement, and contextual socialization. Progress between levels in the VLE will be based on the creation, by the student, of a narrative linking together a number of conceptual elements obtained through game-play at that level. Support for the narrative creation process will help the student to contextualize the conceptual elements, providing the necessary linking elements or themes to enable the student to produce a coherent description of their understanding of the concepts. A particular challenge in such environments is the need for fast, real-time feedback to students to maintain the level of engagement and to support the game-play metaphor. Additionally, the student must be able to make as many attempts to progress as they need and it will be their decision when and how often to submit for assessment. Since the student narrative will be in a textual form and can therefore be related to a sample solution narrative, generated by the author of the level within the learning environment, the idea of using plagiarism detection software as the mechanism for automated comparison and assessment was considered appropriate for investigation. While the limitation of such tools would appear to be that they are seeking direct copies of text elements, the authors wanted to investigate whether they offered sufficient richness and fuzziness to detect common conceptually-linked texts. The initial decision was to experiment with text-analytic tools, since they are both widely used and readily available. The tools chosen were TurnItIn, a commercial tool provided to the U.K. higher education community by the U.K. Joint Information Systems Committee (JISC), and VALT/VAST, a set of tools created at the Centre for Interactive Systems Engineering at London South Bank University, London, U.K., the workings of which are based on recognized and well-published research. An experiment using a small group of students in a traditional assessment situation was carried out, and is described in detail. The rationale for this approach was that there is not yet a fully working prototype of the VLE in which to carry out such an experiment, but that the conditions necessary to test the hypothesis that plagiarism tools could be utilized for such a purpose could be replicated sufficiently to make such an experiment viable. The results of the experiment demonstrated neither a correlation between the sample solution and student solutions, nor any correlation between the individual student solutions, proving the null hypothesis. This result demonstrates that these tools are not useful for the development of automated assessment within the VLE, and the authors are now giving consideration to the use of lexical analysis/tokenizer and other tools. However, it also suggests that these text-analytic plagiarism tools are too firmly focused on direct copy, which does raise the question of whether or not they offer enough richness and fuzziness to detect a sophisticated plagiarism attempt using, for example, text replacement tools. An ongoing close relationship between research in automated assessment and plagiarism detection is also proposed, to achieve mutual benefit.

Is There an Effective Approach to Deterring Students from Plagiarizing?

The purpose of this study was to evaluate the effectiveness of plagiarism detection software and penalty for plagiarizing in detecting and deterring plagiarism among medical students. The study was a continuation of previously published research in which second-year medical students from 2001/2002 and 2002/2003 school years were required to write an essay based on one of the four scientific articles offered by the instructor. Students from 2004/2005 (N = 92) included in present study were given the same task. Topics of two of the four articles were considered less complex, and two were more complex. One less and one more complex articles were available only as hardcopies, whereas the other two were available in electronic format. The students from 2001/2002 (N = 111) were only told to write an original essay, whereas the students from 2002/2003 (N = 87) were additionally warned against plagiarism, explained what plagiarism was, and how to avoid it. The students from 2004/2005 were warned that their essays would be examined by plagiarism detection software and that those who had plagiarized would be penalized. Students from 2004/2005 plagiarized significantly less of their essays than students from the previous two groups (2% vs. 17% vs. 21%, respectively, P < 0.001). Over time, students more frequently choose articles with more complex subjects (P < 0.001) and articles in electronic format (P < 0.001) as a source for their essays, but it did not influence the rate of plagiarism. Use of plagiarism detection software in evaluation of essays and consequent penalties had effectively deterred students from plagiarizing.