scholarly journals Detection of Online Contract Cheating Through Stylometry: A Pilot Study

2020 ◽  
Vol 24 (2) ◽  
Author(s):  
David Ison
Keyword(s):  
Pilot Study ◽  
Academic Integrity ◽  
Software Systems ◽  
Plagiarism Detection ◽  
Contract Cheating ◽  
Software Packages ◽  
Average Accuracy ◽  
Detection Software ◽  
Authorship Authentication ◽  
News Headlines

Contract cheating, instances in which a student enlists someone other than themselves to produce coursework, has been identified as a growing problem within academic integrity literature and in news headlines. The percentage of students who have utilized this type of cheating has been reported to range between 6% and 15.7%. Generational sentiments about cheating and the prevalent accessibility of contract cheating providers online seems to only have exacerbated the issue. The problem is that there is currently no simple means identified and verified to detect contract cheating, as available plagiarism detection software has been shown to be ineffective in these cases. One method that is commonly used for authorship authentication in nonacademic settings, stylometry, has been suggested as a potential means for detection. Stylometry uses various attributes of documents to determine if they were written by the same individual. This pilot study sought to assess the utility of three easy to use and readily available stylometry software systems to detect simulated cases of contract cheating on academic documents. Average accuracy ranged from 33% to 88.9%. While more research is necessary to further investigate the reliability of the best performing software packages, stylometry software appears to show significant promise for the potential detection of contract cheating.

Selection of Plagiarism Detection Software and Its Integration Into Moodle for Universities

2019 ◽  
pp. 200-215 ◽  
Author(s):  
Mehmet Bilge Kağan Önaçan ◽  
Mesut Uluağ ◽  
Tolga Önel ◽  
Tunç Durmuş Medeni
Keyword(s):  
Higher Education ◽  
Open Source ◽  
Selection Criteria ◽  
Nominal Group Technique ◽  
Education Institution ◽  
Nominal Group ◽  
Plagiarism Detection ◽  
Software Packages ◽  
Detection Software ◽  
Selection Of

Plagiarism detection software packages have an important role in detection of plagiarism in exams, assignments, projects, and scientific researches. The main goal of this chapter is the selection of plagiarism detection software (PDS) and its integration into Moodle, an open source learning management system (LMS), for the use of a higher education institution. For this reason, first, the selection criteria are determined by nominal group technique (NGT) and then the most appropriate PDS is selected. At the end of the study, Crot, an open source PDS, is determined and integrated into Moodle. The suggested selection criteria would be useful for other higher education institutions in Turkey and other countries that rely on open software.

Selection of Plagiarism Detection Software and Its Integration Into Moodle for Universities

2018 ◽  
pp. 239-258
Author(s):  
Mehmet Bilge Kağan Önaçan ◽  
Mesut Uluağ ◽  
Tolga Önel ◽  
Tunç Durmuş Medeni
Keyword(s):  
Higher Education ◽  
Open Source ◽  
Selection Criteria ◽  
Nominal Group Technique ◽  
Education Institution ◽  
Nominal Group ◽  
Plagiarism Detection ◽  
Software Packages ◽  
Detection Software ◽  
Selection Of

Plagiarism detection software packages have an important role in detection of plagiarism in exams, assignments, projects, and scientific researches. The main goal of this chapter is the selection of plagiarism detection software (PDS) and its integration into Moodle, an open source learning management system (LMS), for the use of a higher education institution. For this reason, first, the selection criteria are determined by nominal group technique (NGT) and then the most appropriate PDS is selected. At the end of the study, Crot, an open source PDS, is determined and integrated into Moodle. The suggested selection criteria would be useful for other higher education institutions in Turkey and other countries that rely on open software.

scholarly journals Preventing Plagiarism and Fostering Academic Integrity: A Practical Approach

2017 ◽  
Vol 5 (3) ◽  
Author(s):  
Nicole Brown ◽  
Rosalind Janssen
Keyword(s):  
Academic Integrity ◽  
Plagiarism Detection ◽  
Formal Evaluation ◽  
Detection Software ◽  
Practical Experiences ◽  
The Individual ◽  
The Impact ◽  
Further Development

Although plagiarism, cheating and academic integrity receive increased attention, literature provides little practical advice or strategies on how to approach these topics with students. In this paper we describe a case study in relation to an intervention we have developed to help our students prevent plagiarism and to foster academic integrity amongst our studentship. In the two hour workshop students are supported in gaining a deeper understanding of what plagiarism is and provides them with practical examples of how plagiarism can be avoided. In the context of the workshop plagiarism is discussed in its many forms of the intentional and unintentional stealing or appropriating of ideas that are not credited accordingly (Helgesson & Eriksson, 2015). The intervention also encompasses discussions around academic integrity and what academic integrity means in theory and in practice. The six steps in our intervention are a sorting activity (what is plagiarism?), the presentation of real cases (what is the impact of plagiarism?), practising to synthesise ideas (how can I prevent plagiarism), the role of plagiarism-detection software such as Turnitin (how can I check for plagiarism?), the formulation of an integrity code and a summary of the content covered in the session (what do I know now?). The intervention draws upon research and practical experiences and is designed in such a way that with adaptations it can be delivered to all levels of students and courses. Following the presentation of the individual elements of the workshop the article concludes with a brief outline of a research project in relation to our workshop, which will be used to inform our further development of the intervention but also to provide a more formal evaluation of its effectiveness.

scholarly journals Effectiveness of Coaching Interventions using Grammarly Software and Plagiarism Detection Software in Reducing Grammatical Errors and Plagiarism of Undergraduate Researches

2013 ◽  
Vol 1 (1) ◽  
Author(s):  
Genaro V. Japos
Keyword(s):  
Academic Integrity ◽  
Academic Discipline ◽  
Pearson Correlation ◽  
Writing Style ◽  
Plagiarism Detection ◽  
Grammatical Errors ◽  
Student Researchers ◽  
Detection Software ◽  
Keywords Education ◽  
The University

Grammar checker and plagiarism software are indispensable tools in aiding researchers to identify and correct their mistakes. The study examined the errors detected by grammarly software and plagiarism software and how these were reduced due to coaching interventions. The study used the descriptive and inferential research design involving 47 specimens of student research as undergraduate theses written as publishable paper. These papers were intended for the Advancing Research Journals by academic discipline available online, cross referenced and indexed.  The study involved a statistical analysis of data derived from software reports tested through the use of t-test and Pearson correlation. The results showed significant reductions in the occurrence of the grammar errors indicating that the coaching interventions were effective. There is also an inverse, moderate and significant correlation between occurrence of grammatical score and plagiarism. The study concludes that those who commit higher incidents of plagiarism also have lower commission of grammatical errors. When students are poor in writing style and vocabulary use, their score for originality increases.  The study recommends for adoption of academic integrity policies to curb grammar and plagiarism occurrences among student researchers in the university. Keywords: Education, Grammar checker, plagiarism detector accumulator, plagiarism detection, coaching, descriptive design, Cagayan de Oro City, Philippines

scholarly journals De-Emphasizing Plagiarism with big data: Modern Approaches and Ethical Considerations

2020 ◽  
Author(s):  
Daniel Dusza
Keyword(s):  
Big Data ◽  
Academic Integrity ◽  
Semantic Network ◽  
Big Data Analytics ◽  
Plagiarism Detection ◽  
Contract Cheating ◽  
Process Verification ◽  
Mass Migration ◽  
Writing Problems ◽  
The Future

This article introduces present trends in Big Data analytics and how they might be implemented to de-emphasize plagiarism. Regrettably, academic institutions have continued to rely on essay-based coursework and written reports as a basis of assessment. As a result of the COVID-19 pandemic, there has been a mass migration into online learning, and with it, a further increase in the reliance on textual content. With more writers now composing online in the absence of face-to-face accountability to peers and teachers, the risks to academic integrity through plagiarism and contract cheating should be expected to increase. Three empirical research studies were used to investigate how the writing process might be automatically and covertly monitored to measure the dynamics of compositions. The areas of interest include the equipment, the method of data management, and the information that could be gleaned from the recorded data. Each study is progressively more complex, and presented in a manner to support the future formulation of a framework for implementation into education. The results indicate that the equipment that is readily available to most students is capable much more than composing and transmitting a written manuscript. Currently, technology is capable of identifying writing problems and providing assistance to help writers navigate even the most difficult tasks in composition. The technological solutions suggested in this paper provides far more than plagiarism detection. The results in this paper indicate that future writing will be supported through process verification, semantic network authentications, and other certifications that will form part of the future requirements of assessment and academic integrity.

Detection and Deterrence of Plagiarism in Online Learning Environments

2011 ◽  
pp. 604-615
Author(s):  
Alan McCord
Keyword(s):  
Online Learning ◽  
Learning Environments ◽  
Academic Integrity ◽  
Plagiarism Detection ◽  
Online Learning Environments ◽  
Student Plagiarism ◽  
Learning Programs ◽  
Detection Software ◽  
Individual Use ◽  
Detection Technologies

Student plagiarism inhibits student learning and damages institutional reputations. Online learning provides different opportunities for student plagiarism than in the traditional classroom, and many observers question whether online learning environments can demonstrate the same level of academic integrity found in traditional classrooms. One method of combating plagiarism is the use of plagiarism detection software, which are licensed for individual use or integrated into an institutional course management system (CMS). Understanding the nature of plagiarism and implementing a plagiarism education and detection program can improve the effectiveness of these tools and therefore improve the quality and reputation of online programs. This article focuses on how plagiarism may be reduced in online learning environments. The article begins with a definition of plagiarism and the characteristics of online learning environments that make them vulnerable to student plagiarism. A review of plagiarism detection technologies and the capabilities of popular detection tools are discussed. The article then addresses how plagiarism detection software can be systematically implemented in support of online learning programs: establishing academic integrity policies, improving the design of assignments and assessments, and establishing effective education programs. The article concludes by exploring future developments in online learning environments and plagiarism detection technologies.

Plagiatserkennungssoftware in der Praxis: Ein erster Erfahrungsbericht / Plagiarism detection software in practice: A first experience report / Logiciel de détection de plagiat dans la pratique: Un premier examen

2014 ◽  
Vol 65 (1) ◽  
Author(s):  
Sabrina Mayer ◽  
Stefan Röhle
Keyword(s):  
Experience Report ◽  
Plagiarism Detection ◽  
Detection Software

Laut FAIRUSE-Studie, die von Soziologen der Universität Bielefeld und der Universität Würzburg im Auftrag des Bundesbildungsministeriums für Bildung und Forschung (BMBF) durchgeführt wurde, gibt beinahe jeder fünfte Studierende zu, mindestens einmal in den letzten sechs Monaten plagiiert zu haben. Die im Rahmen der Studie erhobenen Zahlen sind besorgniserregend und wecken das Bedürfnis nach technischen Möglichkeiten, um Plagiate und Fälschungen leichter aufzuspüren. Im Interview mit dem an der Universitätsbibliothek Mainz angesiedelten Projekt „Akademische Integrität“ erklären Stefan Röhle vom Zentrum für Datenverarbeitung (ZDV) der Johannes Gutenberg-Universität Mainz und Sabrina Mayer vom Institut für Politikwissenschaft an der Johannes Gutenberg-Universität Mainz (JGU), welche technologiebasierten Maßnahmen dort zum Einsatz kommen, um Plagiate aufzuspüren und wie sie zu bewerten sind.

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