scholarly journals Student and staff perceptions of the effectiveness of plagiarism detection software

2008 ◽  
Vol 24 (2) ◽  
Author(s):  
Doug Atkinson ◽  
Sue Yeoh
Keyword(s):  
Business School ◽  
Academic Misconduct ◽  
Teaching Staff ◽  
Survey Questionnaire ◽  
Research Model ◽  
Plagiarism Detection ◽  
Staff Perceptions ◽  
Mixed Methods Approach ◽  
University Of Technology ◽  
Detection Software

<span>The aim of this research was to determine student and staff perceptions of the effectiveness of plagiarism detection software. A mixed methods approach was undertaken, using a research model adapted from the literature. Eight hours of interviews were conducted with six students and six teaching staff from Curtin Business School at Curtin University of Technology, which had trialled the plagiarism detection software, </span><em>EVE2</em><span>. A survey questionnaire was completed by 171 students involved in the trial. The summary indication was that students perceived that plagiarism is an important issue; detection software makes it easier for lecturers; it is fair to use detection software; students support its use; and it will have some effect in preventing plagiarism. However, students' concerns included being caught for unintentional plagiarism, teaching staff placing too much emphasis on detection results above student ability, and the accuracy of the software at detecting plagiarism. Concerns for teaching staff included the time taken for the detection process, limitation of the software to publicly based Internet sources and direct copying, and the extra workload involved with pursuing academic misconduct.</span>

Academic Misconduct and the Internet

2017 ◽  
pp. 82-111 ◽  
Author(s):  
David Ison
Keyword(s):  
Best Practices ◽  
Empirical Studies ◽  
Negative Influence ◽  
Academic Misconduct ◽  
Study Data ◽  
Future Research ◽  
The Internet ◽  
Plagiarism Detection ◽  
Subsequent Section ◽  
Detection Software

This chapter provides a general background on the problem of plagiarism, how the Internet has been implicated as a negative influence on Academic Integrity (AI), empirical study data on the influences of the Internet on plagiarism, reasons why students may conduct plagiarism, and best practices in the use of plagiarism detection. Within the first section, three empirical studies are highlighted to indicate the actual occurrence of plagiarism in graduate education and the role the Internet may play in influencing AI. In the second section, a description of both how and why students conduct plagiarism is presented. Existing literature on the topic is explored to better inform stakeholders on the ‘why' component with suggestions for potential mitigating solutions. The subsequent section describes plagiarism detection software that is commonly in use across the globe including best practices on how to interpret detection results. Lastly, recommendations and calls for future research are provided.

scholarly journals Ethical ambiguity in the academic periphery: Global versus local science in explaining plagiarism

2021 ◽  
Author(s):  
Katerina Guba ◽  
Angelika Tsivinskaya
Keyword(s):  
Academic Discipline ◽  
Empirical Studies ◽  
Academic Misconduct ◽  
Lower Percentage ◽  
Plagiarism Detection ◽  
The Past ◽  
Research Fields ◽  
Average Share ◽  
Detection Software ◽  
Doctoral Dissertations

The past decade has seen extensive research carried out on the systematic causes of academic misconduct. Simultaneously, less attention has been paid to the variation in academic pathologies between research fields, as most empirical studies focus on one particular discipline. We propose that academic discipline is one of several systematic factors that might contribute to academic misbehavior. Drawing on a neo-institutional approach, we argue that on the academic periphery, the norm of textual originality has not drawn equal support across different research fields depending on its level of internationalization. Using plagiarism detection software, we analyzed 2,405 doctoral dissertations randomly selected from all dissertations defended in Russia between 2006 and 2016. We measured the globalization of each academic discipline by calculating the share of publications indexed in the global citation database in relation to overall output. Our results showed that, with an average share of detected borrowings of over 19%, the incidence of plagiarism on the academic periphery is remarkably higher than in Western countries. Overall, disciplines closely follow the pattern of higher globalization associated with a lower percentage of borrowed text. We also found that unauthorized borrowing is less prevalent at research-oriented institutions supporting global ethical standards. Our findings suggest that it might be misleading to measure the prevalence of academic misconduct on the academic periphery without paying attention to variations at the disciplinary level.

Academic Misconduct and the Internet

2019 ◽  
pp. 22-51
Author(s):  
David Ison
Keyword(s):  
Best Practices ◽  
Empirical Studies ◽  
Negative Influence ◽  
Academic Misconduct ◽  
Study Data ◽  
Future Research ◽  
The Internet ◽  
Plagiarism Detection ◽  
Subsequent Section ◽  
Detection Software

This chapter provides a general background on the problem of plagiarism, how the Internet has been implicated as a negative influence on Academic Integrity (AI), empirical study data on the influences of the Internet on plagiarism, reasons why students may conduct plagiarism, and best practices in the use of plagiarism detection. Within the first section, three empirical studies are highlighted to indicate the actual occurrence of plagiarism in graduate education and the role the Internet may play in influencing AI. In the second section, a description of both how and why students conduct plagiarism is presented. Existing literature on the topic is explored to better inform stakeholders on the ‘why' component with suggestions for potential mitigating solutions. The subsequent section describes plagiarism detection software that is commonly in use across the globe including best practices on how to interpret detection results. Lastly, recommendations and calls for future research are provided.

scholarly journals A UK institution's university-wide approach to plagiarism:

2006 ◽  
Vol 2 (1) ◽  
Author(s):  
Christina Mainka ◽  
Scott Raeburn ◽  
Shirley Earl
Keyword(s):  
Role Model ◽  
Action Plan ◽  
Good Practice ◽  
Student Support ◽  
Academic Misconduct ◽  
Plagiarism Detection ◽  
Record Keeping ◽  
Support Materials ◽  
Detection Software ◽  
The University

Research and consultations in session 2003/2004 by a University's Plagiarism Working Group uncovered a poor understanding of plagiarism and inconsistent handling procedures throughout its schools. In an effort to address both these issues, a strategic 2-year Action Plan was developed and rolled out beginning the following academic year in order to improve student support, staff awareness and more consistent practice overall. The plan included a pilot using the detection software service, Turnitin'UK, with five of the University's 14 schools. The pilot was only one of a series of university-wide deliberations, others included the revision and piloting of a University Plagiarism Code of Practice, implementation of school-based academic conduct officers, improved staff development opportunities and student support materials and events. One school in the University has served as a role model of good practice throughout. Noteworthy is the school's record keeping practice since session 2001/02 of incidences of plagiarism and other academic misconduct. In the paper we present the factors such as gender, nationality and level of study that have been found linked to the incidences of plagiarism in the school. Additionally, the role plagiarism detection software plays in addressing plagiarism is explored within the collaborative and holistic approach of the Action Plan. Finally, the challenges and resistance faced by key players throughout the implementation of the first phase of the Action Plan at the University are considered and the commitment to continuous enhancement recognised.

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.

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.

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