Effectiveness of Software Approaches to Plagiarism Prevention
Numerous workers have reported instances of plagiarism by students at universities to have increased in recent years, positing the increasing causal influence of internet-enabled information ubiquity (Warn, 2006), online essay marketplaces (e.g. Coughlan, 2008), and varied demands on student time (e.g. Postle, 2009). This may, however, represent an artefact of more effective and widely used means of detecting plagiarism being utilised (Hunter, 2012).
Deliberate plagiarism may be the result of students being motivated primarily by a desire to perform well at summative assessments, rather than form a deep level understanding of the subject (Hunter, 2009), however not all plagiarism is a deliberate act of academic dishonesty and may instead reflect poor awareness or implementation of good academic practice.
Software tools designed to detect acts of plagiarism through comparison of student work with other published and unpublished literature have been widely adopted by UK universities and include, amongst others, Turnitin, Copycatch, and Safeguard. For the educator, these solutions have two intended purposes: to detect cases of plagiarism to inform disciplinary procedures, and to discourage students from attempting plagiarism for fear of the consequences of discovery. Some universities make these resources available to students to use prior to the submission of their work, in this case the student may use the software as a means of formative assessment (Hunter, 2012).
Effectiveness at Detecting Plagiarism
Contrary to their popular conception, these tools do not — sensu stricto — detect plagiarism, rather they assess how closely a student’s submission matches to other published and unpublished literature. These tools match words, phrases, sentences and paragraphs and can often detect the substitution of original words with their synonyms. They may, however, not detect a match if the text is sufficiently reworded or present false-positive results with the use of technical terminology, phrases or references and therefore requires the teacher to interpret their output and determine if plagiarism has been committed. As such, these tools are no longer referred to as “plagiarism detection software” and are instead termed “text comparison software” (Hunter, 2012).
Effectiveness at Discouraging Plagiarism
In spite of the presence of these tools, plagiarised work continues to be submitted. This may be due to the student deciding it worth the risk, either because they believe they will not be caught or because the consequences for being caught are equal or preferable to a late or non-submission (Love and Simmons, 1998). It is therefore important for teachers and institutions to provide powerful disincentives through policy. These disincentives may include a mark of zero for the assignment and/or disciplinary action (Hunter, 2012).
Unintentional plagiarism, either due to misunderstandings regarding referencing, paraphrasing or quotations, is rooted in ignorance of academic practice, and as such students submitting this work must be further educated in the standards expected of them.
Effectiveness as Formative Assessment
Some institutions provide students with the facility to check their work with these tools without consequences to their grade, with the intention that this will act as a formative assessment. It is hoped that this will have a positive effect on unintentional plagiarism as it allows students to learn good academic practice from experience of using the tools; encouraging students to think more about the content and rewrite it using their own words, thereby producing higher quality work and reflecting a deep understanding of the subject (Hunter, 2012).
However, allowing students to use these tools presents an opportunity for students intent on committing plagiarism to “tweak” the wording of their work until the software fails to register a match (Hunter, 2012). Hunter (2012) suggest limiting the number of formative submissions in an attempt to prevent this behaviour.
Conclusion
Text comparison software is a useful tool but its effectiveness varies depending on its intended use and how it is utilised. Their ability to detect plagiarism would be enhanced by not granting students access to it, thereby preventing them plagiarising in a way not detected by the system. However, students would therefore be unable to check for unintentional plagiarism and be denied this opportunity to learn good academic practice. This would likely result in an increase in accidentally plagiarised work. It may be argued that it is unfair to inflict strict punitive measures on the grounds of an accident or ignorance, however any punitive action must be sufficient to deter deliberate plagiarism.
It is therefore the role of the institution to find a balance between these three, partially competing, uses of text-comparison software. Such a balance must be consistent across the institution and should, where possible, be of benefit to the education of the student, as is the ultimate objective of the institution.
Hunter, Arlene (2009). Enabling students to proactively evaluate, test and adapt the effectiveness of their learning through interactive online formative assessment. In: SOLSTICE Centre for Excellence in Teaching & Learning , 4th International Conference, 04 Jun 2009, Edge Hill, UK.
Hunter, A.G. 2012. ‘ Text comparison software for students ’: an educational development tool or quick ‘ text checker ’ — examining student use and perceptions of value Software detection solutions In: IIP Conference, July 2012.
Love, P.G. and Simmons, J. (1998) ‘Factors influencing cheating and plagiarism among graduate students in a college of education’, College Student Journal, 32:4, pp.539-551
Postle, K. (2009) ‘Detecting and deterring plagiarism in social work students: implications for learning for practice’, Social Work Education, 28: 4, pp.351-362
Warn, J. (2006) ‘Plagiarism software: no magic bullet!’, Higher Education Research & Development, 25:2, pp.195-208
Effectiveness of Software Approaches to Plagiarism Prevention
Numerous workers have reported instances of plagiarism by students at universities to have increased in recent years, positing the increasing causal influence of internet-enabled information ubiquity (Warn, 2006), online essay marketplaces (e.g. Coughlan, 2008), and varied demands on student time (e.g. Postle, 2009). This may, however, represent an artefact of more effective and widely used means of detecting plagiarism being utilised (Hunter, 2012).Deliberate plagiarism may be the result of students being motivated primarily by a desire to perform well at summative assessments, rather than form a deep level understanding of the subject (Hunter, 2009), however not all plagiarism is a deliberate act of academic dishonesty and may instead reflect poor awareness or implementation of good academic practice.
Software tools designed to detect acts of plagiarism through comparison of student work with other published and unpublished literature have been widely adopted by UK universities and include, amongst others, Turnitin, Copycatch, and Safeguard. For the educator, these solutions have two intended purposes: to detect cases of plagiarism to inform disciplinary procedures, and to discourage students from attempting plagiarism for fear of the consequences of discovery. Some universities make these resources available to students to use prior to the submission of their work, in this case the student may use the software as a means of formative assessment (Hunter, 2012).
Effectiveness at Detecting Plagiarism
Contrary to their popular conception, these tools do not — sensu stricto — detect plagiarism, rather they assess how closely a student’s submission matches to other published and unpublished literature. These tools match words, phrases, sentences and paragraphs and can often detect the substitution of original words with their synonyms. They may, however, not detect a match if the text is sufficiently reworded or present false-positive results with the use of technical terminology, phrases or references and therefore requires the teacher to interpret their output and determine if plagiarism has been committed. As such, these tools are no longer referred to as “plagiarism detection software” and are instead termed “text comparison software” (Hunter, 2012).Effectiveness at Discouraging Plagiarism
In spite of the presence of these tools, plagiarised work continues to be submitted. This may be due to the student deciding it worth the risk, either because they believe they will not be caught or because the consequences for being caught are equal or preferable to a late or non-submission (Love and Simmons, 1998). It is therefore important for teachers and institutions to provide powerful disincentives through policy. These disincentives may include a mark of zero for the assignment and/or disciplinary action (Hunter, 2012).Unintentional plagiarism, either due to misunderstandings regarding referencing, paraphrasing or quotations, is rooted in ignorance of academic practice, and as such students submitting this work must be further educated in the standards expected of them.
Effectiveness as Formative Assessment
Some institutions provide students with the facility to check their work with these tools without consequences to their grade, with the intention that this will act as a formative assessment. It is hoped that this will have a positive effect on unintentional plagiarism as it allows students to learn good academic practice from experience of using the tools; encouraging students to think more about the content and rewrite it using their own words, thereby producing higher quality work and reflecting a deep understanding of the subject (Hunter, 2012).However, allowing students to use these tools presents an opportunity for students intent on committing plagiarism to “tweak” the wording of their work until the software fails to register a match (Hunter, 2012). Hunter (2012) suggest limiting the number of formative submissions in an attempt to prevent this behaviour.
Conclusion
Text comparison software is a useful tool but its effectiveness varies depending on its intended use and how it is utilised. Their ability to detect plagiarism would be enhanced by not granting students access to it, thereby preventing them plagiarising in a way not detected by the system. However, students would therefore be unable to check for unintentional plagiarism and be denied this opportunity to learn good academic practice. This would likely result in an increase in accidentally plagiarised work. It may be argued that it is unfair to inflict strict punitive measures on the grounds of an accident or ignorance, however any punitive action must be sufficient to deter deliberate plagiarism.It is therefore the role of the institution to find a balance between these three, partially competing, uses of text-comparison software. Such a balance must be consistent across the institution and should, where possible, be of benefit to the education of the student, as is the ultimate objective of the institution.
References