Plagiarism is a serious offence, which the University wishes actively to identify and prevent. Measures have been put in place to help students to recognise and avoid plagiarism in their own work

Turnitin

The University makes use of a national plagiarism detection service known as ‘Turnitin’ that allows it to check any piece of work for plagiarism before it is marked. It is therefore necessary for students to provide an electronic copy of some or all of the work which they submit for assessment to be uploaded into the detection facility.

There it will be stored indefinitely in a database and compared against the world wide web and extensive databases of reference material, including work submitted by other students from this and other UK institutions using the service. For the purposes of identifying and preventing plagiarism, the University may therefore share the work you submit for assessment with third parties, including other UK institutions if so requested.

Students may ask for their work and personal data to be removed from the service after it has been checked for plagiarism by contacting Judy Cohen at turnitin-help@kent.ac.uk. You need to follow existing University procedures for removing personal data from the University’s systems (including the VLE and any assignments including Turnitin which exist within Moodle).

Avoiding plagiarism

For information on plagiarism and the correct way to quote material, students should consult their course tutor and the Academic Integrity guide published here 

Annex 10 of the Credit Framework: Academic discipline: Procedures contains a definition of plagiarism and explains the process which will follow if plagiarism is suspected in your work. Further advice is available from Kent Union

The Library provides reference management software to help you to create, store and re-use bibliographical information for use in essays and dissertations. 

Storing of personal data

There is a FAQ page on the Academic Integrity site with further information on the storing of personal data.

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