The threat to the integrity of educational assessments is no longer from ‘essay mills’ and contract cheating but from Artificial Intelligence (AI).
It is not so long ago that academics complained that essay mills, ‘contract cheating’ services, and commercial companies piecing together ‘bespoke’ answers to standard essay questions, were undermining the integration of higher education’s assessment processes. The outputs of these less than ethically justifiable endeavours tried to cheat the plagiarism detection software (such as Turnitin and Urkund) that so many institutions have come to rely on. This reliance, in part the result of the increase in the student-tutor ratio, the use of adjunct markers and poor assessment design, worked for a while. It no longer works particularly well.
If you are interested in reviewing your programme or institutional assessment strategy and approaches please get in touch. This consultancy service can be done remotely. Contact me
Many institutions sighed with relief when governments began outlawing these commercial operations (in April 2022 the UK passed the ‘Skills and Post-16 Education Act 2022’ following NZ and Australian examples) and went back to the business-as-usual. For the less enlightened this meant a return to setting generic questions, decontextualised, knowledge recitation essay tasks. Some have learnt to at least require a degree of contextualisation of their students’ work, introduced internal self-justification and self-referencing, requiring ‘both sides’ arguments rather than declared positions, and applied the ‘could this already have been written’ test in advance. Banning essay mills, or ‘contract cheating’, is necessary, but it is not enough to secure the integrity of assessment regimes.
Why students plagiarise is worthy of its own post, but suffice it to say it varies greatly depending on the student. A very capable student may simply be terrible at time management and fear running out of time or feel the assessment is unworthy of them. Another student may be fearful of their ability to express complex arguments and in pursuit of the best possible grade, plagiarise. Some may simply have not learnt to cite and reference, or to appreciate that rewording someone else’s thoughts without attributing them also constitutes plagiarism. And there is that category of students whose cultural reference point, deference to ‘the words of the master’, make plagiarism conceptually difficult for them to understand.
I remember receiving my most blatant example of plagiarism and academic malpractice back in 2006. A student submitted a piece of work that included 600 words copied wholesale from Wikipedia, complete with internal bookmarks and hyperlinks. I suspect the majority of students are now sufficiently digitally literate not to make that mistake, but how many are also now in a position to do what the essay mills used to do for them, stitch together, paraphrase and redraft existing material using freely available AI text generation tools.
As we encourage our students to search the web for sources, how easy is it for them now to access some of the easily accessible, and often free, online tools? These tools include https://app.inferkit.com/demo which allows you to enter a few sentences and then generate longer texts on the basis of that origin. You can enter merely a title, of at least five words, or a series of sentences into https://smodin.io/writer and have it generate a short essay, free of references. Professional writing tools aimed at marketers, such as https://ai-writer.com, would cost a subscriber to be effective but would allow students to generate passable work. This last tool actually tells you the sources from which its abstractions have been drawn, including academic journals.
You might find it enlightening to take something you have published and put it through one of these tools and evaluate the output.
It is insufficient to ask the student to generate their own question, or even to ask the student to contextualise their own work. Some of the emergent AI tools can take account of the context. There is a need to move away from the majority of long-form text assessments. With the exception of those disciplines where writing more than a thousand words at once is justifiable (journalism, policy studies, and some humanities subjects), there is a need to make assessments as close to real-world experience as possible. It needs to be evidently the product of an individual.
Paraphrasing is a skill. A valuable one in a world where most professions do not lack pure information. The issue is to evaluate the quality of that information and then be able to reduce it to a workable volume.
I’ve worked recently with an institution reviewing its postgraduate politics curriculum. I suggested that rather than try and stop students from ‘cheating’ by paraphrasing learned texts, they should encourage the students to learn what they need to do to enhance the output of these AI tools. Using one of these tools to paraphrase, and essentially re-write, a WHO report for health policy makers made it more readable, it also left out certain details that would be essential for effective policy responses. Knowing how to read the original, use a paraphrasing tool, and being able to explore the deficiencies of its output and correct them, was a useful skill for these students.
We cannot stop the encroachment of these kinds of AI text manipulation tools in higher education, but we can make their contemporary use more meaningful to the student.
If you are interested in reviewing your programme or institutional assessment strategy and approaches please get in touch. This consultancy service can be done remotely. Contact me.
Image was generated by DALL-e