Academic Misconduct

Academic Misconduct Appeal Form 2023-24

Academic Misconduct Request for a Review Form 2023-24

 

Academic Misconduct Allegation Appeal Form 2022-23

Academic Misconduct Allegation Request for Review Form 2022-23

For a better understanding of the University's approach to Academic standards in assessments, please see Academic Integrity guidance. 

Generative Artificial Intelligence (AI) Apps offer students many opportunities to support their learning or work creatively, but over-reliance on these tools could lead to poor academic practice or academic misconduct. 

London Metropolitan University is aware of the high-profile discussions and debates about the use of Artificial Intelligence Apps to produce text images and other content. The University helps its students to produce their own work with confidence in many ways, including support with understanding assessments, research, academic writing and referencing. This includes navigating the use of new and emerging AI technologies. Our approach to AI is to engage with and adapt to these new technologies, with a focus on appropriate and responsible use. 

The University’s principles are outlined below. 

1. We permit the appropriate and responsible use of Generative AI applications by our students.

2. We recognise that generative AI applications can be useful tools in specific aspects of learning, including:

• assisting in the structuring or organising existing work. 

• getting inspiration / overcoming 'writer's block'. 

• spelling and grammar checks. 

• supporting international students with language challenges. 

• aiding students with specific learning requirements. 

• creating prompts for image making. 

• creative image making and media production. 

• producing quick summaries / synopses of large documents 

• other subject specific tasks such as debugging code.

3. We are committed to engaging with generative AI within the context of our wider commitment to equity and social justice (through our ESJF (Education for Social Justice Framework). We will work with students to understand the biases that may be perpetuated by AI and to minimise any inequities in access and usage.

4. Course and module content at London Metropolitan University will be regularly reviewed to ensure the exploration and understanding of emerging technologies, including AI, within specific sectors. We will encourage staff and students to actively participate in sector-wide debates and discussions on emerging issues related to Generative AI and other emerging technologies.

5. We will ensure and maintain fairness in assessment while accommodating our students' access to and innovation with emerging technologies. This will include the use of varied and creative assessments, the active use of version histories where relevant, critical, and creative engagement with AI in class including to explain its unreliability and a focus on subject specific implications within the curriculum.

6. We will support students in their Generative AI literacy within wider learning skills development, assessment literacy, information literacy, digital literacy, and awareness of academic misconduct.

7. London Metropolitan University Students will be expected, when required, to document or reference their use of Generative AI for assessment submissions.

8. We will collaborate with employers, employer networks, Professional Statutory Regulatory Bodies (PSRBs) and other professional organisations to ensure our courses prepare students for the changing recruitment and workplace environment, where AI will be a part of everyday life.

9. The University commits to engage with the broader legal, ethical, and philosophical issues surrounding the use of Generative AI in teaching and learning contexts and other relevant student facing spaces.

10. The University will provide its staff with appropriate training, development, support, and resources to engage with Generative AI, and related issues including Academic Misconduct.

For general guidance about the use of Generative AI in your studies, Visit London Metropolitan University's AI Guide on Library Guides.   

For guidance related to your subject speak to your course leader or any member of the teaching staff.

Essay Mills are services that facilitate commissioning and contract cheating. This type of academic misconduct when another person completes your assessment or your work, which is then submitted as your own. It can be hard to spot that these services are not legitimate, often uses terms such as 'proof-reading' or advertising themselves as academic support. 

It is now a crime to give, or arrange for another person to provide contract cheating services for financial gain to University students in the UK. Therefore, it is worth noting the dangers of using these services:

• You do not benefit personally or develop by relying on such services and if found out, you could be reported for Academic Misconduct. It does not matter if this is after your degree is awarded. If it has been found on the balance of probabilities that these services have been used to complete an item of assessment, you could have your award taken away after it has been completed.
• You could be at risk of blackmail. Not only could the service inform the University or your employers if you do not pay them money, but they may also not produce the work that you have paid for. 
• If found to be facilitating these services or supporting them by advertising them to other students you could be at risk of a Major Misconduct report through our Student Conduct procedures and risk losing your place at University. 

It is your responsibility as a student to ensure that you act with academic integrity. If you fail to meet the requirements of academic integrity, this is considered academic misconduct.  So if you plagiarise, cheat or do anything that attempts to gain an unfair academic advantage, or you assist others to do so, you are committing the offence of academic misconduct. However, there is support available for students through our Library Study Skills Guides to support you with this. These guides provide guidance on what constitutes plagiarism, how to avoid it, and how to reference correctly.