It is suggested that you add this link to the 'How to engage with this unit on Canvas' page of the Canvas template. You may additionally want to include the link in your weekly content pages if this seems appropriate. Programme teams are encouraged to standardise where lectures are linked to across the different units of a programme.

Canvas also has a wide range of videos on different features in their video library. Please note that not all features will be available to us as some appear to depend on institutional subscription levels.

• Arrange peer-review / exchanges between CUDs (e.g. pair up CUDs for level 1 units to review each other's approach to Canvas)

• Host a subject show-and-tell session where colleagues might share an aspect of Canvas they've tried out - focussing on what did and didn't work

  
  

If teaching staff set up their own Cadmus inboxes, please liaise with the AMP team above to ensure that 1/ assessment groups can be set up if needed, 2/ the settings for the assessment are correct.

• Student-facing site, with a link to Canvas's own student-facing video library

• There will be drop-in sessions for technical fixes across the four School hubs (students can go to any of the session, they don't need to go the one for their own School):

  • Drop-ins with elearning (with IAG presence) across Humanities Hubs (held once a week across Oct):

  • SOSS Hub - 7th October - 10-1pm

  • AMBS Hub - 16th October - 1pm - 4pm

  • SALC Hub - 21st October - 10-1pm

  • SEED Hub - 30th October - 1pm -4pm

Question on integrating Cadmus with Manchester systems

Book a 1-on-1  with the eLearning Team

Detailed design support

If you want to arrange a 1-to-1 design consultation with a team member from Cadmus email cara.berger@manchester.ac.uk and I can put you in touch with them.

• Stress test assessments: Use AI tools to produce an exemplar response to your assignment brief. Consider how much and what kind of prompting it takes to create work that is passable. Track what kind of ethical grey areas arise in this process. Use the stress testing exercise as a starting point for discussing what variously constitutes good practice, poor practice and malpractice in relation to your assignment.

• Map GenAI outputs against Grade Descriptors: Take a core essay question or assignment brief from your programme. Generate a response using a common AI tool with a relatively simple prompt. Analyse the AI-generated text against the Grade Descriptors in hour unit. Identify its strengths (e.g., coherent structure, clear prose) and, more importantly, its weaknesses. Does it lack a critical voice? Does it fail to engage with specific scholarly sources from the reading list? When it uses sources, does it only do so superficially? If it uses direct quotations, are these real or ‘hallucinated’? The findings can be used to create guidance for students on what constitutes high-quality work within the Grade Descriptors.

• Diversify assessment tasks: Consider exploring assessment formats that are inherently less susceptible to uncritical AI use because they reward authentic student engagement. The goal is to design tasks that evaluate skills beyond automated text production, such as critical thinking in real-time, personal reflection, or embodied practice. By diversifying the forms of assessment, you can more effectively measure learning outcomes that AI cannot easily replicate. Examples of such assessment tasks include:

  • In-person or 'live' assessments: Formats such as oral exams (vivas), in-class debates, observed practical exercises, or authentic assessment tasks. These methods assess a student's ability to articulate, apply, and defend their understanding dynamically and in a specific context.

  • Context-specific and reflective assessments: Tasks that require students to connect course concepts to their own experiences, a specific seminar discussion, or a local event. These rely on unique, individualised contexts that GenAI cannot access or authentically reproduce since they aren’t part of its training data.

These suggestions have been generated in part by drawing on guidance developed in SEED and SOSS.

LinkedIn Learning (which all staff have free access to) also has a lot of training course on AI that will give you a basic understanding of the technology and how it is used. For example:

• What is Generative AI? by Pinar Demirdag (very informative, despite the uncritically technofuturist tone)

• Various AI courses by Jules White (gives simple, concrete examples of how to use GenAI in everyday tasks, and how to create good prompts)

• TLSE Sharepoint page (for staff)

• SALC student community page (for students)

• Humanities Canvas Microsite which includes:

  • How-to Guides

  • Canvas Go! Training modules

  • Example Course Templates

• If you need detailed design support for a Canvas page you can book a 1-on-1  with the eLearning Team

• If you need technical help (e.g. a missing unit, unsuccessful migration), log an IT ticket on Connect

• For eLearning questions beyond Canvas, explore the Humanities Teaching Academy Resources

If your problem seems structural, i.e. colleagues in other subjects might benefit from an answer - please email cara.berger@manchester.ac.uk for your query to be added.

You can find this in the Adopting Canvas FAQ item.