Currently viewing the tag: "AI"

With an overload of information and such dichotomous opinions about Artificial Intelligence (AI), it is difficult to know where to begin; especially if you are yet to experience using AI at all. One starting point is to find out where you are with your own knowledge and the Jisc discovery tool can assist with this.

The discovery tool, which was introduced to UON in 2020, is a developmental tool that students and staff can use to self-assess their digital capabilities, identify their strengths, and highlight opportunities to develop skills. The tool has been recently updated to include a question set for both staff and students on their capability and proficiency with AI and generative AI tools.

The question sets for students and staff have been developed with assistance from Jisc and aligns with the latest AI advice and AI guiding principles developed by Jisc and the Russell Group on the responsible and equitable use of AI to enhance learning and teaching.

How the discovery tool helps students and teachers

The new question sets provide users with a basis to self-assess their skills and knowledge of what AI is and how it could, or should, be used in the context of their studies or role.

An image of a wheel that is divided into sections to show a users confidence level with different areas of the question set.
Example of the AI Question set report wheel

Once users complete the question set, they can then access a personalised report with a confidence rating which will vary from ‘developing’ through ‘capable’ to ‘proficient’ depending on their experience. The report also provides recommendations and courses on how to advance knowledge around AI.

Images to show a sample of the resources that are available once the report has been generated
A sample of the resources that are available once the report has been generated

Users can repeat any of the discovery tool’s question sets at any point and therefore keep a dynamic view of their confidence levels.

Where can I access the tool?

Click here to log straight into the discovery tool and the AI question set, or copy and paste the link below into your address bar.

How can I Support Students?

To assist students in enhancing their digital skills and their knowledge and understanding of AI, we have put together a student guide which can be found here. It may also be helpful to add a link to this guide, or to the discovery tool itself, within NILE courses.

What if I would like to know more?

For more information about how to use the discovery tool, see:

For further information about the AI design assistant in NILE or Padlet’s new AI features, please get in touch with your Learning Technologist. 

Helpful links

Who is my Learning Technologist?

Learning Technology Lib Guides

The new features in Blackboard’s April upgrade will be available on Friday 5th April. This month’s upgrade includes the following new/improved features to Ultra courses:

Anonymous discussions

Following feedback from staff, April’s upgrade will allow staff to set up Ultra discussions to allow students to post and reply to posts anonymously. After the upgrade, the option to allow anonymous responses and replied will be available in the ‘Discussion Settings’ panel.

• Discussion settings with ‘Allow anonymous responses and replies’ highlighted

Please note that selecting ‘Allow anonymous responses and replies’ does not mean that all replies and reponses will be anonymous; rather it means that students and staff can choose to post anonymously if they want to. To post anonymously, the ‘Post anonymously’ checkbox will need to be selected. Once posted, the anonymity of a post cannot be changed – i.e., an anonymous post cannot be de-anonymised by the person who posted it, and a non-anonymous post cannot be changed to anonymous.

• Discussion post prior to posting with ‘Post anonymously’ selected

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AI Design Assistant: Select course items/context picker enhancements

Following last month’s upgrade which introduced the context picker (the ‘Select course items’ tool) for auto-generated test questions, April’s upgrade introduces the option to select course items when auto-generating learning modules, assignments, and discussion and journal prompts.

The purpose of the ‘Select course items’ tool is to allow staff to specify exactly which resources should be used when auto-generating content. If ‘Select course items’ is used, the auto-generated content will be based only upon the items selected. Where no course items are selected, auto-generated content will be based upon the course title.

• AI Design Assistant tool with ‘Select course items’ (context picker) highlighted

You can find out more about the AI Design Assistant and how to use it it at: Learning Technology Team: AI Design Assistant

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Duplicate test/form question option, plus change to default test question value

The April upgrade introduces the ability for staff to duplicate test and form questions. Additionally, following the upgrade the default point value for newly created test questions will be changed from 10 points to 1 point.

• Test question with ‘Duplicate’ option selected

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Likert form questions includes options for 4 and 6, as well as 3, 5, and 7

The February 2024 upgrade introduced the ‘Forms’ tool to Ultra courses. One of the question types available in forms is a Likert question; however, the original release only included options for staff to select Likert scales with 3, 5, or 7 points. April’s upgrade will add options to choose scales with 4 or 6 points.

• Form with Likert question and scale range selected

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More information

As ever, please get in touch with your learning technologist if you would like any more information about the new features available in this month’s upgrade: Who is my learning technologist?

Click to view interview with Anne-Marie Langford, UON Learning Development tutor on uses of GenAI

In this short video UON Learning Development tutor Anne-Marie Langford discusses her work employing generative AI to produce sample passages of academic writing for analysis and refinement in development workshops.

Anne-Marie notes that the use of AI-generated text can prompt students to critique academic writing, encouraging them to develop higher order thinking skills. This proves particularly valuable in scrutinising shortcomings in generative AI-generated text which can prove useful in identifying and presenting knowledge but are less adept and applying, analysing and evaluating it.

While recognising the time-saving potential of chatbots such as ChatGPT and their uses in enhancing student learning, she underscores the limitations of GAI in academic writing and referencing. Anne-Marie emphasises the importance of students adopting a critical, ethical and well-informed approach to using generative AI, urging them to cultivate their own critical voices and refine their skills.

By incorporating text from generative tools into her sessions, Anne-Marie exemplifies the advantages of modelling critical use of generative AI with students.

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Click to view video - Fashion GAI
Click to view this video case study in a new tab

This short film features three BA Fashion, Textiles, Footwear & Accessories students discussing their experiences using Generative AI (GAI) in their projects. The students demonstrate diverse applications of GAI, highlighting how they tailor the technology to their individual creative needs.

The film features Subject Head Jane Mills, who discusses the potential of AI to support students, and outlines the introduction of a new AI logbook – designed to provide a framework for students to confidently explore and utilize GAI for brainstorming and research purposes.

Click to view David Meechan’s abridged talk from the Vulcan Sessions on 26/01/24.

In this condensed talk from the Vulcan Sessions on 26/01/24, Senior Lecturer in Education David Meechan discusses the opportunities and considerations of using AI in education.

Introducing the concept of Generative Artificial Intelligence (GAI) as a diverse and constantly evolving field without a consistent definition among scholars. He shares personal examples of how GAI can help support students by scaffolding their learning and reducing the initial cognitive load through the creation of basic first drafts.

David expresses, ‘I’m a big believer in experiential learning, providing children, and now students, with experiences they can build on.’ Therefore, he advocates for the use of GenAI tools, which offer ‘varied, specific, and potentially creative results, revolutionising education and supporting lifelong learning.’

Emphasising the importance of the ethical use AI tools in education, he argues for engagement with a wide range of GenAI tools to prepare students for navigating future changes in the education and technological landscape.

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Jane Mills talk at Vulcan Sessions (abridged) 5 mins - Click to view.
Click to view of Jane Mill’s abridged talk from the Vulcan Sessions on 26/01/24.

In this short film Jane Mills delves into the realm of text-to-image Generative AI models, experimenting with platforms such as Stable Diffusion and Midjourney. Initially encountering what she described as “odd and distorted” images, she highlights the evolving landscape of Generative AI images during this period.

“In 2023 the images started to look better,” Jane explains, noting a significant breakthrough as these AI models began capturing intricate details, showcasing her expertise as a fashion specialist, particularly in facial features, colour pallets, fabric textures and embellishments.

By May 2023, AI integration became a reality in the discipline of Fashion teaching. Jane champions the fusion of human creativity with machine efficiency, enabling designers to conceptualise runway shots, intricate patterns, and expressive collages.

Highlighting the importance of designing detailed prompts, Jane illustrates how specifying techniques, mediums, and styles could lead to incredible results, ranging from watercolor cityscapes to photorealistic textures.

Generative AI serves as a powerful tool that provides fresh perspectives, preparing students for the ever-evolving fashion industry. This approach facilitates faster design processes, hones skills, and meets industry demands.

“It’s an assistive tool, a collaborator that empowers human imagination. As students gain valuable experience using this transformative technology, they’re not just designing the future of fashion; they’re shaping the way we think about its creation,” she emphasised.

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Play AI
Click to view this case study video – link opens in new tab.

In this short film, Theatre Director Matt Bond delves into the intricacies of his pioneering theater experiment, “PlayAI,” a collaborative venture with the AI tool ChatGPT.

Building on the success of his groundbreaking work at Riverside Studios in London in April 2023, this project challenges the traditional boundaries of playwriting by immersing itself in the realms of exploration and experimentation with Artificial Intelligence.

Over a transformative four-week period, Bond collaboratively engaged with UON BA Acting students to craft a new play that delves into profound themes. These themes encompass the nuanced emotions surrounding redundancy and belonging in the age of Artificial Intelligence, the complexities of forging relationships with digital avatars, and the conflicting dynamics between idealism and capitalism within a futuristic digital ‘metaverse’ society.

The film provides valuable insights as four BA acting students share their perspectives on how they have embraced AI technology as a powerful catalyst for innovation and exploration.

Moreover, the impact of the project transcends the realm of performance. It becomes evident that the students, in their exploration of key AI concepts, have not only expanded their digital literacies but have also delved into the ethical boundaries of AI. Their involvement reflects a meticulous and comprehensive approach to working with AI, showcasing a profound commitment to understanding and navigating the intricate facets of this transformative technology.

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The new features in Blackboard’s January upgrade will be available between Friday 5th and Monday 8th January. The January upgrade includes the following new/improved features to Ultra courses:

AI Design Assistant: Authentic assessment prompt generation

Currently, staff are able to auto-generate prompts for Ultra discussions and journals. The January upgrade will add the ability to auto-generate prompts for Ultra assignments too. Following the upgrade, when setting up an Ultra assignment, staff will see the ‘Auto-generate assignment’ option in the top right-hand corner of the screen.

• Ultra assignment with ‘Auto-generate assignment’

Selecting ‘Auto-generate assignment’ will generate three prompts which staff can refine by adding additional context in description field, selecting the desired cognitive level and complexity, and then re-generating the prompts.

• Auto-generated assignment prompts

Once selected and added, the prompt can then be manually edited by staff prior to releasing the assignment to students.

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AI Design Assistant: Generate rubric Improvements

Following feedback from users, the January upgrade will improve auto-generated rubrics. The initial version of the AI Design Assistant’s auto-generated rubrics did not handle column and row labels properly, and this will be improved in the January upgrade. Also improved in the January upgrade will be the distribution of percentages/points across the criteria, which were inconsistently applied in the initial release.

• An auto-generated rubric

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Total & weighted calculations in the Ultra gradebook

The Ultra gradebook currently allows for the creation of calculated columns using the ‘Add Calculation’ feature. However, the functionality of these calculated columns makes the creation of weighted calculations difficult, e.g., when generating the total score for two pieces of work where one is worth 60% of the mark and the other 40%. At present, this would have to be done in a calculated column by using the formula AS1 x 0.6 + AS2 x 0.4, like so:

• Using the ‘Add Calculation’ option in the Ultra gradebook to generate an overall grade for two pieces of work weighted at 60% and 40%

However, weighting problems can be further compounded if the pieces of work are not all out of 100 points, which can often be the case when using computer-marked tests. Following feedback about this issue, the January upgrade will bring in an ‘Add Total Calculation’ option, which will allow staff to more easily generate an overall score for assessments with multiple sub-components. The new ‘Add Total Calculation’ column will simply require staff to choose the assessments which are to be used in the calculation, and specify how they are to be weighted. Using the same example as above, the calculation would look like so:

• Using the ‘Add Total Calculation’ option in the Ultra gradebook to generate an overall grade for two pieces of work weighted at 60% and 40%

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More information

To find out more about all of the AI Design Assistant tools available in NILE, full guidance is available at: Learning Technology – AI Design Assistant

And as ever, please get in touch with your learning technologist if you would like any more information about the new features available in this month’s upgrade: Who is my learning technologist?

Dr Cleo Cameron (Senior Lecturer in Criminal Justice)

In this blog post, Dr Cleo Cameron reflects on the AI Design Assistant tool which was introduced into NILE Ultra courses in December 2023. More information about the tool is available here: Learning Technology Website – AI Design Assistant

Course structure tool

I used the guide prepared by the University’s Learning Technology Team (AI Design Assistant) to help me use this new AI functionality in Blackboard Ultra courses. The guide is easy to follow with useful steps and images to help the user make sense of how to deploy the new tools. Pointing out that AI-generated content may not always be factual and will require assessment and evaluation by academic staff before the material is used is an important point, and well made in the guide.

The course structure tool on first use is impressive. I used the key word ‘cybercrime’ and chose four learning modules with ‘topic’ as the heading and selected a high level of complexity. The learning modules topic headings and descriptions were indicative of exactly the material I would include for a short module.

I tried this again for fifteen learning modules (which would be the length of a semester course) and used the description, ‘Cybercrime what is it, how is it investigated, what are the challenges?’ This was less useful, and generated module topics that would not be included on the cybercrime module I deliver, such as ‘Cyber Insurance’ and a repeat of both ‘Cybercrime, laws and legislation’ and ‘Ethical and legal Implications of cybercrimes. So, on a smaller scale, I found it useful to generate ideas, but on a larger semesterised modular scale, unless more description is entered, it does not seem to be quite as beneficial. The auto-generated learning module images for the topic areas are very good for the most part though.

AI & Unsplash images

Once again, I used the very helpful LearnTech guide to use this functionality. To add a course banner, I selected Unsplash and used ‘cybercrime’ as a search term. The Unsplash images were excellent, but the scale was not always great for course banners. The first image I used could not get the sense of a keyboard and padlock, however, the second image I tried was more successful, and it displayed well as the course tile and banner on the course. Again, the tool is easy to use, and has some great content.

• Ultra course with cybercrime course banner

I also tried the AI image generator, using ‘cybercrime’ as a search term/keyword. The first set of images generated were not great and did not seem to bear any relation to the keyword, so I tried generating a second time and this was better. I then used the specific terms ‘cyber fraud’ and ‘cyber-enabled fraud’, and the results were not very good at all – I tried generating three times. I tried the same with ‘romance fraud’, and again, the selection was not indicative of the keywords. The AI generated attempt at romance fraud was better, although the picture definition was not very good.

Test question generation

The LearnTech guide informed the process again, although having used the functionality on the other tools, this was similar. The test question generation tool was very good – I used the term ‘What is cybercrime?’ and selected ‘Inspire me’ for five questions, with the level of complexity set to around 75%. The test that was generated was three matching questions to describe/explain cybercrime terminologies, one multiple choice question and a short answer text-based question. Each question was factually correct, with no errors. Maybe simplifying some of the language would be helpful, and also there were a couple of matched questions/answers which haven’t been covered in the usual topic material I use. But this tool was extremely useful and could save a lot of time for staff users, providing an effective knowledge check for students.

Question bank generation from Ultra documents.

By the time I tried out this tool I was familiar with the AI Design Assistant and I didn’t need to use the LearnTech guide for this one. I auto-generated four questions, set the complexity to 75%, and chose ‘Inspire me’ for question types. There were two fill-in-the-blanks, an essay question, and a true/false question which populated the question bank – all were useful and correct. What I didn’t know was how to use the questions that were saved to the Ultra question bank within a new or existing test, and this is where the LearnTech guide was invaluable with its ‘Reuse question’ in the test dropdown guidance. I tested this process and added two questions from the bank to an existing test.

Rubric generation

This tool was easily navigable, and I didn’t require the guide for this one, but the tool itself, on first use, is less effective than the others in that it took my description word for word without a different interpretation. I used the following description, with six rows and the rubric type set to ‘points range’:

‘Demonstrate knowledge and understanding of cybercrime, technologies used, methodologies employed by cybercriminals, investigations and investigative strategies, the social, ethical and legal implications of cybercrime and digital evidence collection. Harvard referencing and writing skills.’

I then changed the description to:

‘Demonstrate knowledge and understanding of cybercrime, technologies used, methodologies employed by cybercriminals, investigations and investigative strategies. Analyse and evaluate the social, ethical and legal implications of cybercrime and digital evidence collection. Demonstrate application of criminological theories. Demonstrate use of accurate UON Harvard referencing. Demonstrate effective written communication skills.’

At first generation, it only generated five of the six required rows. I tried again and it generated the same thing with only five rows, even though six was selected. It did not seem to want to separate out the knowledge and understanding of investigations and investigative strategies into its own row.
I definitely had to be much more specific with this tool than with the other AI tools I used. It saved time in that I did not have to manually fill in the points descriptions and point ranges myself, but I found that I did have to be very specific about what I wanted in the learning outcome rubric rows with the description.

Journal and discussion board prompts

This tool is very easy to deploy and actually generates some very useful results. I kept the description relatively simple and used some text from the course definition of hacking:

‘What is hacking? Hacking involves the break-in or intrusion into a networked system. Although hacking is a term that applies to cyber networks, networks have existed since the early 1900s. Individuals who attempted to break-in to the first electronic communication systems to make free long distance phonecalls were known as phreakers; those who were able to break-in to or compromise a network’s security were known as crackers. Today’s crackers are hackers who are able to “crack” into networked systems by cracking passwords (see Cross et al., 2008, p. 44).’

I used the ‘Inspire me’ cognitive level, set the complexity level to 75%, and checked the option to generate discussion titles. Three questions were generated that cover three cognitive processes:

• Discussion prompts auto-generated in an Ultra course

The second question was the most relevant to this area of the existing course, the other two slightly more advanced and students would not have covered this material (nor have work related experience in this area). I decided to lower the complexity level to see what would be generated on a second run:

• Discussion prompts auto-generated in an Ultra course

Again, the second question – to analyse – seemed the most relevant to the more theory-based cybercrime course than the other two questions. I tried again and lowered the complexity level to 25%. This time two of the questions were more relevant to the students’ knowledge and ability for where this material appears in the course (i.e., in the first few weeks):

• Discussion prompts auto-generated in an Ultra course

It was easy to add the selected question to the Ultra discussion.

I also tested the journal prompts and this was a more successful generation first time around. The text I used was:

‘“Government and industry hire white and gray hats who want to have their fun legally, which can defuse part of the threat”, Ruiu said, “…Many hackers are willing to help the government, particularly in fighting terrorism. Loveless said that after the 2001 terrorist attacks, several individuals approached him to offer their services in fighting Al Qaeda.” (in Arnone, 2005, 19(2)).’

I used the cognitive level ‘Inspire me’ once again and ‘generate journal title’ and this time placed complexity half-way. All three questions generated were relevant and usable.

• Journal prompts auto-generated in an Ultra course

My only issue with both the discussion and journal prompts is that I could not find a way to save all of the generated questions – it would only allow me to select one, so I could not save all the prompts for possible reuse at a later date. Other than this issue, the functionality and usability and relevance of the auto-generated discussion and journal prompt, was very good.

On Friday 8th December, 2023, three new NILE tools will become available to staff; the AI Design Assistant, AI Image Generator, and the Unsplash Image Library.

AI Design Assistant

AI Design Assistant is a new feature of Ultra courses, and may be used by academic staff to generate ideas regarding:

  • Course structure
  • Images
  • Tests/quizzes
  • Discussion and journal prompts
  • Rubrics

The AI Design Assistant only generates suggestions when it is asked to by members of academic staff, and cannot automatically add or change anything in NILE courses. Academic staff are always in control of the AI Design Assistant, and can quickly and easily reject any AI generated ideas before they are added to a NILE course. Anything generated by the AI Design Assistant can only be added to a NILE course once it has been approved by academic staff teaching on the module, and all AI generated suggestions can be edited by staff before being made available to students.

• Auto-generating ideas for the course structure
• Auto-generating ideas for a discussion prompt
• Auto-generating ideas for test questions

AI Image Generator & Unsplash Image Library

Wherever you can currently add an image in an Ultra course, following the upgrade on the 8th of December, as well as being able to upload images from your computer, you will also be able to search for and add images from the Unsplash image library. And, in many places in Ultra courses, you will be able to add AI-generated images too.

• Selecting the image source (upload from device, Unsplash, or AI-generated)
• Searching for an image using Unsplash
• Generating an image using AI Design Assistant

First Thoughts on AI Design Assistant

Find out more about what UON staff think about AI Design Assistant in our blog post from Dr Cleo Cameron (Senior Lecturer in Criminal Justice): First Thoughts on AI Design Assistant

Other items included in the December upgrade

The December upgrade will see the ‘Add image’ button in a number of new places in Ultra courses for staff, including announcements (upload from device or Unsplash), and Ultra tests and assignments (upload from device, Unsplash, and AI-generated images). However, please note that images embedded in announcements will not be included in the emailed copy of the announcement; they will only be visible to students when viewing the announcement in the Ultra course.

Ultra rubrics will be enhanced in the December upgrade. Currently these are limited to a maximum of 15 rows and columns, but following the upgrade there will be no limit on the number of rows and columns when using an Ultra rubric.

More information

To find out more about these new tools, full guidance is already available at: Learning Technology – AI Design Assistant

You can also find out more by coming along to the LearnTech Jingle Mingle on Tuesday 12th December, 2023, between 12:30 and 13:45 in T-Pod C (2nd Floor, Learning Hub).

As ever, please get in touch with your learning technologist if you would like any more information about these new NILE features: Who is my learning technologist?