Between the 8-10 July, the Learning and Teaching Enhancement Unit hosted the 13th Annual Learning and Teaching Conference.
The materials from the conference are now available on our webpages.
We would like to thank all of our contributors and attendees. The sessions were of such high quality.
We’re already heading into planning our 14th Annual Learning and Teaching Conference which is scheduled to take place in September 2026 (date TBC).
We hope to see you at a forthcoming event.
Turnitin will be unavailable between 16:00 and 22:00 on Saturday 9 August 2025 for scheduled maintenance.
During this time, you will be unable to submit or grade any assessments.
We apologise for any inconvenience caused.
We are working on a series of case studies to share practices of using Generative AI in Learning and Teaching Activities.
In this series of blogposts, colleagues who are using Generative AI in their teaching, will share how they went about designing these activities.
We’re delighted to welcome Dr Gareth Hoskins (tgh@aber.ac.uk) from DGES in this blogpost.
This was a classroom evaluation of an AI-generated summary of the scientific concept ‘flashbulb memory’ as part of a lecture on ‘individual memory’ in the 3rd year human geography/sociology module GS37920 Memory Cultures: heritage, identity and power.
I prompted ChatGPT with the instruction: “Create a 200-word summary of the concept of flashbulb memory”, created a screengrab of the resulting text and embedded this within my lecture slides giving the class 3 minutes to read it and discuss it on their tables asking specifically for responses to the questions:
Discussion didn’t touch too much on the questions I posed but focused more on the ChatGPT content where students were much more critical of the content than I had anticipated. They noted the dull tone, the repetition, uncertainty surrounding facts presented the vague approach and general lack of specificity. Those students showed a surprising degree of GenAI literacy which was conveyed to the class as a whole. During the discussion, the students became more aware of the utility of GenAI tools, more comfortable speaking about how they use it and might go on to use it, and how its limitations and weaknesses might affect the content it generates.
I developed the exercise using UCL guidance webpage ‘Designing Assessments for an AI-enabled world’ https://www.ucl.ac.uk/teaching-learning/generative-ai-hub/designing-assessments-ai-enabled-world and re-designed my exam questions on the module to remove generic appraisals of famous academics’ contributions to various disciplinary debates and substitute with hypothetical scenario-based questions that were much more applied.
My intension was to acknowledge that we exist in an AI-enabled world which creates opportunities but also problems for learning. I also used the exercise to introduce the risks relating to assessment and outline my own strategy for assessing on this module using real-life problem-based seen-exam questions requiring use of higher-level skills of evaluation and critical thinking applied to “module-only” content and recent academic publications which GenAI essay-writing tools struggle to access.
The activity helped students become more familiar with the use GenAI as a “research assistant” (for creating outlines and locating sources) and created an environment for open discussion about the limitations of AI-generated content in terms of vagueness, hallucination, lack of understanding, and lack of access to in-house module content on Blackboard or up-to-date research (articles published in the last two years).
I would flag other systems including DeepSeek, Gemini, Microsoft Co-Pilot and Claude AI as well as discuss their origins, pros and cons, and crucially caution about environmental and intellectual property consequences.
Keep a lookout for our next blogpost on Generative AI in Learning and Teaching case studies.
In the July update, we are particularly excited about an improvement to mathematical notation with MathJax and a way to measure student engagement with Blackboard Announcements.
There are enhancements to navigation in Group Assignments, adding captions to images in documents, and enhancing instructor efficiency in the activity page.
We are delighted to see this enhancement, which is something that we have been asking for since our move to Blackboard Ultra.
Blackboard have enhanced the formula rendering experience in the Content Editor by implementing MathJax, a tool for displaying mathematical notation:
This update improves the visual accuracy and consistency of LaTeX-based formulas, aligning them more closely with scientific and academic standards.
MathJax offers a more precise rendering style preferred by many STEM instructors. When activated, MathJax will automatically render LaTeX code entered directly in the Content Editor across supported areas of Blackboard. Wiris is still available as the default to render formulas for the Content Editor. If MathJax is not activated, Wiris will render formulas.
Further information is available on the updated help page: Math Editor.
Instructors can now verify which students have marked an announcement as viewed. By selecting the viewer count on the main Announcements page, instructors can open a list showing who has and hasn’t acknowledged the message. From this list, instructors can send a message to follow up with students who haven’t viewed the announcement or confirm that key information was received. This helps instructors understand how effectively their announcements are reaching students.
Image 1. Each announcement comes with a Viewers column on the Announcements page.
Image 2. The list of viewers for an announcement shows that two students have read the announcement and one hasn’t.
Blackboard Assignment offers a Group Submission function. This allows for one member of the group to submit on behalf of the students in their group. For markers, this means marking one submission, with marks and feedback allocated to all members of the group.
In this month’s update, Blackboard have made reviewing and grading group submissions more efficient with the addition of Previous and Next navigation controls. Instructors can efficiently move between group submissions using header bar controls, creating a smoother grading experience with fewer clicks.
Instructors can now navigate between group submissions without needing to return to the submission list. The Previous and Next buttons appear in the header bar:
Instructors can now add captions above or below image blocks in Documents.
Image 1. Instructors can go to Edit File Options to add image captions and set positions.
Image 2. The image caption appears above the image and provides more context.
Note that to use this feature, you need to upload the content as an image in the document editor.
The Activity Stream for instructors has changed to include courses, announcements, and activity updates in one place.
New features on the Activity page:
Shortcuts: New shortcuts have been added to enhance instructor efficiency.
Announcements: Read important institutional announcements.
Image 1. The new Activity page has sections for announcements, courses, and the activity stream.
If you have any enhancements to request from Blackboard, please get in touch with us via elearning@aber.ac.uk.
We are delighted to announce our training series for the forthcoming semester.
All training can be booked online using your Aberystwyth username and password. Our training booking system is now automated, so you will receive your calendar invitation within an hour into your calendar. Please join these sessions from your Outlook calendar.
If you have any questions, please contact us: elearning@aber.ac.uk.
As usual, our training sessions are grouped into 3 series:
In addition to the usual offerings, we also wanted to highlight the new sessions that we have introduced for 2025-26:
This session will introduce colleagues to Generative AI and offer the opportunity to think about ways in which you can incorporate Generative AI into your learning and teaching practice.
You can book your place on all the other sessions in this E-learning Essentials series via this link.
A reminder that all Essentials sessions are strongly recommended for any new members of staff in your department.
Blackboard Documents have had a complete overhaul in Ultra. This 30-minute pro session gives an overview of the new features and allows you to give it a go in your course.
We’ve combined our Discussions and Journals session into one. We’ll go through activity design for our interactive tools to help maximise student engagement.
We will look at the analytical tools available in your Blackboard course to help monitor student engagement. We’ll use this to tailor messaging as well as creating other activities such as knowledge checks and learning module progression to help keep your students engaged with their learning.
One of the features of Turnitin is PeerMark which allows you to create peer assessment opportunities for your students. This is great to allow students to provide formative feedback on each other’s work.
Want to spruce up your recordings? This session will showcase different ways in which you can use Panopto: from inserting quizzes mid recording, to give students the opportunity to get creative and use Panopto themselves. This session is great for those adopting a flipped classroom approach or who want to make use of Panopto beyond Lecture Capture.
Other sessions include the Blackboard AI Design Assistant and Advanced Vevox polling software design.
You can book your place on all the other sessions in this E-learning Enhanced series via this link.
We’ve designed 4 new workshops for colleagues based on the 4 areas of the Exemplary Course Award. Looking at each aspect, colleagues will reflect on how their own courses can be developed.
The 4 sessions are:
You can book your place on all the other sessions in this E-learning Excellence series via this link. Other sessions include Submitting an Exemplary Course Award.
If there are any other training topics that you’d like us to consider for Semester 2, please contact us.
In April, Blackboard introduced the Learning Object Repository [LOR] – we wrote about this in our monthly update blog. We also recently added Generative AI Assessment statements into the Repository for staff to use.
We have now written an LOR Policy for colleagues who are interested in adding content to the Repository for others to use.
The LOR allows us to create items centrally for colleagues to copy into their courses and organisations. LOR items can be updated, applying changes to content items across all courses and organisations. For more information, see the Blackboard help site.
The LOR is ideal for standardised content that is required across many courses. For example:
If you have any questions about the LOR or the new Policy, please contact us (elearning@aber.ac.uk).
We are working on a series of case studies to share practices of using Generative AI in Learning and Teaching Activities.
In this series of blogposts, colleagues who are using Generative AI in their teaching, will share how they went about designing these activities.
We’re delighted to welcome Dr Megan Talbot (met32@aber.ac.uk) from the Department of Law and Criminology in this blogpost.
We designed an assessment to improve AI literacy skills in our family law module.
The students were given a normal essay question: “To what extent should British law recognize prenuptial agreements?”.
They were also presented with the response of ChatGPTo1 to the same question.
The students were advised that their objective was to write an essay in response to the question. They were free to use the AI response in any way they wanted, they could build off it, use it as a starting point for research or totally ignore it, whatever they prefer. They were told that we would not tell them how the AI essay would score if they submitted it with no modification, but they were free to do that if they wished (none did).
We explained that with the increased use of AI tools they will not only need to be able to use AI outputs competently and responsibly, but also will need to demonstrate that they can add value that an AI cannot. Therefore they should view the task as trying to show that they can perform better than the AI.
The students generally did very well. We recorded fewer failing marks (below 40%) than previous years, as well as fewer marks below 50%. Very high performing assignments tended to use the text provided by the AI far less than those scoring lower.
They were provided with the normal assignment briefing sheet, as well as a lecture session on how to approach the assessment. The briefing document included more guidance than normal to help overcome any uncertainty as to how to approach the assessment. This included spesific guidance on things they may be able to do to improve on the AI answer, such as more use of case law, evidence of understanding the caselaw, examining more critical arguments advanced by academics and looking at the peer reviewed literature and writings by legal professionals. Students were also specifically warned about hallucinations (the tendency of AI to provide false information in a way that appears “confident”) and the need to fact check the AI if they were going to rely on it.
We received a number of questions from higher performing students asking “do I have to use the AI response”, to which we responded “no”. Students generally seemed uncertain as to what they were allowed to do despite a great deal of guidance given in the initial briefing document and accompanying lecture.
Unfortunately, a significant number of students were tripped up by failing to factcheck one of the case descriptions that ChatGPT used, which was inaccurate. Feedback was left on those essays to remind them of the need to factcheck AI resources.
We did not survey the students on this assignment specifically, but in the SES several of them reported that they found it very useful in understanding the limitations of AI. In conversation, a number of students said it helped them overcome initial procrastination, as they were given a starting point to build from. Higher scoring students reported reading the AI output, but doing their own research and writing as normal, only referring to the AI to make sure that they did not ignore any core points by mistake.
We are considering reducing the length of the essay and incorporating a small reflection on their use of AI as a part of the assignment. Additionally, we will be elaborating on the warning to factcheck AI outputs to specifically mention that real cases may be cited but be given misleading or false descriptions or may be cited to support points not addressed by the case.
Keep a lookout for our next blogpost on Generative AI in Learning and Teaching case studies.
Now that the 2025-26 modules are available to teaching staff, we can link them together at the module co-ordinator’s request. This process is called merging courses (previously known as parent-childing) and works with courses in Blackboard Ultra. Linking courses together is an effective way of dealing with separate courses with the same content so you don’t have to upload materials to two or more different courses.
This process makes one course the Primary (previously parent), whilst the other course(s) becomes Secondary (previously child). There’s no limit on how many secondary courses you can make but there can only be one primary.
If you’d like to merge any courses, we invite module coordinators to contact elearning@aber.ac.uk
indicating the module codes for the primary and every secondary course in the following format:
Primary module code: secondary module code/s
Many members of staff are currently using the merge course facility across the institution. Some examples are:
Essentially, any module/course that shares the same content is ideal for Merging courses.
Students will see the name of the course that they are enrolled on (even if it’s the secondary course) when they log into Blackboard but they will see all the content placed in the primary course. Instructors will not be able to place content in the secondary course.
Now, before the start of term and whilst course content is being built, is the perfect time for linking your courses. Whilst the linking of courses does save time in the loading of materials, here are some points to consider:
Whilst all content is automatically visible once the courses are merged, you can use groups and adaptive release if you only want the content to be visible to a specific module cohort. This might be useful, for example, if you have merged a 2nd year and 3rd year course but your students on the different courses have separate assignments. You can use groups – 1 for the 2nd year students and one for 3rd year students and limit who can see the assignment information and submission point. See our guidance on Creating Groups and Release Conditions (previously ‘adaptive relesease’ in Blackboard Original).
Once the merging takes place, all students will appear in the Grade Book of the primary course. You can, however, determine whether they are enrolled on the parent course as this information displays against the student in the Grade Book columns.
If you’d like further information on this process or have any questions, please contact us on elearning@aber.ac.uk.
We are working on a series of case studies to share practices of using Generative AI in Learning and Teaching Activities.
In this series of blogposts, colleagues who are using Generative AI in their teaching, will share how they went about designing these activities.
We’re delighted to welcome Dr Panna Karlinger (pzk@aber.ac.uk) from the School of Education in this blogpost.
This activity is focused around finding reliable academic sources for students to use in their coursework. The students are invited to use a ‘seed paper’ for an upcoming assignment to feed into ResearchRabbit, that uses machine learning to map related literature based on authors, citations, related topics or concepts. The students are then prompted to choose sources for their assignments, and critically evaluate these using the CRAAP test – checking the currency, relevance, accuracy, authors and purpose of the sources to pass a judgment on overall reliability before use.
Students reported an increased confidence and ability to find academic sources and to demonstrate criticality within their work. Despite the vast resources and detailed guidance provided by both the teaching and library staff, students often struggle to find relevant sources to support their work, which was successfully addressed where students engaged with the activity.
This activity was part of a key skills module, where students had prior knowledge of the CRAAP test, finding sources and had a discussion around and introduction to generative AI, the opportunities and risks involved as well as efficient and ethical use. Synthesising their prior knowledge, the tool was introduced as a demonstration, and then students used their own devices to find sources for a chosen, upcoming assignment for a different module.
Some students are still wary or skeptical about using AI, or fear being accused of unfair practice, so it was important to demonstrate use cases where they can use AI in a confident manner to help develop these skills. Some students did not have large screen devices on them and the activity was challenging to carry out on a phone, this has to be considered in the future, and some students require more hands-on guidance and support with the activity, this is largely down to digital skills and competence.
It reinforced some messages about critical AI literacy, evaluating output and sources in general, reminding them of the importance if criticality in their work, and finding further and often more up-to-date information and resources helped inform the coverage and evaluations in their assignments where students engaged as expected.
As we no longer teach the key skills module, there is an opportunity to embed this into other modules, for instance in assignment support sessions or optional drop-ins. This allows for smaller groups of students and more one-to-one time as necessary, which could make this activity more successful; given that the students received the necessary guidance from the department on the use of AI. This could also be part of research methods modules or guidance we give to PGRs, as this resource is not only free, but also has more advanced capabilities compared to similar literature mapping tools, which was be valuable to anyone working on a dissertation or thesis.
Keep a lookout for our next blogpost on Generative AI in Learning and Teaching case studies. If you are using Generative AI in your teaching practice and would like to submit a blogpost, please contact elearning@aber.ac.uk.
As leader of our PGCTHE programme, I keep an eye out for resources to help staff teach effectively. These include webinars, podcasts, online toolkits, publications and more. Topics include active learning, online/blended teaching, accessibility/inclusion, and effective learning design based on cognitive science. Below I’ve listed items that came to my attention in the past week. In the interest of clarity, our policy is to show the titles and descriptions in the language of delivery.
Please see the Staff Training booking page for training offered by the LTEU and other Aberystwyth University staff. I hope you find this weekly resource roundup useful. If you have questions or suggestions, please contact our team at lteu@aber.ac.uk. Social media: BSky, X.com.