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On 23 May 24 I attended an AL development event (in my capacity as an OU tutor) that was all about Generative AI (which is abbreviated to here as GenAI). This blog sits alongside a couple of other blogs that I shared last year that also relate to GenAI and what this means for education, distance learning, and education practice.

What follows is some notes that I made during a couple of the sessions I attended, and what points and themes I took away from them. I also share some critical perspectives. Since GenAI is a fast moving subject, not just in terms of the technology, but in terms of policy and institutional responses, what is presented here is also likely to age quickly.

Opening keynote

The event opened with a keynote by Mychelle Pride which had the subtitle: Generative AI in Learning, Teaching and Assessment I won’t summarise it at length. Instead, I’ll share some key points that I noted down.

One important point was that AI isn’t anything new. A couple of useful resources were shared, one from the popular press, How AI chatbots like ChatGPT or Bard work – visual explainer (The Guardian) and another from industry: The rise of generative AI: A timeline of breakthrough innovations (Qualcomm).

An interesting use case was shared through a YouTube video: Be My Eyes Accessibility with GPT-4. Although clearly choreographed, and without any indication of whether any of this was ‘live’, one immediately wonders whether this technology is solving the right problems. Maybe this scenario implicitly implies that visually impaired people should adapt to the sighted world, whereas perhaps a better solution might be for the world to adapt to people with visual impairments? I digress.

There are clear risks. One significant concern lies with the lack of transparency. Tools can be trained with data that contains biases; in computing there’s the notion of GiGO: garbage in, garbage out. There’s also the clear potential that GenAI tools may accept and then propagate misinformation. It is clear that “risks need to be considered, along with the potential opportunities”.

A point was shared from a colleague Michel Wermelinger who was quoted saying “academic conduct is a symptom, not the problem”, which directly takes us to the university’s academic conduct policies about plagiarism.

In this session I learnt a new term: “green light culture”. The point here was that there are a variety of positions that relate to GenAI: in HE there are policy decisions that range from ‘forbid’ to ‘go ahead’.

I made a note of a range of searching questions. One of them was: how might students use Generative AI? It might become a study assistant, it might facilitate language learning, or support with creative projects. Another question was: how could pedagogies be augmented by AI? Also, is there a risk of over dependence in how we use these tools? Could it prevent us from developing skills? How can we assess in a generative AI world? Some answers to this question may be to have project-based assessment, collaborative assessment, to use complex case studies, and to consider the use of oral assessments. 

A point is that students will be using Generative AI in the future, which means that the university has a responsibility to educate students about it

Towards the end of the keynote, there was some talk about all this being revolutionary (I’ll say more about this later). This led onto a closing provocative question: what differentiates you (the tutor) from Generative AI?

During the keynote, some interesting resources were shared:

• Alpha Go Documentary (YouTube)
• Jisc: A Generative AI Primer
• How to use generative AI creatively in Higher Education

Teaching and learning with AI across the curriculum

The aim of a session by Mirjam Hauck was to explore the connection between AI and pedagogy, and to also consider the issue of ethics.

Just like the previous presentation, there were some interesting resources that were shared. One of them was a talk: TED Talk: How AI could save (not destroy) education.

Another resource was a recent book, Practical Pedagogy: 40 New Ways to Teach and Learn by Mike Sharples which students and staff can access through the OU Library.

I had a quick look at it, just to see what these 40 new ways were. Taking a critical perspective, I realised that the vast majority of these approaches were already familiar to me, in one way or another. These are not necessarily ‘new’ but are instead presented in a new way, in a useful compendium. The text also shares a lot of informal web links, which immediately limits the longevity of the text. It does highlight academic articles, but it doesn’t always cite them within a description of a pedagogy. My view is: do consider this text as something that shares a useful set of ideas, rather than something that is definite.

During this session, there were some complementary reflections about how GenAI could be linked with pedagogy: it could be used to help with the generation of ideas (but to be mindful that it might be regenerating ideas and bits of text that may be subject to copyright), play a role within a Socratic dialogue, or act as a digital assistant for learning (which was sometimes called an AIDA – an AI digital assistant).

Power was mentioned in this session, with respect to the power that is exerted by the corporations that develop, run, and deploy AI tools. The point I had in my mind during this part of the session was: ‘do be mindful about who is running these products, why, and that they hope to get from them’.

A brief aside…

Whilst I was prepping this blog, I was sent a related email from Hello World magazine, which is written for computing educators. In that email, there was a podcast which had the title: What is the role of AI in your classroom? 

There was an interesting discussion about assessment, and asking the question of ‘how can this help with pedagogy?’ and ‘how can we adapt our own practices?’ A further question is: ‘is there a risk that we dumb down creativity?’

A scholarship question?

A few times this year tutors have been in touch with me, to ask the question: ‘I’ve seen a students answer in a script that makes me think they may well have used Generative AI. What do I do?’ Copying TMA questions, or any other elements of university materials into a Generative AI tool represents a breach of university policy, and can potentially be viewed as an academic conduct issue. The question is: what do tutors do about this? At the moment, and without any significant evidence, tutors must mark what they have been given.

An important scholarship question to ask is: how many tutors think they are being presented with assessments that may have been produced by Generative AI tools?

Reflections

There was a lot of take on board during this session. I need to find the time to sit down and work through some of the various resources that were shared in this session, which is (in part) the reason for this blog.

When I was a computing undergraduate I went to a couple of short seminars about the development of the internet. When it came to the topic of the web browser, our lecturer said: “this is never going to catch on; who is going to spend time creating all these web pages and HTML tags?” Every day I make use of a web browser; it is, of course, an important bit of software that is embedded within my phone. This connects with an important point: it is notoriously difficult to predict the future, especially when it comes to how technologies are used. There are often unintended consequences, both good and bad.

Being a former student of AI (late in the last century) I’m aware that the fashions that surround AI is cyclical. With each cycle of hype, there are new technologies and tools. Following an early (modern) cycle of AI, I remember a project called SHRDLU, which demonstrated an imaginary world, where users could interact with natural language. This led to an expression that they key challenges had been solved, and all that needs to be done is to scale everything up. Reality, of course, is a whole lot more complicated.

A really important point to bear in mind is that GenAI (in the general sense) cannot reason. You can’t play chess with it. There are, however, other tools within the AI toolset that can do reasoning. As a postgrad student, I had to write an expert system that helped to solve a problem: to figure out a path through a university campus.

I’ve also been around for long enough to see various cycles of hype regarding learning technologies: I joined when e-learning objects were the fashion of the day, then there was the virtual learning environment, and then there was a craze that related to learning analytics. In some respects, the current generation of AI feels like a new (temporary) craze.

Embedding AI into educational tools isn’t anything new. I remember first hearing about the integration of neural networks in the early 2000s.  In 2009 I was employed on a project that intended to provide customised digital resources for learners who have different requirements and needs.

As the models get bigger, more data they hoover up, and the greater potential of these tools generating nonsense. And here lies a paradox: to make effective use of GenAI within education, you need education.

Perhaps there is a difference between generally available generative AI, to generative AI that is aligned to particular contexts. This takes me to an important reflection: no GenAI tool or engine can ever know what your own context is. You might ask it some questions and get a sensible sounding response, but it will not know why you’re asking a question, and what purpose your intended answer may serve. This is why the results produced by a GenAI tool might look terrible, or suspicious if submitted as a part of an assessment. Context is everything, and assessments relate to your personal understanding of very particular learning context.

Although the notion of power and digital corporations was mentioned, there’s another type of power that wasn’t mentioned: electrical power. I don’t have figures to hand, but large language models require an inordinate amount of electrical energy to do what they do. Their use has real environmental consequences. It's easy to forget this.

Here is my view: it is important to be aware of what GenAI is all about, but it is also really important not to get carried away and caught up in what could be thought of as technological froth. It’s also important to always remember that technology can change faster than pedagogy. We need to apply effective pedagogy to teach about technology. 

In my eyes, GenAI, or AI in many of its other forms isn’t a revolution that will change everything, or is an existential threat to humanity; it is an evolution of a set of existing technologies.

It’s important to keep everything in perspective.

Resources

A number of resources were highlighted in this session which are worth having a quick look at:

• Open Learn: An introduction to artificial intelligence – a free short course that also addresses the history of AI.
• Exploring Generative AI: critical skills and ethical use – some useful resources from the OU library.
• Generative AI for students – OU policy guidance for students.

Acknowledgements

Many thanks to the presenters of this professional development event, and the team that put this event together. Lots to look at, and lots of think about.

In June 2017 I attended the Heathrow and Windsor staff development event. Like other events that are run by the AL support and professional development (ALSPD) team, this was a residential event, which meant an overnight stay. The evening comprised of a meal and an opportunity to network with fellow associate lecturers and to participate in a number of activities that allowed us to share practice.

Overview

The main conference day comprised of a faculty specific sessions followed by two cross-faculty AL development sessions that everyone could choose from. There appeared to be a good mix of presentations, which included a talk about professional recognition (which relate to fellowship of the Higher Education Academy), updates about a new teaching tool called Adobe Connect, and how to apply for new associate lecturer vacancies.

The faculty session began with a short talk about a professional development initiative called By ALs For ALs (which I hope to blog about later at some point). This was followed by a breakout into different rooms depending upon the ‘schools’ that tutors were affiliated to.

I led the School of Computing and Communications session, where I shared a number of updates (thanks to slides that were prepared by the head of school). Key points included plans for the updates to the Group Tuition Policy, and the recruitment for new modules. In my school, two new modules are: TM111 and TM112, which are new introduction to computing modules, replacing a larger 60 point module.

Workshop: delivering excellent correspondence tuition quickly

In the afternoon, I facilitated two cross faculty workshop sessions which had the title: Delivering excellent correspondence tuition quickly: is it possible and how do we do it? This session had a big and deliberately provocative title, and relates to a subject that is really important to me: I’m very mindful of the importance of delivering effective correspondence tuition.

Here is the abstract of the session: Correspondence tuition takes a lot of time. Delivering excellent correspondence tuition is both an art and a challenge, but how we can try to deliver excellent correspondence quickly? This session is open to anyone in any faculty and is all about sharing experiences and uncovering correspondence tuition techniques to make things easier for ourselves. If you are a new tutor and would like to learn some useful tips and techniques, then do come along! If you are an experienced tutor and would like to share your experience with others, you will be especially welcome too! You will hopefully come away with an armoury of techniques that you can apply with your next TMA. An outcome of the session will be a useful resource that will be shared to everyone after the AL conference.

To prepare for the session, I wrote a PowerPoint presentation. I also designed the session to be as interactive as possible since I felt that I wouldn’t have all of the answers, and that it was important to listen to the views of tutors. To give a feel for the session, here is a quick summary of all the slides that I had prepared.

Summary of session presentation

After a quick introduction, I asked a series of questions to elicit thoughts about how to define excellent correspondence:  What do you think is important? What should be included? What tone should you adopt? What really matters in your subject or module? Where does feedforward go?, and Where does feedback go?

Next up was a slide that described some research by a former colleague called Mirabelle Walker, who wrote a paper entitled ‘An investigation into written comments on assignments: do students find them usable?’ This paper was an OU study which conducted an analysis of over 3000 comments on 106 assignments in 3 modules. Different comment types were identified: content, skills development, motivating (and demotivating!), mention of future study, references to resources.

Some research

A key factor was depth of comments: indication of a problem, correction of a problem, correction along with an explanation. .Motivating comments offered identification, amplification relating to the praise, explanation as to why something is good. In terms of the analysis, these came out as indication (33.3%), amplication (56.1%), explanation (10.6%). Another type of comment was skills development comments, where were analysed as follows: indication (7.7%), correction (78.8%), explanation (13.5%)

A key point that I had on the slide was the comments aimed to bridge gaps of understanding, i.e. they are intended to move things along. I also posed a question to everyone: is there anything that your module team can help with? The implication of this is: if there is something that a tutor think that a module team can help with, then it is really important to get in touch and to let them know.

Questions

For the next bit of the slide, I presented a set of questions across two slides. The first slide had the title: How do you do your correspondence teaching? The questions were: Where do you do your marking? What do you do before you start? Do you have a routine? If so, what is it? Do you have a strategy or an approach?, and What do you tell your students?

The second slide had the title: Doing things quickly… or using time efficiently. It had three key questions: (1) What would be your biggest tip for a new tutor? (2) What would be your biggest tip for a fellow tutor? (3) What would you put in a resource for a tutor?

Tips

Towards the end of the session, I shared set of eleven personal marking tips and opinions. The idea of sharing these personal views was to consolidate all the discussions; the tips and any differences in opinions about them could facilitate further discussions. 

My marking tips were: (1) check on the tutor forum to see what other tutors are saying, and whether other tutors have any issues with the scripts that students have submitted, (2) create a TMA summary template using comments that have been given to a student as a part of an earlier TMA, similarly (3) take time to look at the previous TMA (PT3) summaries. (4) to ensure consistency, mark a question at a time (unless your module assessment structure suggests it might be easier doing something different) (5) use a computer that has multiple screens; this way you can see different views of the work more easily. (6) don’t agonise over individual marks; use your marking instincts and commit to something; you’ll invariably be right.(7) when giving feedback, explain why things are assessed (what is it assessing) (8) offer pointers beyond boundaries of the module; this may help students to understand the assessment structure. (9) Proactively tell students how marking are going either by email, or by a forum, or both! (10) Always praise effort, not the score. And finally, (11) if it is apparent that a student is having real problems, you can always recommend running a special session.

Discussion summary

During each of the two workshops, I captured some of the key discussion points by making notes on a flipchart. What follows is a brief summary of some of the main points captured from each of the two groups.

Group one: excellent correspondence tuition can mean timeliness, i.e. returning things quickly so the students can benefit from the feedback. Sign posting is considered to be important, as is being specific. It is important to acknowledge effort, and to stretch students. It is also important to manage their expectations. 

An interesting approach is to ask them leading questions, or to present a series of questions. It is useful for tutor to do some monitoring (to help with module quality control). Feedback should be personalised, and should be concise and precise. Use positive language. Other thoughts included defining what is meant by learning success, or setting a learning goal for the future. Finally, use the KISS principle, which means: keep it simple. Also use a ‘feedback sandwich approach’ that emphasises the positive.

Group two: the feedback should be personalised for the needs of students, so it can help them to progress. Feedback should be detailed, but not too detailed. It is also (of course) important that tutors follow the marking notes (and refer to the learning outcomes) that have been provided by the module team. Offer students some priorities in terms of things to work on. As well as be encouraging, give students three (positive) points of advice, and offer signposts to the things that they can do to improve.

Also, do contact the students if we need to. Offer pointers to encourage them to look forward to different parts of a module and explain how the different parts are connected together. In terms of tone, emphasise what needs to be done to move forward. Be professional, and also do comment on study skills, such as referencing. Explain module ideas and correct terminology. Offer feedforward comments with reference to the final assessment and accompanying learning outcomes.

The second group also had some very practical suggestions: tutors should encourage students to become familiar with the assignment submission process by submitting a dummy eTMA. Another point was about the use of discussion forums to share information (and, perhaps, even notes that relate to the module). 

Reflections

There was a lot of discussion that took place during both of the two workshop sessions that I facilitated. These notes are drawn from the plenary sessions that I ran. Another thought is that the points that I have presented here are, of course, influenced by my own experiences as a tutor. Different tutors at the same sessions may have come away with a very different view about what was discussed, and that is something that is okay: every time we go to one of these professional development sessions, invariably we pick up something new.

The biggest thing that I have, personally, taken away from the session is the thought of: ‘offer the students three key points when you give them feedback; offering more than three points has the risk of overloading them’. This comment relates to the assessment summaries which are used to offer feed-forward guidance, rather than feedback which is directly left on a student’s script. This is a thought that I have thoroughly taken on board within my own practice as a tutor on a Computing and IT project module.

I came away with another thought: I felt that the use of Mirabelle’s research really helped to contextualise and explain our academic practice. This got me thinking: perhaps I could do a literature review of research that relates to correspondence tuition. Whilst I certainly could do that (I’ve made a note!), there are other things that I need to get on with. One of those things is a summary of another professional development event that was held in Leeds.