I’m an AL at UAL Creative Computing Institute (CCI), I teach Mathematics and Statistics for Data Science on BSc (Hons) Data Science and AI, and Exploring to Machine Intelligence unit on MSc Creative Computing. I’m pursuing a PhD degree in AI and music technology.
I hope to use this PgCert as a point of reflection, reflecting on my identity as a researcher (my PhD works)/ teacher (my teaching at CCI)/ student (me being a research student)/ artist (me being a music composer and producer), to situate myself into this state of disequilibrium. An overarching theme of my reflections is demystifying the materiality of computational technologies in accessible language and inclusive environments.
I’m also looking forward to meeting colleagues from across UAL to learn about the diversity in pedagogic practices.
A recurring theme highlighted in the interview is that disability is not seen as an impairment on a person, but as the barriers created by the environment/world/society that prevent individuals from achieving their full potential. This aspect of the Social Model of Disability is my main takeaway from the materials. In line with Kimberlé Crenshaw’s theory of intersectionality (Crenshaw, 1990), the social model identifies the societal attitudes such as stereotypes and prejudice (mentioned by Ade Adepitan), physical environments such as the mobility of a venue (mentioned by Chay Brown), and many other environmental factors as the main contributors to disabling experiences.
In addition, the intersections of disability and identity impact how individuals are included or excluded in various social contexts. For instance, Christine Sun Kim‘s worries about the effect of socioeconomic status on the support a citizen can receive, shows that identities can limit access to care and education; or having to go to the “hearing world” from the sign language community due to her identity as an artist, show that members of marginalised community can have the fear of attending to the “outside world”.
Disability considerations in my teaching context
At the UAL Creative Computing Institute, one of the disability considerations I have is that turning on the real-time automatic captions in PowerPoint during lectures can be really helpful (see the screenshot below, which can be activated simply by clicking an icon on the bottom of the slides). It was a really simple change to make, but I didn’t know about this until I worked with one of the students in a BSc unit, who has a hearing impairment. (Context: The main teaching activities in the unit are lectures and workshops, in which I deliver a 2-hour-long lecture, followed by class activities.) The student worked with two interpreters from UAL Disability Service who translated my spoken words into sign language.
I am really grateful for the support provided by the interpreters, and I found that it’s necessary for me to seek advice from students who are facing disabilities/challenges, and from people who work closely with them. As an education provider who is not familiar with the sign language community, I might not be aware of some of the facilities that are already there. For instance, I didn’t realise that the automatic captions nowadays are actually very useful until the BSc student prompted me, and even the student only found it out a few weeks ago when they were with another lecturer, who also has a hearing impairment themselves. It was the intersectionality of the lecturer who has multiple contexts and identities that revealed this technical affordances to us. This aligns with one of the recommendations from Lukkien et al. (2024) that the voices of minority faculty members with intersectional identities should be sought: (i) to help people who are facing disability to know the affordances and articulate their needs, and more importantly, (ii) to help educators who providing the learning environment (UAL, 2025) to understand what kind of supports are needed.
References
Crenshaw, K. (1991) ‘Mapping the Margins: Intersectionality, Identity Politics, and Violence against Women of Color’, Stanford Law Review, 43(6), pp. 1241–1299.
Lukkien, T., Chauhan, T. & Otaye-Ebede, L. (2025). Addressing the diversity principle–practice gap in Western higher education institutions: A systematic review on intersectionality. British Educational Research Journal, 51, 705–736. https://doi.org/10.1002/berj.4096 [Accessed: 24-Apr-2025]
UAL. (2025) ‘The Social Model of Disability at UAL’, YouTube. Available at: https://youtu.be/mNdnjmcrzgw [Accessed: 24-Apr-2025]
Observer: John O’Reilly Observee: Jasper Shuoyang Zheng
Part One: Context
What is the context of this session/artefact within the curriculum?
Methods 2: Digital Systems is a Year 1 unit in BSc Computer Science and BSc Data Science and AI, at UAL Creative Computing Institute. The unit is led by my colleague Dr Kayalvizhi Jayavel, who commissioned me to give two guest lectures on digital image processing and linear algebra. I will be delivering the sessions on the 10th and 17th of March. Each session will last about 3 hours, with 1.5 hours of lecture and followed by 1.5 hour of class activities.
How long have you been working with this group and in what capacity?
This is my first point of contact with most of the students. About 10 students from the BSc Data Science and AI course already met me when they were in one of the units that I taught last term. I’m new to other students from BSc Computer Science.
What are the intended or expected learning outcomes?
Taken from the unit brief:
[These two sessions] investigates the process of digitising and treating reality as sets of numbers. It introduces techniques of linear algebra as ways of dealing with large datasets, such as digital images, and how they can be manipulated using software packages. Inherent in all this abstraction are codified power relations that need to be unpacked to begin understanding the effects of computing on all groups in our larger, interconnected world.
I’ll be covering the LO2 and LO3 of the unit:
LO2: Identify and apply basic concepts of linear algebra such as vectors and matrixes (Knowledge)
LO3: Experiment with different methods of representing, storing, and manipulating datasets in digital systems (Enquiry)
What are the anticipated outputs (anything students will make/do)?
The planned activity session is for students to study the Python/JavaScript codes for the case studies in groups, and verbally describe and explain the codes to the class.
Are there potential difficulties or specific areas of concern?
Since it’s a joint unit, students from BSc Computer Science might not be familiar with some of the concepts in linear algebra, because they didn’t have the Math and Statistics unit last term. I’ll try to explain these concepts in easier terms.
How will students be informed of the observation/review?
I’ll send a Slack message to the students before the class to inform them that the session will be observed by a colleague in the room, and clarify that the instructor is the subject/observee. This will be verbally reiterated at the beginning of the session.
What would you particularly like feedback on?
One of the feedback I got from Ignacia last week was that the lecture part was overly long, it would be good to break it down into smaller sessions, and let students play with the hands-on practical activities right after every concept was introduced. I’ll try this strategy this week, so it would be great if I could get some feedback on the overall flow of the lecture, and whether students are actively experimenting with the practical activities.
How will feedback be exchanged?
Ideally by email.
Part Two: Feedback from John
#teachingspace
The classroom space is bright and large with quite intense strip lights. There are two large screens at the top of the room and two screens in the middle of the room attached to the ceiling. There is a table at the back of the room by the entrance where students can engage, it looks like a way in which community is being fostered. In relation to this, I liked the image of the forest as the screensaver, I wondered if this image of nature was intended as a contrast to the bright, lab-like intensity of the room? A good idea! I also wondered whether an image from the lecture might have been displayed, just to connect people with the content of the class. It can be a challenge to bring learning spaces to life – perhaps I was aware of this also due to the size of the room and numbers of students.
#stagingtheintroduction
As the time gets closer to the start you have the lecture title on the screen which is a useful and helpful way of focusing people as they come into the room. You make a lovely introduction inviting questions about last week’s class – establishing the narrative and continuity of the learning design is great practice (need to do more of this myself!) and you announce that the lecture is going to start in two minutes, which is a nice, effective way of slowly gathering people’s attention away from their chat.
#learningexpectations
What’s interesting is that you have the text running along the bottom of the screen – this makes the lecture more accessible, the scrolling text is another place for the students’ attention to land, complementing your voice and the slide. Having the slide with the agenda and the schedule is great and again, connecting to last week’s lecture is really excellent in establishing the continuity and design of the learning experience for the students. As you show the introductory slides you have an effective narrative voiceover that enthuses the students on why this topic is so interesting. Your pacing, to this listener, is really excellent. You also explain that the case studies are going to be the focus of the activities later on which is a great way of helping the students organize their expectations and energies for the session. It was also really useful to situate this particular class in terms of the learning outcomes – it’s such a helpful landing point for students, a place to situate what they are learning in this particular session.
#messyworkingout
When you begin to work through the slides you write on the screen in red-ink, working out and showing the mathematics of the activity. The ‘messiness’ of this is really helpful in mirroring how we figure things out when we learn, it is a really strong ‘aesthetic’ of learning, of representing how we begin to know things.
#learningwithchallenges
I thought how you foregrounded activities and slides in terms of ‘challenges’ was great too, that you identified the tricky stuff that this class was going to work with – it is really helpful to present specific problems and then do the storytelling of working out. There was a nice image example explaining image recognition that the machine needs to recognize the pattern – throughout the session you used the image examples rally well, especially in the contrasts.
#checkingin
As you worked through the slides it would be worth checking in if people are following your thinking, if they have any questions – these questions may of course emerge in anyway in the practical part of the class when the students do the case studies. It is always a difficult process to know when to take questions, some students are happy to keep going others can get lost, when to check-in is a matter of judgment. In a good way checking in also changes the class dynamic, makes it ‘interactive’ when you did check-in there is lots of nodding and confirmation that they understood the concept you were teaching.
#breakout
When you shared the link and asked them to experiment with the kernel and the values it is a useful breakout moment, just to break up the concentration demanded in listening to the lecture. All the students engaged with the activity discussing and sharing how they are changing the image post up. It was great you then checked in with the student who has support from the two signers,
#storytelling
You were effective in connecting the theoretical and technical aspects of the first part, to the different kind of learning happening later in the class. The nod to Eliza was excellent and it may have been interesting to give a little more history and storytelling around this. When we become expert in our research, as teachers we often forget just how much we know and take for granted, and telling the ‘human’ (and industry) histories around examples such as Eliza is a great way of bringing technical or abstract material to life.
#sharingquestions
You are really considered and thoughtful building out the context from each bullet-point on the slides. When a student asked a question (think it was Nicola?) it might be worth repeating the question out to the class as a whole, so every can hear the question and follow your answer – “Nicola just asked…” Sometimes you can then ask others to see if they have any thoughts on the question. When you do talk through the answer the student has an ‘aha moment’. It’s also excellent that you direct the student to the slides from the previous week – students often don’t connect their learning in the ways we design it!
#debatehistories
There was a really interesting example and questioning around the issue of gender bias in vectors that are embedded and wondering whether in material like this it might be worth opening this out for discussion? Perhaps even just a nod to the history of this and how was it discovered. Sharing histories and contexts in such hot topics are invaluable ways of helping students connect the technical elements of their learning.
Summary
I made some suggestions above Jasper, and in general to a non-expert such as myself, the pace of your delivery was really considered and measured – that can be a really hard thing to do, well done. You had a lot of material to work through, but it never felt rushed or dense. And though I didn’t get to see the workshopping part of the class, the way you signposted different parts of the lecture to later work on the case studies was really well designed. It helps the student imagine and locate themselves in a future task. I hope the rest of the class went well.
Part Three: Response from Jasper
John gave thorough and thoughtful suggestions for the lecture session. Many ideas pointed out by John were very inspiring and constructive.
John pointed out the idea of using a forest screensaver to contrast the lab-like intensity of the room. There hasn’t been any design of this (it’s actually just one of the default wallpaper in Macintosh), but pointing out how it might have created a lively environment is a reminder for me to think about setting the tone/vibe of the classroom. For instance, () mentions how lighting can affect alertness and the overall ambience in a learning space. And in fact colleagues at CCI have recently bought plants for the third-floor kitchen, which is such a nice idea for brightening the room.
I learnt the on-screen red-ink approach from typical math pedagogy – the instructor works out equations on a writing board. One of the advantages I found is that addressing while writing down key points/formulas is an effective way to slow the pace down, and therefore giving learners time to think.
Oratory and fluency in hosting conversations between the instructor and students (or between students and students) is a skill that I hope to improve at. John suggested repeating questions from students for the class (e.g., using sentences like “[name] just asked…”), which is indeed something I feel that I should have done. In addition, the suggestion of directing questions to other students is inspiring! I’ll definitely put that into my “strategy list”, as well as the suggestion of turning the bias issues of language models into a topic for an open discussion.
The second half of the class – the hands-on workshop session ended smoothly, lasted for about 60 minutes. We divided the class into three groups, and each group worked on a case study. I instructed all groups to run the source code for their case study, and explore how it implements concepts mentioned in the lecture. I tasked them to present the case study they worked on to the class. I prepared prompt questions for groups to structure their presentation (e.g., What does the project do? What library did they use? How was the data loaded and processed? How were the algorithms/techniques implemented?).
During the activity, I observed an interesting collaboration strategy: Two groups stayed at their table, after each student played with the source code individually on their machine, they eventually moved all content to a shared laptop. Their inspection of the source code and preparation of the presentation were mostly done together. During the activity, one or two students actively contributed to the slides and took control of the source code. Some students were less active but still had their attention on the shared laptop, others were working silently on their own laptops. This mirrors the suggestion from Harris (2022) that “students who are quiet because they are inclined toward silence”, this preference to “lurk in the shadows” for processing, considering and reflecting should also be acknowledged.
Overall, the unit is at its growing stage (this is the second cohort of this unit and I’m handling the unit for the first time), I’m planning to add more content and materials and maybe replace some of the existing ones. It was nice to have John to feedback on the session from a third-person point of view.
Reference
Harris, K., 2022. Embracing the silence: introverted learning and the online classroom. Spark: UAL Creative Teaching and Learning Journal 5, 101–104.
I read the article “Embracing the silence: introverted learning and the online classroom” (Harris, 2022) from the set reading list. The article gives an important provocation on admitting the introverted learning preference, and acknowledging that not all students are super-skilled at speed-thinking and oratory. It prompted me, the reader, to rethink the notion of active participation.
I read this article right before I received the observation feedback from John, who has signposted me for oratory strategies in the classroom. Therefore, my thoughts when reflecting on this article mostly centred around my delivery in class, including sharing questions with the class, allowing for a muted breakout for contemplation or working, and working with class dynamics. And they all centred around the topic of embracing silence (not necessarily in online sessions, but also for in-person sessions):
Pausing and Leaving Blank for Contemplation
One thing I noticed about my delivery was that I asked a question in class. Sometimes, I rushed for utterances to fill the silence. I noticed this when I recently tried out the “video camera” approach – to look at my own lecture recording (thanks to the nice IT facilities at High Holborn) for self-reflection. The article (Harris, 2022) quoted sentence, “While students are working or thinking, don’t use this as a time to share information” from Phillips (2017), which resonates with this recent discovery. I’ll try to purposefully pause and leave blank for thinking. In addition, when addressing practical knowledge in the lecture, I’ll try pausing the class for a few minutes and signposting students to break out and play with demos/materials. I believe this can be a nice way for working and thinking to emerge during a lecture.
Working with Class Dynamics
I recently learnt to arrange the pacing of a lecture by deciding which parts should speed up or simply use signposts to direct students to extended readings, and which parts should slow down to flourish thinking. Sometimes I purposefully slow down the pace of addressing by using written notes. Because of the lower speed of writing, the pace of the class slows down.
I also noticed a decrease in dynamics when more critical topics were introduced. In a lecture that I recently delivered, I mentioned the bias issue that is historically and systematically inherited in AI language models. There was a noticeable silence but focused attention in the students, with occasional nodding indicating that thinking and information processing were happening.
References
Harris, K., 2022. Embracing the silence: introverted learning and the online classroom. Spark: UAL Creative Teaching and Learning Journal 5, 101–104.
Phillips, K., 2017. How to Use Silence as a Teaching Tool [WWW Document]. The Art of Education University. URL https://theartofeducation.edu/2017/11/silence-teaching-tool/ (accessed 3.18.25).
Last term (Fall 2024) I led the unit Critical 1: Mathematics and Statistics for Data Science at CCI BSc Data Science and AI course. It was the first time I had the opportunity to arrange the entire unit from preparation to delivery and assessments. I wanted the unit to have a strong emphasis on the practical side of mathematics and statistics so that students can learn from examples, practical exercises, and projects.
Evaluation
The assessment has two elements. Element 1 is a composition of eight weekly submissions, similar to a quiz, with 2-3 multiple-choice questions corresponding to lecture contents and 1-2 written questions for students to report on the practical coding/programming exercises they did. Element 2 is an unseen time-constrained examination in which students work on a task sheet individually over one week and make a submission by the end.
I finished the marking for this unit before I read about the “Student understanding of assessment” paper (Berry O’donovan and Rust, 2004), which described an “explicit” to “tacit” framework for knowledge transfer. So this would be a timely opportunity to evaluate the two assessing elements according to the framework offered in the paper. The overall aim is to approach a balance between explicit and tacit aspects of the assessments.
Apart from the written marking criteria, I prepared a mocked examination for Element 2 (the examination), the mock gives a detailed breakdown of marks, and an illustration of how a completed task sheet is assessed. It acted as an exemplar in the spectrum between explicit and tacit processes (Berry O’donovan and Rust, 2004). However, I found implementing the mocked examination tricky because I do not want it to constrain what students think they will be assessed on, so instead of a full mock examination, I might reduce it into a set of (one or two) questions selected from a full examination, as a reduce exemplar next cohort.
Discussion/Feedback from the Instructor
The timeline towards the end of the unit got quite tight, I didn’t have time in class to discuss the mock exemplar. And timely discussion is indeed an important aspect of feedback exchanges since it gives time for retrospective discussion (Brooks, 2008). So for the next cohort of this unit I’ll make sure that (i) the weekly quizzes are checked in by myself or tutors, (ii) the task brief and mock/exemplar for the examination are published earlier, not toward the end of the unit.
Incorporating Formative Assessing Method
The mathematics and statistics unit combines foundational and practical learning outcomes. While I attempted to bring more practical elements into the assessment, some of the elementary math concepts are particularly harder to assess in a tacit project-based setting. For instance, calculating vector transformation might not be helpful in practical projects, but it’s a foundational element in the learning outcomes (knowledge) that need to be assessed.
The quizzes seem homogeneous in assessing this combination of foundational and practical knowledge. As discussed in the literature (Berry O’donovan and Rust, 2004), a combination of assessing methods around both the tacit aspect (learnt through experience) and the explicit aspect (disseminated knowledge). Therefore, to move forward, I will try to incorporate formative assessing methods in the future. For instance, replace the weekly quizzes with a weekly reflective blog, or a portfolio of practical exercises to be submitted by the end of the unit.
References
Berry O’donovan, M.P., Rust, C., 2004. Know what I mean? Enhancing student understanding of assessment standards and criteria. Teaching in Higher Education 9, 325–335. https://doi.org/10.1080/1356251042000216642
Brooks, K., 2008. Could do better? Students’ critique of written feedback. Networks 5.
I read the article “Know what I mean? Enhancing student understanding of assessment standards and criteria” (Berry O’donovan and Rust, 2004) before the last workshop. The article discusses assessment transparency and tacit knowledge in education. Some of the aspects resonate with my pedagogic practice in creative computing and artificial intelligence and machine learning (AIML) for media and arts. I’ll describe in this blog.
The article starts by describing the historically changing context in HE, highlighting the need to make assessment standards explicit and meaningful to students (p. 326). It then describes some of the challenges in addressing this need. For instance, the fuzziness and vagueness of written marking briefs. This mirrors the lack of well-defined measures in the context of AIML and creative computing – students in my course (even myself when I was a student three years ago) can struggle to interpret rubrics such as “computational creativity”, “innovation”, “reflection and evaluation”. Students in the course often interpret “evaluation” in a scientific context, which typically means technocentric methods such as the accuracy of an algorithm. However, this is not always desired in a creative computing context, in which evaluation can also mean a reflection of the making process, creative goals, and realisation.
The conceptual framework proposed in the paper becomes clearer in the spectrum illustration in Figure 1 (p. 331), which is very informative since it gives a landscape understanding of what kind of assessing elements can help balance explicit and tacit knowledge transfer. I’m recently co-working on an assessment brief for the unit Digital Systems, in which students work on a mini-project over the term. This illustration gives me very timely tips on incorporating some tacit aspects to the brief – apart from written instructions and marking criteria, I planned to create some examples of work to help students understand what distinguishes an excellent submission from an average one. In addition, adding some peer discussion of work-in-progress during class can also help the evaluation process.
In conclusion, the main takeaway of this paper for me is the understanding of challenges in transparent assessment standards and criteria, as well as the implementation of the “carefully considered combination of elements from along the spectrum” in my future pedagogic practice.
Reference
Berry O’donovan, M.P., Rust, C., 2004. Know what I mean? Enhancing student understanding of assessment standards and criteria. Teaching in Higher Education 9, 325–335. https://doi.org/10.1080/1356251042000216642
Session to be observed: Studio day during Part 3 personal project Size of student group: 31
Folded mini-book I made while following Ignacia’s demonstration.
Part One: Context Provided by Ignacia
What is the context of this session/artefact within the curriculum?
This session falls on the second week of part 3 of the course, where students write a personal project proposal (PPP) to research and execute for the remaining 8 weeks of the course.
Students have handed in their personal project proposal and are carrying out independent studio work to realize one of their outcomes. The tutor is giving informal feedback and facilitating the session.
How long have you been working with this group and in what capacity?
I’ve been working with this illustration group since November 2024.
I am the lead tutor seeing them 2 days a week – They have an AL lecturer seeing them 1 day a week.
What are the intended or expected learning outcomes?
Work independently during the session with their proposal with a self-initiated action for the week. This can include drawing, writing, photographing etc.
Receive and reflect on feedback on their work done during the week by their peer group in an informal crit format.
Act upon received feedback by tutor during the session.
Draft a plan of action for the following week using feedback as a starting point (materials to bring, questions they have ahead of hand in)
What are the anticipated outputs (anything students will make/do)?
Studio work from the day. This will vary student to student – can be a series of drawings, riso prints, digital work or 3d work etc.
Are there potential difficulties or specific areas of concern?
Students are working independently on self-set goals for the day and this could lead to some students losing sight of their intended aim for the week.
How will students be informed of the observation/review?
I will verbally inform them at the beginning of the session, saying that there will be a colleague in the room, clarifying that it is part of my PGCert and that they are not being observed or graded in any way.
What would you particularly like feedback on?
Mostly if peer to peer learning is happening while I focus on tutorials, something that has been more challenging for me this year.
How will feedback be exchanged?
Ideally written by email so I can have a record of it.
Part Two: Feedback from Jasper
I observed the first hour of Ignacia’s studio session. It was a lovely Thursday morning, the studio room was arranged into small groups of tables, and students arrived and greeted each other – it was a vibrant environment. The session started with Ignacia calling for students’ attention and giving a brief of the session’s aims and weekly plans. The briefing took around 10 minutes, and eventually, it connected to printing facilities and printed samples – a very nice transition from things like field trips to projects.
Then students diverged to work on individual projects, and Ignacia walked around to give one-to-one feedback. While I walked around with Ignacia during her one-to-one conversation with students, I tried to stay within a distance that was not too far or close to avoid distracting the conversation.
Students generally have an idea of their project and some work-in-progress sketches or experiments on the materials. So the conversation typically starts with students presenting their ideas, and then Ignacia comments on the work.
Ignacia did well in directing students to move from ideas to actionable and solid plans. For instance, prompting them to think about what kinds of material/technique/canvas they would like to use. I think this is very helpful to ensure students’ engagement in the process, and it is also a very good point of reflection for them. In one of the conversations, she demonstrated the canvas-folding technique to figure out the sequence and orientation of pages in a book, which was really informative (and fun!). Something I noticed is that Ignacia tends to give students a timeframe to work on. This could involve short-term plans for the day (the next two hours, before lunch, etc), or some general guidance on how long a process might take (e.g., “some steps might take two days”). This temporal aspect is something I would definitely benefit from if I were working on new materials/techniques – to have someone more experienced to give me a rough timeframe.
In the meantime, Ignacia knows individual students’ progress very well, causally checking on missing submissions from students to ensure they are on track, which I think is an effective strategy for pre-degree teaching so that students won’t get lost and have the “push” to stick to the progress.
On some tables, students have casual chat with each other. Some tables were quieter – student mostly working on their stuff with headphones on. This working-in-parallel setting gave a very nice studio vibe. My observation hasn’t reached the time when students share or
talk to each other about their work; maybe this is something that will emerge as the day unfolds, or maybe it needs a bit of a prompt. But having students working on shared tables like this seems to be a very nice approach to peer-to-peer learning since they are able to have a peek at each other’s progress easily.
This was a wonderful experience for me to learn about studio work! Thanks so much Ignacia for the session!
Part Three: Ignacia’s Response
It is always helpful to have an outside observer sitting in on sessions. Once I get over the nervousness of having someone in the room, I understand that there are many things that are embedded into my teaching I don’t notice.
Jasper mentioned how I occasionally give set timelines to students to finish tasks (‘in the next two hours’ ‘by lunch time’) and tend to clarify timelines (might take 2 days)
With a cohort I know well, giving timeframes to complete tasks has worked well. The current project we are working on is self-led and some students need little to no encouragement and with some needing more support to clarify their aims for the day.
In general, I try to manage expectations in terms of how long processes take – if a student wants to make a 3 colour screenprint in 1 day it is probable that it won’t be possible, so I outline that that idea might take 2 days or more to gage if the student wants to commit to that timeline or consider other options.
I do, however, need to keep an eye on not structuring the timings too much; some students might in fact finish a task in 2 hours, but some might need 4. I’m also not accounting for students changing the aim as they make and discover, which is something that happens during a studio day.
Jasper also pointed out something I hadn’t considered – to have points on the day where students check on each other’s progress with more intent or have students engage with someone they have less knowledge of their project. I would like to try and do this after the lunch break, when students need to re-engage with their work and it can take a while to get going again. Looking at someone else’s work before starting again could be good to re-engage with the day.
I’m pleased that he mentioned that the atmosphere in the studio is vibrant and friendly.
After lockdown and teaching online, it was important to rebuild the sense of community and bring emphasis to being together. It has taken a few years to achieve, but creating an environment where students want to come in is important to me as a tutor, and it has proven to be conducive to engagement with the course, leading to better retention and ultimately better results.
Session to be reviewed: Week 4 lecture for the BSc unit Digital Systems Size of student group: 36
Part One: Context
What is the context of this session/artefact within the curriculum?
Methods 2: Digital Systems is a Year 1 unit in BSc Computer Science and BSc Data Science and AI. The unit is led by my colleague Dr Kayalvizhi Jayavel, who commissioned me to give two guest lectures on digital image processing and linear algebra. I will be delivering the sessions on the 10th and 17th of March. Each session will last about 3 hours, with 2 hours of lecture and 1 hour of class activities.
How long have you been working with this group and in what capacity?
This is my first point of contact with most of the students. About 10 students from the BSc Data Science and AI course already met me when they were in one of the units that I taught last term. I’m new to other students from BSc Computer Science.
What are the intended or expected learning outcomes?
Taken from the unit brief:
The second part investigates the process of digitising and treating reality as sets of numbers. It introduces techniques of linear algebra as ways of dealing with large datasets, such as digital images, and how they can be manipulated using software packages. Inherent in all this abstraction are codified power relations that need to be unpacked to begin understanding the effects of computing on all groups in our larger, interconnected world.
I’ll be covering the LO2 and LO3 of the unit:
LO2: Identify and apply basic concepts of linear algebra such as vectors and matrixes (Knowledge)
LO3: Experiment with different methods of representing, storing, and manipulating datasets in digital systems (Enquiry)
What are the anticipated outputs (anything students will make/do)?
The planned activity session is for students to study the Python/JavaScript codes for the case studies in groups, and verbally describe and explain the codes to the class.
Are there potential difficulties or specific areas of concern?
Since it’s a joint unit, students from BSc Computer Science might not be familiar with some of the concepts in linear algebra, because they didn’t have the Math and Statistics unit last term. I’ll try to explain these concepts in easier terms.
How will students be informed of the observation/review?
I’ll send a Slack message to the students before the class to inform them that the session will be observed by a colleague in the room, and clarify that the instructor is the subject/observee. This will be verbally reiterated at the beginning of the session.
What would you particularly like feedback on?
I’ll do some recaps/calibrations on the prerequisite knowledge with students during the session. So mostly on the clarity of narrative and explanation, and perhaps the overall flow/speed of the lecture.
How will feedback be exchanged?
Feedback will be exchanged via email.
Part Two: Feedback from Ignacia
Jasper delivered a session on Digital systems: Computer science x Digital images x Data science for the Creative Computing institute at UAL. I observed the first hour of the session.
Jasper sent the slides in advance so I could look at the material before the session. This was helpful to get acquainted with it beforehand, considering it had technical computing elements I was not familiar with. It also gave me an idea of what to expect on the day.
When students arrived in the room, they chose freely where to sit and arranged themselves in table groups of 4 or 5. The slides for the session were displayed in several monitors throughout the room, making visibility of the material easily accessible to everyone, including students that sat at the back. Jasper used a microphone to ensure that everyone heard clearly. There was an interpreter present in the session for a student with a hearing impairment.
Jasper was a new face to many of the students, being his first point of contact with some. He introduced himself and gave his background for new students. He invited students to get in touch with any questions and gave his UAL contact email information.
He did a recap of previous sessions and explained how this one fit into the sequence of learning (last week hardware, this week software)
He clarified learning outcomes and outlined the agenda. The session would be split in 2: a lecture and a practical workshop to apply case studies.
Jasper checked with a show of hands if students had previous knowledge of JavaScript and Python to acknowledge the level of the cohort. He explained that they did not need previous knowledge and put students at ease.
Throughout the lecture, Jasper used a pen to interact with the slides, drawing a red line to point out things or write equations as he explained concepts – this made the slides more dynamic, turning them into a whiteboard and helping with explaining concepts. He purposely left space in the slides to write equations, showing good planning on his side.
Jasper used live code to illustrate concepts and directed students to use Google Colab, where they can run code online rather than download software.
Throughout the session, students used Google Colab to test code as the lecture was ongoing – helping to deepen the understanding of the concepts as they were explained. Overall, students were engaged, and their attention was retained throughout. There was a break roughly 45 minutes in, allowing students to recharge before continuing.
The information in the lecture was technical, but was often contextualised into the creative realm by showing examples of it in use in art (moving image and photography)
Example: John Whitney, catalog (1961) – the world’s first computer animation
Because of the nature of the lecture (straightforward delivery to an audience with the lecturer at the front) there were not many chances to specifically check on the students one to one – that was left for the second half of the session where the more hands-on element came in.
A question I might pose is: would the lecture become too long if there were tasks in-built after every concept was introduced? Would it be possible to let students have a go at playing with the code rather than them doing it independently as the lecture is ongoing so the tutor can do some concept checking?
Part Three: Response from Jasper
Ignacia’s feedback is very timely, which has given me time to update some of the planning for next week’s session.
The interpreter with the student with hearing impairment was something I hadn’t planned before the lecture. It was the first time I worked with an interpreter – although I checked with them to see if there was anything I needed to pay attention to, at the beginning I was still a bit nervous about the overall accessibility of the delivery. I checked on them after the first half of the lecture, and they helped me turn on the auto-transcript in PowerPoint, which I think helped the overall interpretation.
Ignacia mentioned that I write equations and diagrams on the slides with a pen. This is something that I kept doing but haven’t thought/reflected much about. Compared to simply putting content on the slides in a click-to-display way, writing them down seems to be a way to intentionally slow things down and give learners time to think/absorb. Recalling my previous slide preparation process, I actually didn’t have a rule of thumb on deciding what to put into slides and what to write live – it would be nice to reflect on this aspect in future teaching.
It was great to know that students opened the Google Colab while the lecture was ongoing. This made me realise that the live coding section seems to be a good chance to be turned into a hands-on element next time, where students follow the actions of the instructor to work on a task together.
Ignacia pointed out that the lecture part was overly long and there were not many chances to check on the students one-on-one. This was indeed something that I also noticed during the lecture – students can lose focus toward the end of the session. Letting students play with the code after every concept was introduced seems a sensible idea to keep them on track, as well as give me some chances for concept-checking. This is very timely feedback since I have another session with a similar setting next week and I’m currently working on the final tweak of the content. The plan is to have small demo sections (similar to the Google Colab section), but stop for 5 minutes to allow students to explore the code by themselves.
In a session for MSc Data Science and AI, I gave a lecture on unconventional techniques of using generative AI models, such as circuit bending and glitching neural networks, to create unexpected artistic expressions. As a part of the learning outcomes, students will do a hands-on programming activity to gain practical knowledge of the techniques. The main challenge of this activity was approaching these advanced practical techniques while ensuring students with less strong practical skills could also engage with the activity.
Evaluation
In the activity, I used an interactive programming notebook as a task sheet (link). In the notebook, I provided step-by-step guidance for students to follow. A typical interactive notebook in programming pedagogy requires students to execute the “code blocks”, and eventually adapt part of the code in the notebook to complete a few tasks as elaborations.
I have experience in running hands-on programming activities over the past two years. A critical aspect of ensuring students with different levels of practical skills all engage with the activity is to (i) have straightforward instructions in the notebook for those who may require more help getting on with the tasks, while (ii) giving a high degree of freedom to explore for those who are looking for more challenging tasks.
Given these considerations, I planned and experimented with the following strategies to address the challenge.
Moving Forward
Converging points during the activity
In my previous experience, after students had signed off to work on the notebook, the classroom diverged to individual or small-group structures, and they worked at their own pace. However, for this session, I experimented with a diverge-converge-diverge strategy (Palmgren-Neuvonen et al., 2021): students diverge to work through the first half of the interactive notebook. Then, before entering the advanced sections, we converge and meet again in a lecture style to reiterate key techniques they have encountered and explain the following advanced sections. Then we diverge again to keep working individually.
In the actual session, this strategy was implemented smoothly. As a result, students were actively engaging with the advanced section of the notebook. For future applications of this strategy, the class size might be a consideration. The class I ran was relatively small, with around 10 students. However, in another MSc unit I’m assisting on, the class size can go up to 80 students. Getting the attention back in such a large classroom might be harder. Clearer instructions on where and when to converge might be needed.
Co-created board for results-sharing
The idea of results-sharing is a commonly used pedagogic practice in creative coding, and it has been used by colleagues at CCI (Fiala et al., 2016). Borrowing this idea, I set up a collaborative Miro board for students to communicate their results. The board allows students to upload their creations and the code they have written.
This strategy ensured students who worked smoothly throughout the notebook kept engaging in the classroom to discuss their creations. The collection of results was very interesting, as shown below (permission and consent to share these results were granted by students).
Group works/ group discussions
If I were to do the lesson again, toward the end of the session, I would encourage students to work in groups, discuss their results, and encourage students who have finished the tasks to help out students who are still working on them. The aim is to foster peer learning – less-experienced coders may seek help from their peers rather than face the challenges alone.
References
Fiala, J., Yee-King, M., Grierson, M., 2016. Collaborative Coding Interfaces on the Web, in: International Conference of Live Interfaces. REFRAME Books, pp. 49–57.
Palmgren-Neuvonen, L., Littleton, K., Hirvonen, N., 2021. Dialogic spaces in divergent and convergent collaborative learning tasks. Information and Learning Sciences 122, 409–431. https://doi.org/10.1108/ILS-02-2020-0043
I read the article “Aesthetic Learning About, In, With and Through the Arts: A Curriculum Study” (Lindström, 2012). The article describes a conceptual framework for aesthetic learning, in which the delineation between convergent and divergent goals resonates with my pedagogic practices.
In the “Four ways of learning” section (p. 168), the article describes convergent goals as achieving something in pre-defined frameworks, and divergent goals as combining knowledge to construct something new. In the pedagogic practice of creative computing, converged and diverged learnings are equally important. A solid understanding of theories in pre-defined frameworks (e.g., computing and computer science) is a requirement. On the other hand, it is also important to have practical experience in diverged contexts. In a common setting of a creative computing classroom, information is disseminated during the lectures, and students actively test out their perceived information in practical sessions.
The divergent aspect also resonates with the constructivism learning theory (Narayan et al., 2013) that I am recently looking at, which describes applying current understandings, noting relevant elements in new experiences, and iterating knowledge.
I reflected on my teaching when I read about the four categories of learning “with”, “about”, “in”, and “through” art (p. 170). I typically focus on the “in” aspect – students experiment with techniques and materials (often digital materials such as data, models, and codes) with the goal of creating a digital artefact. And sometimes explore the “through” aspect – we reflect on what we can learn about the algorithmic and engineering aspects from applying them to the creation of art. I experimented with the “about” aspects in one of the case study, in which I framed a lecture on the algorithmic technique of “circuit bending” with the concept of appropriation in the arts. Through this experience I found how these four pillars are interweaved together as in Table 1 (p. 169) – starting with knowledge about principles, styles, and artists (“about”) to a diverged exploration space for experiments (“in”), then converge to “with” and “through” to think about what knowledge can be distilled and learnt.
Reference
Narayan, R., Rodriguez, C., Araujo, J., Shaqlaih, A., Moss, G., 2013. Constructivism—Constructivist learning theory., in: The Handbook of Educational Theories. IAP Information Age Publishing, Charlotte, NC, US, pp. 169–183.
Lindström, L., 2012. Aesthetic Learning About, In, With and Through the Arts: A Curriculum Study. International Journal of Art & Design Education 31, 166–179. https://doi.org/10.1111/j.1476-8070.2012.01737.x
In MSc Creative Computing, students come from diverse backgrounds in terms of their technical know-how in the field of computing. For many students, it is their first time getting on with programming languages or setting up programming environments on their computers. While some students already have skills in coding and programming.
Evaluation
So far in the classroom, my colleagues and I have focused more on delivering knowledge on the conceptual level, such as methods and theories. This is typical because we think conceptual-level knowledge and ideas are more important than technocentric know-how and are often worth discussing in the limited class time. However, this is often not a sufficient approach to support the diversity in students’ training needs. In my past two years of experience as a lecturer, I observed students at the beginning level put in a lot of effort, and often struggle to catch up with the technical aspects.
Therefore, to move forward, it is worth exploring how to support this diverse training needs on technical skills, and how to effectively equip students with practical skillsets that are sufficient for them to start exploring the creative aspects of computing.
Moving Forward
Code repositories:
I usually maintain online repositories (e.g., link) within the UAL network to keep course related source codes. For each week, there will be one or two notebooks as as interactive task sheets – studenst follow and work through the example codes provided in the notebook to learn the practical side of the unit. This is also a typical workflow in computer science – developers use code repositories to share open-source content, as well as an approach suggested by the literature in the pedagogy of AI/ML (Raman and Kumar, 2022). Introducing this approach in pedagogy can be an opportunity to learn the professional practices in the field.
I experimented with this approach in the Mathematics and Statistics for Data Science unit, and I received students’ feedback in which they mentioned that they appreciated the well-prepared materials. Moving forward, I will keep using and adapting this approach, for instance, providing more documentation to the repositories and clearer guidance on how to set up and navigate the repository, as well as undertaking actions that can ensure accessibility.
Asynchronous step-by-step tutorials:
Instead of having synchronous workshops, which are technical training in coding and programming, having learners follow pre-recorded video tutorials in a step-by-step manner can also be a beneficial approach. This has been an effective learning strategy for computer science education in engineering or more technical departments. It typically offers the benefit of allowing students to follow their own pace, tailor their own technical equipments, or adapt to their routine of setting tools and materials.
Several colleagues of mine have experimented with this approach, and they are generally well-received by the students. I will dedicate more time to offering these asynchronous resources as supplementary materials to my teaching.
Reference
Raman, A., Kumar, V., 2022. Programming Pedagogy and Assessment in the Era of AI/ML: A Position Paper, in: Proceedings of the 15th Annual ACM India Compute Conference, COMPUTE ’22. Association for Computing Machinery, New York, NY, USA, pp. 29–34. https://doi.org/10.1145/3561833.3561843
