Observation by a Peer

Posted on 16th March 2025 by Jasper Zheng Shuoyang

Observer: Ignacia Ruiz
Observee: Jasper Shuoyang Zheng

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.

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Planning and Teaching for a Hands-On Activity (Case Studies #2)

Posted on 26th February 2025 by Jasper Zheng Shuoyang

Background

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
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Learning About, In, With and Through the Arts in the Classroom of Creative Coding (Reflective Post #2)

Posted on 26th February 2025 by Jasper Zheng Shuoyang

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
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Supporting Diverse Training Needs on Programming Skills (Case Studies #1)

Posted on 25th February 2025 by Jasper Zheng Shuoyang

Contextual Background

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
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Storying the Self as/in Pedagogic Practice (Reflective Post #1)

Posted on 22nd February 2025 by Jasper Zheng Shuoyang

In the paper “An a/r/tographic métissage: Storying the self as pedagogic practice”, Osler et al. (2019) presented the practice of narratives and storying the self, as a pedagogic practice to embrace the multifaceted perspectives and subjectivity in artistic practices.

After presenting the four pieces of narratives, the paper weaving together these piece and constructs the fifth narrative, “as a means of critically examining and elevating personal narrative”. Therefore, when I was reading this paper, I decided to write down notes of my thoughts and reflection, if appropriate, as the sixth narratives (See the screenshot below for a few samples).

I see this storying the self approach as a wonderful opportunity to document my learning process in the context of the field/subject I teach – artificial intelligence and machine learning (AIML) for media and arts. Over the past decade, AIML for media and arts has become a field in which new methods, new practices, new norms are proposed, experimented, and implemented every months, weeks, or even days. As a new researcher/lecturer in this field, learning and adapting to these changes often benefit my practices. 

Materialising, appropriating, and sensing making around new technological advances (Dix, 2007) has been a longstanding technique. Often during this process, my colleagues and I pull out the threadscape. For instance, we derive teaching materials (such as examples of works discussed in class), theoretical frameworks (such as taxonomies of approaches), and practical infrastructure (such as the coding repositories for each units). And eventually deliver these contents in a way to encourage students in the course to explore in this intersection of technologies and arts.

In this intersection, I often struggle to keep up with changes. I think narrating my own process of learning and adapting can be a fruitful approach to “weaving the threadscape” in this fast pace and sometimes disequilibrium domain. And if time is allowed, keeping blog posts of narratives, or documentation the development of materials, are definitely sometime I would like to experiment with in future teaching works.

References

  • Dix, A., 2007. Designing for Appropriation. Presented at the Proceedings of HCI 2007 The 21st British HCI Group Annual Conference University of Lancaster, UK, BCS Learning & Development. https://doi.org/10.14236/ewic/HCI2007.53
  • Osler, T., Guillard, I., Garcia-Fialdini, A., Côté, S., 2019. An a/r/tographic métissage: Storying the self as pedagogic practice. Journal of Writing in Creative Practice. https://doi.org/10.1386/jwcp.12.1-2.109_1
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Re-Materialisation in the Pedagogy of Computational Technologies (Microteaching Reflection)

Posted on 13th February 2025 by Jasper Zheng Shuoyang

In the microteaching task, I hope to explore re-materialisation, the practice of transforming intangible computational concepts (the immaterial) back into traditional formats, such as paper and wood, and channelling them into tangible experiences (Ferreira, 2022).

Context

When approaching the object-based learning task, I started by reflecting on my journey as a student and a teacher in the classroom of computational technologies. Object-based learning, especially with physical objects, is not a frequently used practice in this context, since the materiality of computational technologies is often deposited into digital data and virtual environments without their objecthood.

Although we often attempt to use real-world scenarios to demonstrate theoretical concepts, for instance, using the classic tin can phone example to demonstrate information theory, or the Alice and Bob fictional characters to demonstrate cyber security protocols, they typically remain in intangible theoretical scenarios or thought experiments.

What if we re-materialise these fictional scenarios in pedagogic practices? Will the learning experience benefit from it? Will this re-materialisation offer a more accessible language for computational technologies, particular in the context of art and creativity?

Preparation

I decided to plan a rolling dice activity to explore re-materialisation because it’s quick, lightweight and at entry-level. Rolling dice is a classic activity in mathematics pedagogy to demonstrate a concept called probability distribution: throw a die with 6 faces for a few times and tally the results – you’ll likely get uneven counts for each face even if the dice is perfectly fair – this is because rolling dice is always random and uncertain.

I prepared physical dice, papers, and pens. And also gave it a tweak: three out of the five dice are loaded (i.e., they are unfair and biased toward some numbers). In the activity, I asked participants to pick two dice and inspect if they were fair. They were instructed to roll the dice several times, count the results, and discuss their thoughts with the group.

I prepare printed task sheets shown below. It contains a quick brief, instructions, and two template tables for tallying the dice.

microteaching_task_sheet_zhengDownload

Delivery

The delivery on the day followed mostly according to the plan. Frst, I made some impromptu decisions on the day:

I was the first one to run the microteaching on my session, and people were sitting in quite scattered seats in the room, I decided to reorganise the space. I merged two large tables and asked everyone to join together. So this was turned into a group icebreaker – a group of two and a group of three.

Then we started the session:

  1. I distributed the printed hand-outs, and gave a quick introduction of what I teach and how this activity fit into my class.
  2. Then I briefed the participant on the activity – mostly reiterating the first few lines in the hand-out.
  3. Then I asked each group to pick a die and we dived into the dice-rolling.

Filled hand-outs collected from participants.

Reflection

One of the feedback from the participants was “I enjoyed seeing math concepts and jargon turn into familiar objects”. This prompted me to constructivist learning theories, describing how learning can happen when learners construct knowledge through hands-on activities (Narayan et al., 2013). This is something I always wanted to incorporate in my teaching.

I also see the opportunities re-materialisation can bring to the learning experience. Last year during the Mathematics and Statistics unit, I used a software dice roller that I programmed for this activity. But in this microteaching session, by turning it into a tangible activity and bringing participants to a closer space, they actively engaged in the task. And critical thinking also happened during their investigation of the dice – both groups were actively reflecting on the evidence they gained, challenging and updating their answers, and hopefully, learning something new.

References

  • Ferreira, P., 2022. Rematerialising Digital Technologies Through Critical Making, in: Proceedings of the 10th Conference on Computation, Communication, Aesthetics & X. pp. 134–147. https://doi.org/10.24840/xCoAx_2022_42
  • 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.
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Hello

Posted on 13th December 2024 by Jasper Zheng Shuoyang

This is Jasper.

I’m an Associate Lecturer 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.

List of Posts:

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