Record of Observation or Review of Teaching Practice
Session/artefact to be observed/reviewed: MSc Applied Psychology in Fashion’s Research Methods 1 unit
Size of student group:
Observer: Mason Silveira
Observee: Young-Jin Hur
Note: This record is solely for exchanging developmental feedback between colleagues. Its reflective aspect informs PgCert and Fellowship assessment, but it is not an official evaluation of teaching and is not intended for other internal or legal applications such as probation or disciplinary action.
Part One
Observee to complete in brief and send to observer prior to the observation or review:
What is the context of this session/artefact within the curriculum?
Lecture link: https://ual.cloud.panopto.eu/Panopto/Pages/Viewer.aspx?id=6d2c5904-58c6-4f38-b635-b12b00b04c78
This session is a recorded lecture from the 11th of November, 2023 (academic week 9). The lecture represents an introduction to statistics and covers the basics of some of the things the students will be learning (and applying) over the next 6 months. Typically, some of the students in the classroom are familiar with some of the concepts, via previous undergraduate degrees. However, the lecture material will be new to most of the students.
Please note that the students were presented with the full screen of each slide (not the presenter view as can be seen on the lecture recording).
How long have you been working with this group and in what capacity?
Given my role as the course leader of the given course, I have known the students since September 2023.
What are the intended or expected learning outcomes?
- Some instructions regarding submitting assessments
- Basics of statistics (what is statistics?)
- Descriptive vs. Inferential statistics
- The basics of descriptive statistics
- Data visualization
What are the anticipated outputs (anything students will make/do)?
Students are not asked to produce anything during the lecture. However, sections of the lecture are interactive and students are encouraged to speak out and interact with the tutor.
Are there potential difficulties or specific areas of concern?
The biggest concern is that many students may be intimidated by statistics before learning anything about it. The tutor’s role is to provide a gentle introduction to the subject without sacrificing academic integrity.
How will students be informed of the observation/review?
(not relevant since this is a recording of a previous lecture)
What would you particularly like feedback on?
Method of delivery, student interaction, and the accessibility/readability of the slides. However, other suggestions are welcome.
How will feedback be exchanged?
The feedback will be exchanged via email exchanges (via completion of the sections below) and will be discussed via a chat.
Part Two
Observer to note down observations, suggestions and questions:
Overall, this was a very effective session. Students tend to be quite anxious about stats, and this session was an approachable way of getting students more comfortable with the topic before more technical information is provided in later lectures. Young-Jin was particularly skillful at being supportive, assuring students repeatedly that at first concepts may be unclear but over the course of the unit(s) students will be able to confidently navigate statistical considerations. I appreciated that Young-Jin referred to the ‘beauty’ of statistics, and statistics as a means of ‘storytelling’, which may give students a different perspective on the concept beyond it just being purely mathematics (which may lead to apprehension).
At the beginning of the lecture Young-Jin discussed resources students could consult should they want more help with statistics, which I think was great. Most of the resources were alternative textbooks. I am not sure if this is done on Moodle, but it would be helpful for students to be signposted to relevant resources as specific topics are discussed each week. In addition to textbooks, perhaps other resources (videos, podcasts, etc) could also be discussed and provided to support students who may prefer alternative media formats.
The organization and pace of the lecture was great. There was a clear overview slide of what was to be discussed during the session, and this was revisited at various points. The pace of the session was great, and at no point did it feel like slides were rushed – this is particularly important at this stage, so students do not get overwhelmed at the outset. All slides were clear and accessible.
Young-Jin nicely posed questions to the students to facilitate engagement, and there was a lot of discussion around relevant examples taken from Business of Fashion reports. Notably the materials used were recent (e.g. State of Fashion 2023) and updated (e.g. mention of the recently published meta-analysis on the enclothed cognition) demonstrating that Young-Jin is making sure that lecture content is current.
The discussion of descriptive and inferential statistics was clear, although given the introductory nature of the lesson, perhaps some content could be covered in a later session once the fundamentals are in place. Concerning the discussion of p-values and their relation to inferential statistics, students likey do not have enough knowledge at this point to make sense of them, which Young-Jin noted (‘it may seem as if I am talking in circles…’).This is a minor suggestion, but I wonder whether it would be beneficial to keep focus on the ‘big picture’ as was the case for most of the lecture, before discussing the more technical aspects of inferential statistics. Likewise, there was a useful diagram showing the different types of statistical tests available, but I wonder whether this would be a bit overwhelming to students at this stage if it is not going to be unpacked during the session.
Towards the end of the session Young-Jin asked students if they had any questions, which they did not. In my experience students do not ask questions when prompted this way (even if they do!). Some quiz questions at this point may be useful to gauge student comprehension.
This was an excellent statistics lecture! Considering the anxiety students have around the topic, Young-Jin has nailed how to approach it in an engaging and digestible way.
Part Three
Observee to reflect on the observer’s comments and describe how they will act on the feedback exchanged:
I would like to thank Mason for the insightful and constructive feedback – I appreciate that Mason could observe certain things I have consciously developed as part of the unit (e.g., the accessibility and pacing of the delivery) but I also appreciate some of things Mason mentioned with regards to how my teaching can improve. Below, I will particularly focus on the latter subject.
As Mason wrote, my primary source of alternative resources is textbook-based. In alignment with what Mason wrote, I believe this practice can be improved in two notable ways: 1. Students can be provided with weekly resources as part of the lecture slides (while this information is provided as part of the Scheme of Work, I agree the information can be integrated with the lecture slides). 2. The resources themselves can be diversified, to include non-textbooks. I am primarily thinking of YouTube clips and statistics books aimed at the general public (I think books such as Spiegelhalter’s The Art of Statistics may be a great example, because these books do exactly what I aim to achieve in my statistics lectures – explain a complex concept using simple language!). That said, I will be slightly careful with blog posts or YouTube channels – I have noticed that in some rare occasions, some explanations of concepts and their applications in behavioural studies can be misleading (e.g., central limit theorem). All in all, I believe these directions encourage the topic of self-directed studying, which was explored as my first case study.
Given the introductory nature of the lecture, I agree that this lecture could have focused more on the “big picture”, doing without some technicalities. These technicalities can be explored later separately, in more technical lectures.
The quiz at the end is a brilliant idea. While I often start each lecture with small quizzes, there’s no hurting of adding quizzes at the end. Alternatively, learning from what I observed in Mason’s lecture, I could add a ‘summary’ slide at the end of each lecture.