Taught by: Dr. Charles Macdonald Burke
Content (Structure/Organization): -
This module is probably the least structured module I have taken so far in NUSC. It has very vague learning outcomes and every class feels like the prof is coming up with stuff on the spot. Also the grading system based on active participation in Slack and Reddit is a very unfair way to judge where students have to understand what and when to post on Reddit instead of actually focusing on learning how to make better indicators.
Accessibility and Assessment: 2
When I was bidding for this module, a lot of my friends advised against it as I had not taken any module under Prof Burke before (except USS). And after spending two weeks in his class, I soon realised why. Prof Burke has his favourites and people he knows from his QR class have a much higher chance of doing well in the module. Content wise everything is quite basic and taught from scratch (however, not much is taught and every class is just prof trying to YOLO his way through).
Manageability of Workload: 4
Workload is on a lighter side with it completely depending on how much effort you want to put in this module. However, from what I have seen with other students, bare minimum effort can get you a B+ as well.
Presence of Technical Learning:
This is a very self-driven module that requires you to learn the skills by yourself with little to no guidance from the prof (except witty remarks and reviews). In the long run, the skills taught to make indicators are somewhat useful but most of it is what you learn from your own or your peer attempts.
Ease/Difficulty of Attaining Grades:
Compared to other modules, a consistent participation in the Slack and Reddit will ensure a good grade of A or higher.
Learning Value/Recommendation: 2
I do not see myself using the skills taught in this class in future except when I might need to make a very high level indicator for a presentation (not for basic pie or bar charts)
About the Instructor:
Prof Burke seems like an intellectual and must have done some credible research but I despise his method of teaching and feedback. He does not prepare much for his classes and does little to reach out to students that are not his favourites.
Additional Comments/Word of Advice:
Please DO NOT take this module if you have not taken a module under Prof Burke before. However, if you want a chill module that doesn't require to come to class, put minimal effort and still get a B+, then I would recommend it.
Name: Ng Jia Yeong (Telegram Handle: @jy_jaywhy)
Content (Structure/Organization):
NIL
Accessibility and Assessment: 5
NIL
Manageability of Workload: 5
NIL
Ease/Difficulty of Attaining Grades:
NIL
Presence of Technical Learning:
NIL
Learning Value/Recommendation: 3
NIL
About the Instructor:
NIL
Additional Remarks:
This module doesn't lend itself well to a structured review. I've written a separate review/reflection piece to better explain how DMI works: https://docs.google.com/document/d/1yr-fTc4p1_FHpJ25blTmjck750kBoK0MPRfg3O1fBiA/edit?usp=sharing
Name: Soh Kai Xin (Telegram Handle: @kaixinsoh)
Content (Structure/Organization):
Dr Charles has a rather interesting way of teaching, so the mod doesn't actually have a specific syllabus, curriculum or structure.
There are both pros and cons to this approach.
I'll first address the negatives, since this is something that may turn a lot of students off from the module. To be clear, this is a highly unstructured module. If you're the type of person who absolutely needs structure—you need a clearly laid out syllabus from Week 1 to Week 13, with readings, assignment deadlines, instructions, guidelines, tutorials, lecture slides etc—then you probably won't like this module.
However, on the positive side, the benefit of having no structure means you have a LOT of freedom and flexibility. You can choose what you want to do—and this is something that Dr Charles actively encourages! All these may be admittedly difficult to get used to, but once you do, I found it to be quite a refreshing change from the typical type of modules/classes you have in uni, where everything is structured and rules and rigidity.
To be very honest, I'm a person who loves structure. I like routine and clear instructions, so initially, when I took this module, I did struggle a bit to find my footing. Therefore, my advice is that if you are taking this module and you're a person who craves structure like I do, try to create structure within the lack of structure.
If there's no deadlines, set your own. If there are no assignments, create your own. If there are no learning objectives, write your own.
At the start of the module, I wrote out an unofficial list of "goals" I wanted to achieve—things I wanted to learn or get out of the module, such as exposing myself to new tools/softwares like Tableau, and learning new skills, such as coding on Python (since I'm more inclined towards the arts and design).
Aalthough there are no grading rubrics, Dr Charles does tell you that the ultimate goal of the mod is to post onto Reddit and see how your visualisations fare with the public. Although this does admittedly detract from the learning value of the mod a little, I learned that the best strategy was to try to optimise for creating data visualisations that would do well on Reddit. Essentially, Redditors are your "markers", and your "KPIs" are Reddit upvotes and comments. Therefore, I set an aim for myself to post a certain number of posts on Reddit, and to have at least one post that generated over x number of upvotes.
Ultimately, what I learned is to embrace the kind of spontaneity and flexibility that Dr Charles advocates for in the module, which means being open to different types of data visualisations I could make, being open to feedback (especially negative criticism on Reddit—which is plentiful), and being open to making changes to the visualisations I created, which actually helped me to become more creative and a better designer/communicator.
Accessibility and Assessment: 4
Pretty accessible; probably about a 4/5?
Basic Excel knowledge (e.g. how to compile and clean data, make charts and graphs) would be a minimum. However, you really don't need to have a lot of prior knowledge in data analytics or data visualisations, and during the module, Dr Charles introduces you to a variety of tools available that you could use (e.g. Tableau, Flourish, Datawrapper etc).
That said, it WILL be incredibly useful if you do have knowledge or experience with some of these softwares, tools or skills. Additionally, although the focus of the module is NOT on visuals, the visual aesthetics of your data visualisation does matter, because it plays a part in influencing your audience—first, whether it will attract their attention, and second, whether it can effectively convey your message. Therefore, even though there is absolutely no need to design amazing graphics or visuals, some knowledge of design skills/tools (e.g. Photoshop) would help. However, for those who don't know graphic design / Photoshop, don't worry as it is still 100% doable! There are easy-to-use and free tools like Canva, Flourish that Dr Charles introduces during the mod. Even just basic Excel charts are perfectly alright!
Manageability of Workload: 3
Even though Dr Charles doesn't set a minimum requirement for the number of data visualisations or Slack posts you should have, I set an arbitrary number for myself to try to create at least one visualisation every x weeks, and to post on Slack (both on my channel, and on other people's channels, to provide feedback) at least once every 1-2 week(s).
Again, the emphasis is on independent learning and doing. Each and every student can work at their own pace and preference. You can choose to post a lot, or you can also choose to be more chill. The number of posts and/or how active you are does affect your grades, but I wouldn't say it is ENTIRELY dependent on that. Obviously, if you only post 1-2 posts throughout the entire 13 weeks of the mod, then you probably won't do well. But ultimately, I think it's more about the quality, not the quantity. Someone who makes 4-5 GOOD data visualisations that show thought in the development, meaningful revision based on feedback gathered from Slack and Reddit, and also garnered significant responses on Reddit (in terms of #comments / upvotes) would likely do better than someone who posts 50 data visualisations and/or Slack posts, but without much substance or effort.
Ease/Difficulty of Attaining Grades:
Again, the lack of specific rubrics and assessment breakdown makes it a little difficult to say how easy/difficult it is to get a good grade. But I think if you make an effort to show up to class, listen, participate in class discussions and/or on Slack, create a couple of good data visualisations (it doesn't have to be a lot! remember: quality > quantity) based on feedback, and post onto Reddit, you can do well.
Presence of Technical Learning:
Dr Charles will have a couple of lessons in which he covers some tools such as Excel, Tableau, Flourish, ArcGIS and Canva. I think for the AY21/22 semester, we didn't have access to DataCamp, although if you want to learn, there are plenty of free tutorials and YouTube videos where you can learn things like matplotlib, Python seaborn, or even R if you're interested.
University is all about independent learning, so you really have to take charge of your own learning. How much or how little you learn from the module (or in uni, really) depends on you! :)
You'll also learn basic data analysis skills, although it's not highly technical or complex.
Learning Value/Recommendation: 5
This mod may not be the easiest to score or to take, because it isn't like the typical uni mod you're used to, but that doesn't mean it's a bad mod, per se.
If you do take the mod, and are open to learning and embracing a different style of pedagogy, the mod can actually be extremely rewarding. Yes, the mod may not teach complex data analytics or programming, but you can learn it yourself! You're also exposed to other new tools and forms of data visualisations you may never have even heard of—for instance, have you ever heard of bivariate choropleth maps? Neither did I, but after taking this mod, I not only know what they are and how to read them, but I also know how to make them.
Beyond the technical skills you learn, I think there are also many invaluable skills that this mod, more than any other mod in uni, taught me—things like independent learning, design thinking, being open to feedback (especially negative criticism) and learning to improve based on feedback and so on.
About the Instructor:
As I mentioned above, Dr Charles is a professor with a very interesting style of pedagogy and teaching philosophy.
I know that amongst the USP community, there are some highly polarising views of his teaching—some students love it, some students hate it. This was the first module I took under Dr Charles, but I came into it with an open mind. As someone who likes clear rules and structure, the unstructured way of teaching was initially difficult, but I came to really appreciate Dr Charles' teaching.
Nowhere would you EVER find a module in USP (or even NUS) that has NO exams, tests or assignments. Instead of a final exam or test, what you're graded on are Reddit posts.
You have absolute freedom in choosing what you want to do, how you want to do it, and how much you want to do. Dr Charles keeps the mod very accessible for students without prior knowledge, so he introduces various tools ranging from basic ones like Excel and Flourish to more complex ones like Tableau and ArcGIS. Although there aren't in-depth tutorials on how to use these softwares, if you do have a question, Dr Charles is always very ready and happy to help and provide his feedback whether in class or on Slack (he replies super quickly as well, which is something I really appreciate).
Additional Remarks:
Okie this is a bit embarrassing, but I made a video on my NUS module reviews, so if you wanna see my full comments and review on UQR2215, you can watch this highly embarrassing video here: https://youtu.be/2hqdBJPBPkA?t=421
Kay, extremely long and verbose review over, but I hope this helps!! 😊❤️
Content (Structure/Organization):
If you require structure from a module, please don't take this module. Instead of giving a lesson plan the first week of the sem, Prof Charles plans his classes based on the performance and interests of the class on a given week. If a few students show interest in a certain topic, he may decide to spend more time on that topic.
The format chosen for the module deliverables is quite polarising, students tend to either love it or hate it. All projects are submitted through a personal slack channel. The slack channel acts as a blog which tracks a student's progress through out the sem. There's also no deadlines so you can post when you want, as much or as little as you want and pretty much anything you want. If you are self motivated, it's nice to have the flexibility to work on projects that interest you the most. I would mark my calender with imaginary deadlines to finish certain posts give some structure to this otherwise unstructured module.
Accessibility and Assessment: 4
This module is very accessible for students with limited background on indicators. The module focus isn't so much on that of traditional indicators that you might have heard of like the GINI coefficient or GDP. It instead teaches you to create effective measures related to any topic of your interest. Some examples include finding the best time to post on instagram or identifying the country with the loneliest people. As long as there are a few random topics that you have some background knowledge in, you have more than enough background knowledge to take this module.
Manageability of Workload: 3
Unfortunately, there is no fixed answer for this. The heaviness of the workload is highly dependent on the student taking the module. Because there are no milestone deadlines and very little guidelines for the projects, some students feel pressured to post more to "compete" with other students that are more consistent with posting on slack. While the quantity of posts don't determine your grade for this module. There is a correlation between the quantity of posts in a channel and the grade a student receives (at least based on my observation). The more you post the more there is to grade you on.
There are also students that feel that the module is chill because they only post when they feel like they have something to share. It depends...
Ease/Difficulty of Attaining Grades:
Again, the lack of specific rubrics and assessment breakdown makes it a little difficult to say how easy/difficult it is to get a good grade. But I think if you make an effort to show up to class, listen, participate in class discussions and/or on Slack, create a couple of good data visualisations (it doesn't have to be a lot! remember: quality > quantity) based on feedback, and post onto Reddit, you can do well.
Presence of Technical Learning:
Prof Charles can be quite unpredictable. Besides trying to figure out what he wants to see, focus on your learning and development too!
Learning Value/Recommendation: 5
Conveying data to an audience in a way that makes them understand why it's important is a skill that is beneficial to have. That's my biggest takeaway. You don't need to take a module to learn this though. However, if DataViz interests you, do consider taking this module.
About the Instructor:
Prof Charles can be quite harsh in his feedback but he is also elaborates why he disagrees with you and offers suggestions for how you can improve. He definitely has experience working with dataviz and with online communities that focus on dataviz.
I appreciate the format of the class because I enjoy doing my own thing but I don't think his teaching is as effective as it could be. If he gave a more elaborate introduction to the module and explained a few key things he looks out for, much fewer students would be stressed out about the deliverables.