Why you should take UQF2101J: Pursuit Of Happiness
It has been 3 whole months and wow where do I start? UQF2101J, Pursuit Of Happiness is my very first module in USP, and it did not in any way fall short of my expectations of a foundational module. Throughout this class, there were many potholes and bumps along the way. Despite the tumultuous journey, I am glad to have been able to experience a classroom setting like never before in my 14 years of education. The student-led nature of the class (instead of always being spoon-fed!) alongside Dr Charles’ constant, critical comments, has helped me learn so much more than I expected to, and even helped me reach new personal milestones! This is my very last medium post of the semester, and I’ll try my best to summarise everything I have learnt, and how much I’ve grown in this class.
QUANTIFYING MY PROGRESS
First things first, let me touch briefly on my progress throughout this entire module. I have managed to use data softwares for the first time in my life (excel, tableau etc), posted a total of 9 medium articles (including the ones in Erika’s medium on our project and this), made it onto the top post on reddit, became a writer for the Nightingale on medium, made tons of hand-drawn visualisations. My main projects included the WHR; generosity and happiness (of which Erika and I created a publication for), perceptions of happiness, food and happiness, education (on Verlyn and I’s medium), and my final individual local data story pdf on mental health in Singapore. Of course, all of which would not have been attainable without the help of Dr Charles and my classmates, and I shall elaborate on this later on.
Application
On to how I have managed to apply what I’ve learnt into my data analysis. Sure, I have learnt how to calculate correlation coefficients, linear regressions, Z test, test statistics (the list goes on), but I never really knew how to apply them and use them in our real world contexts. There were always mathematical structures to me that I had to learn and practice often to ace my exams. But in this class, under Dr Charles’ guidance, I have managed to apply and interpret all these statistical items into datasets and in real world contexts. I always thought learning math was a chore because I would eventually discard everything I learnt as time passed, but Dr Charles helped to jot my memory and helped me to use statistics contextually. I was finally able to appreciate math! And for this I am extremely grateful. This also made me very critical about the data I see. I would somehow always internally ask myself: where did the data come from? How was the data collected? Is there a hidden agenda? Did they cherry-pick? I have come to understand that such critical thinking is super important when looking at datasets.
Data visualisations
Ahh, my data visualisation journey was a wild ride, and I will elaborate more on that later on. Dr Charles will always ask ‘Is this meaningful?’ And if I were to take a shot every time he flamed meaningless data visualisations online (and even mine!), I think I would have passed out already! Hahaha. At first, I always thought that as long as the visualisation looked cool, it would be a good one. Boy was I wrong… if your visualisation is cool, but doesn’t have any narrative, your visualisation is essentially a failure (but Dr Charles always pushes us enroute to success!). I have come to understand that even the simplest data visualisations can be better than complicated ones, if they can get the point across to the layman! And isn’t the whole point of producing data visualisations for people to understand the main gist of the data easily? :)
My new toolkit
Next up would be data tools! As someone who did not even use Excel prior to this class (oh the shame…), I can proudly say that I am at least above the amateur level for softwares like Tableau! This class has managed to let me experience data tools and learnt what worked for me and what did not. (Excel and Tableau in particular are now my go-tos.) Of course, in the initial stages of this class, I have to say Tableau in particular was a major stumbling block for me. I often felt very frustrated at graphs I produced, because Tableau made it so incredibly easy to produce graphs. Personally I felt that this was a downside of Tableau- it indirectly stops you (or at least me) from doing the thinking and does it for me. This, as expected, resulted in many unintuitive graphs or graphs that were not particularly interesting. How Dr Charles helped me overcome this major stumbling block though, was by introducing me to hand-drawn visuals! He mentioned that we may not have an idea of what relationship we want to explore, or data that we want to describe, in the initial stages of our analysis. Hence one good way would be to first draw out what we want to describe first and see if it makes any sense- and this method really worked wonders for me! #nomeaninglesscharts.
My journey on Tableau was much more productive and smooth-sailing now, with this major breakthrough supplemented by a few Tableau tutorials we had in class. In fact, my proudest moment would definitely be managing to create an animated data visualisation, and I hope Dr Charles, that you are as proud too! Apart from excel and Tableau, the main softwares I used, I also managed to play around with Arcgis for map data visualisations, even tried out python on datacamp! Unfortunately, I felt that python and coding was not for me, and was glad that Dr Charles was open to us using any form of data visualisation, especially those that we were more comfortable with! Nevertheless, it was nice getting exposed to python and learning about strings, boolean, numpy etc etc in the beginner course! Apart from software, I just have to talk about the other software I used to produce data visualisations- my very own two hands!
I learnt, the hard way, that my design represents me.
People are going to notice me for the design I produced, what I produced from the data, what my data shows. A single impactful design can be groundbreaking and I felt that this was only possible if I used my hands to create meaningful visualisations before I moved on to Tableau and Excel! I have learnt that even the most boring of datasets can be made interesting if you think out of the box and represent the data in a meaningful way.
Now on to the main point of my reflection:
FAILURE IS NATURAL AND OKAY AND THE BEST WAY TO LEARN!
I really appreciate the fact that Dr Charles is super open to failure as long as we pick ourselves up and learn from it! It is because of this that I was brave enough to post all my thoughts onto slack to which he provided tons of feedback and rooms for improvement! Initially I was only fixated on posting good things on Slack, but then as the semester went on I realised that it is okay, if not great, that Dr Charles is able to see my mistakes and correct me- life is not always about being perfect, it’s okay to have imperfections! That way I can learn from it and others can too. It’s great to have the skills, but to re-skill and pick up even more skills and exploring- I find that really the essence of this class! We are always working with different datasets, new softwares. Even though sometimes I fail to find datasets, or meet a problem with a software, I’ll just have to try again! This, to me, is the best way to reskill.
To my lovely classmates…
Huge shoutout to all of you guys in this module, for all the slack posts, discussions etc etc. Especially since the semester is online, we could work not just within our class, but inter-class too! This gave me the opportunity to work with 4 people in class, Min Yi and Kok Lee on our perceptions of happiness project (thanks Dr Charles for linking us up and introducing me to working in teams!), Erika on our generosity project, and Verlyn on our final education project. The great thing about USP is being able to work with people of all majors! They all definitely provided me completely fresh viewpoints and inputs. I learnt that each major has their own specialty: some a great at coding, others analysis. It was a joy working with them all, especially since non of them are from thev faculty of science (my home faculty). I really also have a lot of people to thank in our small happiness community; Amanda, for introducing me to a Tableau tutorial and her #pharmily gang for educating me about #healthpiness, Min Yi and Erika for always posting super interesting projects (like the Airbnb and Kpop project respectively), Verlyn for always asking critical questions, Pawandeep, Shane, Norman, Yi Ying for always keeping the discussion flowing in our evening class, Christopher for always supplementing #general with memes- I could go on for hours, but I’ll spare the details :’)
Milestones
Finally let me elaborate on certain milestones that I managed to attain in this class:
My first ever reddit post! I managed to post my first ever infographic on reddit after failing to post my hand-drawn visual :(. I was quite disappointed that r/dataisbeautiful did not accept hand-drawn visuals, but I very clearly remember (and will probably remember this for life) that Dr Charles said that:
‘we’ll show those b@5t34s’!
(thank you very much for this advice Prof, I think about it whenever I’m having a hard time :’)). And I managed to garner 22.7k upvotes and ~400 comments here:
and quite a bit of reddit ‘emojis’ on my post! People left tons of comments, some constructive feedback, some negatives, some funny, and I’m really glad this class gave me the chance to venture into reddit because i would never have done it on my own! I have realised how much my data visualisations are able to make an impact on the community, and become a medium of discussion for such a huge platform like reddit. (Go check our r/dataisbeautiful, you will be sucked into the abyss, affirmative.)
I became a writer on Nightingale in Medium (really such an honour)!
Dr Charles suggested I submit one of my medium posts to the Nightingale and I managed to get added as a writer on there and I am super stoked and honoured! I managed to get in touch with one of the main editors for the Nightingale. She gave me comments, shaped my narrative, and really helped me bring my story across.
Hand-drawn data visualisations! I did not know that I had the capacity to produce so much data visualisations by hand, but as Dr Charles always says ‘keep asking questions!’ and this eventually led to the creation of my hand-drawn #localdatastory on mental health pdf that I spent an inordinate amount of time on, but that was worth it since I managed to hone my critical thinking and data skills!
Saving the best for last, my biggest milestone would definitely be one of my hand-drawn data visualizations earning a spot in Dr Charles’ office!!! (I really want to see it in its glory when I return to Cinnamon :’))
My major
Given that my major is Food Science and Technology (FST), I would also like to show y’all how this class so effectively helped me in my FST modules. For a FST kid like myself, we often have to look through a lot of research papers. More often than not, these research papers are testing a hypothesis about a certain food product. For instance, we recently dealt with microbiology and the bacteria in food items. I poured hours into research, and felt so relieved that I could interpret majority of the numbers in the experiments conducted, and thought more critically about the data collected. Did the researchers already have a goal in mind so they only tested for a certain bacteria? Did the researchers only use a certain medium to grow the bacteria? How did the researchers present their data? Did they omit a certain data point? And I could go on but again, I’ll spare you the details…
Quantifying my success:
Indeed I have learnt a lot and grown a lot through this class. So how am I quantifying all of this? Of course, as a USP student, I just have to link all this back to CCCE.
Curious: I think I was in a perpetual state of curiousness throughout this entire module. Every time I come across a dataset I would want to explore more, every time a slack notification came in I would want to look into (or at least tried my best to) whatever my classmates had posted and were researching on, every time Dr Charles mentioned a new software or a new website I would immediately want to try it out for myself. I did not expect so much self-exploration in this class, and I found myself constantly wanting to know more.
Critical: I have come to become very mindful of everything I came across. Analysis, data collection method, data cleaning method. From Dr Charles’ questions I understood that perhaps there was something I’m missing out, and hence I was not as critical as I needed to be. I made sure to be more critical when I worked on another project.
Courageous: I felt that I’ve grown the most in this area. I’ve got to admit, I was quite intimidated by my classmates when I entered this class. Like I mentioned, I barely worked with excel before, and my classmates were using Python, R ad doing coding- I was afraid that my work could not match up to others. However, Dr Charles emphasised on progress!!! I slowly became more daring to post my work on slack, and eventually found my preferred data visualisation style! Only by being courageous could I delve into the world of QR.
Engaged: Although many of my classmates were proficient in other platforms, one platform we all started at the same level at was tableau! I devoted a lot of time tableau (…and i mean a lot), shared the steps as to how to do certain things on tableau. I remember helping Kok Lee with creating a data animated visualisation and was so glad that he managed to figure it out! I also tried to share as much as I found helpful to others as possible, such as the alternative to vlookup on excel (using conditional formatting), and the countif function etc.
So quantifying my success in this class? If you liken success to a jar of water, I would have overflowed! This module was a huge success!
A throwback
I still remember going for my USP interview in January of this year (boy does time fly) and telling my interviewers that I heard of this module ‘Pursuit Of Happiness’ and thought it would be super cool and interesting to take. And I also remember panicking when round 3 results were released because I could not secure this module (I blame my luck…) and had to email in to the USP office for this module. I sat in for the first class despite not being allocated it (thank you Dr Charles for allowing me in), and really enjoyed the first lesson and how chill the class vibe was. Although the class did not turn out to be how I expected it to be, although I often tripped over the potholes and tumbled over the bumps, I am really really glad that this was my first USP module! Dr Charles was always there to give me a band aid and pick me up whenever I needed it and guided me in the right directions.
If I were to choose an analogy for our class, I would say that UQF2101J is like the Great Wall Of China. I came into this class thinking I would pursue happiness, that the hike would be do-able. Though the first few weeks our #topic centred around #happiness, we deviated into #ANYdata after we got more comfortable with data as a result of playing around with the World Happiness Report. And safe to say, my #happiness did not come from the pursuit of it, it did not come from the completion of the Great Wall. It came from every step I progressed, and every scenic view I took in as a result of my progress. Of course, ideally, reaching the end would be great. But just like how it takes 18 months to walk the entire length of the Great Wall, it would probably take a long time for me to become a #MASTERofdata. There are endless datasets, countless softwares, so many ways to present our data and forever room for improvement. But the point of this class was to make steps of achievements along the way, and I have come to eventually love data!
One final thing…
As today marks the end of UQF2101J, I would like to share a personal project(?) I have been doing on my own for the past few weeks.
I was not initially going to post this but I couldn’t help but notice something: If you take a closer look at Tuesdays and Thursdays (aka days when we have class), the feelings are majority yellow/orange, with only 1 day where a experienced a negative emotion! (Apart from today, today is a sad day because QR ends today…) Coincidence? I’m inclined to believe not :’) data shows that Tuesday and Thursdays with QR are the superior weekdays! Why is my mood better on days with QR? Although our class is quite competitive (I guess you could quantify competitiveness via the number of slack posts one has?), our class is also a time where I felt unrestrained and I could really enjoy the class! Everyone, although busy with their own projects, etc, are willing to provide inputs and comment on others’ posts and give helpful feedback. I was prompted to think more, be more critical, and actually wanted to do more by everyone. Not to mention all the interesting things Dr Charles showed us every week! Hence attending this bi-weekly class was really enjoyable for me!
Aaaand this is finally the end (and also the end of my long ramble)! Just needed to give this class the credit it deserved, I really enjoyed taking this module :’). I was a good break and deviation from my other modules, as I could explore what I was interested in! Once again I would like to thank everyone for this hike together. Though the module has come to its sad end, it definitely kickstarted my #datajourney. Thank you all for the ride, and I hope to work with you guys again (apart from you Dr Charles, I still have yet to take your USS, and your inquiry, Developing Meaningful Indicators if my timetable permits hehe (I feel like I can really improve and put my data viz skills into good use here))! At the very least, I’ll have my rubik’s cubes as a poignant memory of this class… All the best for finals everyone, till next time! :)
