I analysed all 29,000+ Skill Futures courses in Singapore, and this is what I found
Background
Growing up in the first-world country Singapore, I was told to fear for my livelihood. We are too small. We have no natural resources. Developing our human capital is our option for survival. In 2015, the Singapore government launched the “Skills Future” ( SF ) programme to provide subsidies for selected courses, as well as providing $500 credits for Singaporeans to sign up for selected courses. In March 2024, the Singapore government is updating this programme to give Singaporeans aged 40 and above $4,000 more credits on selected courses geared towards employable skills. More details are set to be released in the coming months in 2024. With much discussion on the low usage of these SF credits to whether these courses provide any employable skills, I want to add some analytics inputs to this discussion.
Course Data
Doing what I do, I got the basic details of all 29,000+ SF courses from their website. These were the data that I was able to get : “provider_name”, “course_name”, “(course) ratings”, “(course) duration” and “(course) costs”.
After removing duplicates, I have 25,000+ unique courses that my analysis will focus on. A quick check also showed 782 unique course providers, which is an insane number of providers for the government to onboard onto the SF programme.
Next, I did some summary statistics on the full course prices ( I could not get the subsidised rates as they could only be found on the detailed course page ). The cheapest course is a $18 short-course titled “Unmanned Aircraft Basic Training” from the Singapore Polytechnic, while the most expensive course is titled “Bachelor of Medicine and Bachelor of Surgery” from NUS, at $623,364. Median cost is at $1,000 and mean costs is at $3,696.36.
I find it puzzling that the $500 SF credits can be used to offset a $600K surgery programme. In fact, there were many courses that cost more than $100K. Personally, the $500 credit feels so inconsequential to a $100K programme that it wouldn’t affect my decision to take up a course or not. I guess one may argue that every penny counts, or that the subsidy is a matter of principle in encouraging lifelong learning.
Top 10 course providers by courses they provide
Next, I looked at the top 10 course providers with the most SF courses
It is not surprising that the top 10 SF course providers are well-established Singapore educational institutions. Not only do they have many existing courses to qualify for the subsidies, they also have the necessary administrative support to clear the paperwork.
I then looked at their course cost distributions and course durations of these top 10 course providers. To make the patterns of these cost distributions more visible, I applied a logarithm function to reduce the effects that stems from the large number of outliers.
It was visibly clear that median university course prices are higher than those from polytechnic and ITE. While I thought this could be a “university premium”, I realise polytechnics also have a greater proportion of shorter courses, which may make polytechnic courses generally cheaper than longer courses from their counterparts ( For brevity, I am only analysing these three top public universities among all existing universities ). However, the ITE has both a lower median course price and larger proportion of longer duration courses, which could then suggest the price premium exists between universities and polytechnics over ITE. One possibility is that because ITE courses focus more on vocational, blue-collar skills, they are less attractive than the white-collar skill courses provided by the other top 10 course providers.
SMU is an interesting course provider. They have a low distribution of prices among their courses, but then a large number of price outliers. SMU has a larger proportion of short courses, with no courses that are more than one year long. Yet, their median course prices are not too far off from NUS and NTU. Compared to the other top 10 providers, only NUS provides a large number of less than 1 week courses with a sizable number of longer than one year courses, while the NTUC Learning Lab is the only institution with courses that last up to only three months.
Keywords Analysis
To have a better understanding the course characteristics that I found above, I wanted to analyse the keywords of courses that qualify for our SF subsidies. To do this, I cleaned up the course names to remove generic English words, remove punctuations, remove domain-less words like “certificate” and “diploma”, and made all keywords lower cases. Then, I did a simple keyword count on these processed course titles to get this list of top 10 keywords found in our current SF course titles : ‘business’, ‘digital’, ‘design’, ‘data’, ‘workplace’, ‘safety’, ‘wsq’, ‘analytics’, ‘health’ and ‘marketing’.
A word cloud generated from the course names also identified keywords such as ‘business’, ‘design’, ‘digital’, ‘safety’, ‘workplace safety’ and ‘data analytics’. Interestingly, the top keywords don’t draw out more technical roles or jobs like engineering or programming. Maybe such technical courses have more specific keywords in their titles ( such as the keywords “technology” and “machine learning” that are found in the word cloud ) that don’t get aggregated together, so I cannot say for sure if our SF courses are targeting more technical roles or not.
Doing the same analysis for universities ( 4,500 ) , polytechnics ( 6,270 ) and ITE courses ( 1,140 ), these are the list of keywords and word clouds that I was able to build. These are the keywords that are interesting to me:
- Universities — “business”, “digital”, “design”, “innovation”, “system”, “analytics”, “artificial intelligence”
- Polytechnics — “business”, “digital”, “application”, “security”, “analytics”, “engineering”
- ITE — “business”, “technology”, “design”, “services”, “electrical”, “engineering”, “maintenance”
This keyword analysis is still very superficial, as there are many nuances to consider. For example, “engineering” could have popped up as a keyword because it aggregates from a variety of different engineering courses, from software engineering to civil engineering, and some of these “engineering” courses could be very different from each other. “Security” as a keyword could potentially be for “cybersecurity”. Interestingly, the ITE courses do pop up more keywords that are more commonly linked to vocational skills, such as “electrical”, “maintenance” and “services”. Interestingly, “workplace safety” and “safety” are not found in any of these provider course title names, and this could suggest that such courses are provided by other course providers instead.
An important caveat
There is so much data and so many ways to to slice, and I could only cover a tip of the iceberg. However, I want to share something that I found about the SF programme. People interested can read the entire SF Terms of Service ( ToS ), but clause 19 of its ToS states that our government isn’t vouching for any of the course qualities that are found in this SF programme.
To be fair, it is impossible for any government to vet through such a large and diverse set of courses that they do not have expertise in. I do feel at fault for realising this only after nine years into the SF programme. However, for quite some time, I did get the impression that some of these course providers’ seem to use the SF subsidies as a way to legitimise their course by mere association, although I think none explicitly mention they had any government stamp of approval. While clause 19 makes things clear now, I feel stupid for falling for such old marketing gimmicks. I only hoped that this stand was placed on the first page of the SF site and not hidden on its ToS page.
Concluding thoughts
All in all, this was a stressful side project. The SF site is slow and difficult to navigate programmatically, making it an arduous task to get their data. Secondly, while the data felt rather sensitive to analyse, with all the muse around upskilling and unemployment, I also felt compelled to give a data-driven spin to this topic.
Most importantly, as I am qualifying for the updated SF scheme soon, I have vested interest to better understand the current system, so as to prepare for its update. Currently, I am an analytics freelancer, I would be interested to look at more technical or business centric courses to compliment my existing work, rather than to help me pivot into a new role.
In addition, I may also consider vocational skills like plumbing and electrical works courses, so as to ensure that my skills are not too anchored into a specific industry ( tech ). However, rest assured, when the updated SF scheme is up, I will be reading their updated ToS carefully this time round!
Thanks to everyone who has read this post. If you are interested in analytics side projects with a social science narrative, follow me on Medium or Linkedin. Some topics I have explored include (1) Singapore housing prices, the (2) Taiwan housing prices, and (3) I even built a small web app for Singapore residents to track the library books that they want to borrow. I also share less technical stuff, like (4) how I learned to deal with uncertainty and (5) how I ended up being a freelance analytics consultant.
Lastly, I have a Substack (trying to keep that going) as well, where I share ideas on data concepts and strategies for targeted at busy business people.
