In lifelong learning, we are expecting the participants to be able to apply what is being taught into their work. Applications to generate value is the key objectives for lifelong learning programmes. Assessment can conducted if it is on the application phase but unnecessary (but good to have) if it is to check if the participants have gained the knowledge needed from the course. In fact, mentoring might be more important as it guides participants, with an unorganized knowledge base as mentioned above, to start organizing the knowledge base and see where the applications of the knowledge are at the same time. However, this is difficult again due to cost issue. Yes, current experienced staff can be the mentor but they are already swarmed with their own work. Hiring external mentor could be a solution but again, opportunity cost for the freelancer can be high if the company only require an hour from the external mentor for guidance.
Given that my adult training experience mostly consists of only teaching new tournament directors for bridge, I'm probably slightly better qualified to talk about mentorship. And as I write this, I've just taken on my third ever intern (and second here in this role), so I don't claim deep expertise either!
Mentorship is hard, and "unorganized" is pretty much a good way of describing it. The following can all be mentorship to varying levels:
Casual chat at a networking event
More in-depth 1-1 (possibly followup from above)
"Formal" mentorship programmes (e.g. Data Science SG previously)
Long-term friendship/mentorship
Actual workplace mentorship, e.g. internship
The other reason why it's "unorganized" - mentorship is very individualized and every mentor/mentee dynamic is different:
- Context of the mentorship
Aims of the mentee (and the mentor!)
Area of mentorship
What does the mentee want? The first question will usually illuminate what the aims of the mentee are. The odds are good that they are not asking for general advice.
Do I have the right experience/expertise? Not all the time, and I'm not afraid to say so or to point the mentee to other sources.
I don't see a mentor as being the GPS system for the mentee, telling them where to go, but more of an (imperfect) map, showing possible routes that the mentor themselves already know of that the mentee might not be aware of. But first, the mentee needs to tell the mentor where they wish to get to.
The first intern I had was back in 2015, and I definitely felt the massive imposter syndrome then, being relatively junior as a data scientist myself. I recall my throught processes back then being:
Give a task which I have done before which is relatively easy, but involves the whole pipeline (data preprocessing, fitting a model, and presenting results)
Brief the task, take in any questions
Allow her to try the task without any intervention unless needed
Review, pointing out any improvements if needed
This worked pretty well, so iterating on this, my general idea would be to give a fairly good sized task using a dataset, and then let the intern work on it while providing any support when and where needed. I also like to ask questions to guide discovery, as I feel it guides the thinking processes better than just simply feeding answers. Even if the question fails, it allows me to explain the thought process I would have when approaching the problem.
That said though, actual work is half of the mentorship. Usually an intern would have decisions to make regarding next steps, e.g.: pursue a Masters degree/PhD? Stay in Singapore or go overseas? etc. Earlier this year I had to write reference letters for my previous intern, and we spent quite a bit of time previously discusisng her further plans, down to the details of which schools/programmes in the US she should be targetting. Good thing for both of us that I had some expertise/experience to advise her!
That said, it’s always good to seek mentors outside of the workplace who can bring a different perspective. It’s also useful for other soft skills that might otherwise not be so prevalent in the specific industry.
It was a tough struggle for me a decade ago when I was considering doing a PhD, and I was thankful to have both my direct supervisor, Yvonne, and also Shaowei both giving me good advice both on the actual work and on my next steps. Yvonne was very encouraging on non-PhD pathways when I made the decision to give up on a PhD, and Shaowei repeatedly gave me encouragement and feedback on my insights and ideas. I hope that I'm channeling their great mentorship as best as I can as a mentor now myself.