In the 5-min presentation video yesterday (if you haven’t seen it, it is on the Youtube channel https://www.youtube.com/channel/UC4LoD4yNBuLKQwDOV6t-KPw/videos), a question draws my attention: how to match mentors to a large number of pods, with mentors’ available time and pods’ chosen projects.
I have some naive thoughts about it :
What if we start to assume that all mentors work in the afternoon and the morning. When the student project session is in the afternoon, a mentor could mentor pods in his/her own time zone ±1 - 2 time-zone, and a time zone 7-8 time ahead (the mentor is in the morning, the pods are in the afternoon).
The projects are determined after brainstormings, and I suppose there are 5-10 projects.
Then, we score each project with the availability of mentors on that project: number of pods, etc. (with some criteria to measure the shortage and difficulty) We could also score each time zone, that identifies zones require employing mentors from other areas.
With a threshold, we select out a proportion of pods and mentors in high demand, and match for them in priority.
Then, we do a regular matching in sequence for others, with a randomized integer serial number assigned to each pod and mentor, out of fairness.
Hopefully, for a few pods un-matched, people can simply ask around for mentors willing to help in the inconvenient time, for example, at noon or at night.
In another case, hiring more mentors to cover the preferred projects might be easier in some sense.
These are my simple suggestions. There might be some unrealistic factors in it, because I did not participate in the project session myself.
Hope it helps!