Hey @lrnv,
First off, a HUGE thank you for these ideas! I’ll go ahead and say that I am uncertain where and if survival analyses/hazard regressions are covered in our curriculum anywhere but I could easily see these being really fun projects that perhaps some more ambitious student teams could go after – they may just need more mentorship from your side if they haven’t encountered this before. Here is the scoring rubric I am using:
- Scope of Work (1 - 10): How much work or tasks I see here for the students based on the description as well as how clearly scoped each task is.
- Project Clarity (1 - 10): How clearly described the project is.
- Alignment (1 - 10): How closely related I see this project in alignment with eligible classes at Northeastern.
- Feasibility (1 - 10): How feasible or “able to be accomplished” by a student team I see the proposed project being.
- Composite Score (4 - 40): Overall composite score with final grades of:
- “Great Fit with Minimal Revisions” for 31 - 40pts
- “Good Fit with Revisions” for 21 - 30pts
- “Possible Fit with Significant Revisions” for 11 - 20pts
- “Out of Scope” for 4 - 10 pts.
- Scope of Work: 6
- Project Clarity: 6
- Alignment: 9
- Feasibility: 3
- Composite Score: 22pts, Good Fit with Revisions
Comments: I think this is a pretty well-defined project and aligns very well with the sorts of projects that would fit into classes at NEU. What I would want to see more about is the exact methods you’d want to implement – I would say 1 - 3 methods max would probably be feasible for the teams. Additionally, what sort of data would they want to work with to validate their attempts? The reason why feasibility received a low-rank is because non-parametric methods may be unknown to students so they will most likely need additional guidance here.
- Scope of Work: 7
- Project Clarity: 8
- Alignment: 9
- Feasibility: 8
- Composite Score: 32pts, Great Fit with Minimal Revisions
Comments: I think this project is a great fit. I would say that it is outside the scope for students to create a general interface but creating a naive implementation would be a great research product. In this scenario, again, what exact datasets could be used and how might you want the students to validate their findings. If you can provide those details, this looks very great!
- Scope of Work: 6
- Project Clarity: 6
- Alignment: 7
- Feasibility: 5
- Composite Score: 24pts, Good Fit with Revisions
Comments: I think what is most unclear here is what is meant by “bindings” as having students fully understand how to compose survival outcomes with Flux will be a challenge. If you could provide additional clarity, that would be great. One of the reasons why feasibility was low is that this could be a hard problem where you might need to mentor the students more directly for this problem. I think breaking down the scope of this project more into incremental discrete steps would be very beneficial here.
Overall, I think these projects look pretty great and well-defined. There are revisions needed, but I think the major problem across all projects is to also find relevant datasets as I know the curriculum is keen on having student outcomes being not only did they develop a model, but also they applied them to X (e.g. "I developed and applied a hazard regression model from scratch to assess outcomes in diabetic patient populations). This keeps inline with the experiential aspect of the program.
I’ll be in touch on next steps!