Typing thoughts as I go. For reference, LM 83, Utah resident. I understand this tool is a guideline, and you aren't expecting this to be used exclusively to construct a school list, so many of my comments below might be beyond its scope. Overall, it's an awesome site, and thanks for putting all the effort in!
Filling out:
- GPA by year tool doesn't account for high school or additional years e.g. I have high school classes on my AMCAS and that is my lowest GPA, but no way to input
- Wonder if it would be of value to have number of credits too. I know you have cumulative and that is probably all that matters for a tool like this, but a 3.0 for one year at 10 credits vs 40 credits means different things.
- Not sure how the LOR from research lab is factored in?
- Assuming any scientific pubs question is for peer-reviewed papers only (no abstracts etc)
- Could be valuable to ask for abstracts, posters, presentations and the like and value is just a little less than papers
- Just finished filling it out, no question for leadership or other employment? I feel like a question for significant leadership (exclude on campus clubs) and significant employment history (especially in a different field i.e. nontrads) could be valuable.
- Confusion about hours - I put in hours up to June 2023 (so up to AMCAS submission) but there is no way to incorporate projected hours throughout the cycle. For example, my non-clinical volunteering doubles during the app cycle, I think that could be valuable to consider. Of course not weighted as much as completed hours but potentially a little?
Results:
- So it looks like, based on my stats (maybe?), the generator pulled out basically the entire T20-30 and split the first 13 in Reach and the rest in Target.
- the exception is UCSF, which appeared in Target. Not sure how that happened, maybe because their MCAT appears to be a 516.
- On second look, the reach was all schools with MCATs of 521-522 with the exceptions of Stanford and Cornell. Whatever protections those two schools have from falling into Target, would apply the same to UCSF.
- Baseline group looks the most interesting to me. I got Colorado, USF, Hofstra, BU, Brown. This grouping is fascinating, and I wonder what the methodology to produce this was? Was it just a random sampling of schools with stat ranges in the middle of the pack?
- Schools I applied to that fit this category were BU, Brown, UMass, Wisconsin, Tufts, Rochester, Iowa and Dartmouth
- No TMDSAS schools for me. Do these schools only populate if you chose Texas as state of residence? My understanding is schools like Baylor and UTSW are OOS friendly
- Tool seems have done an excellent job with state bias school reduction. For example, UWashington was not recommended even though it is highly ranked. I imagine this was a deliberate outcome from the tool because I am not in a WWAMI state?
- However, my state of residence is Utah (which I put in) and the University of Utah did not populate for me anywhere (imagine it should appear in Target). Did the discrepancy between my stats and the school's medians remove it?
- I got 12 in Reach, 10 in Target, 5 in Baseline. In reality, I:
- Applied to all 12 in the Reach, interviewed at 9, R from 2, Ghost @1
- Applied to all 10 in the Reach, interviewed at 6, R from 2, Ghost @1
- Applied to 2 in Baseline, interviewed at 1, R from 1.
- Applied to an additional 8 that all would probably belong in Baseline except for Utah (imagine that is a Target for me) and CCLCM (CWRU sub-program)
- Tool works well!
Final thoughts and suggestions:
- Could ask applicants to self-identify prominent themes in their application at the end of the survey and use that to link them to even more schools. For example, does your application feature any of these themes and/or are you interested in programs that feature any of these themes as a focus?
- Rural health (would suggest programs like Columbia-Bassett or Tufts Maine Track assuming the rest of the applicant's profile matches)
- Primary care (would suggest programs like NYU Long Island)
- Research (CCLCM, schools with physician-scientist programs like Pitt PTSP)
- Engineering (Carle Illinois)
- Entrepreneurship maybe?
- Service (I am not sure what comes into this list specifically, but maybe Rush?)
- Religion (I think there are some religiously focused schools, right?
- I didn't see CCLCM, is it included in the schools list?
- If you chose the appropriate racial self-identification, do HBCU schools get added to the list?
- How does this change for MD-PhD applicants?
- Could ask applicants to self-identify significant ties to other states to see if state schools with regional bias can be added (like if you have lots of family in Oregon or something, OHSU)
- This is a really good start. I think I am not the best person to test it because applicants with my stats usually shotgun the T20s and pray for the best outcome. Where I struggled the most was finding 'mid-tiers' to round out my school list. Once you start to look at schools outside of the T30ish, the details start to become more shrouded. Which ones are OOS friendly? Are some with 'lower' stat averages kind of a big lie (UCLA lmao, though that is a T20)? And are some with a slightly lower ranking still obsessed with stats (UVA USF)? And, if I was an applicant with, let's say, a 513 and 3.75, my entire list would have to be dug out of this massive group of schools. So tweaking the Baseline group would be the biggest help IMO. I think some of the suggestions I made above could help the Baseline group generate a larger list for confused applicants.
This is awesome feedback! I'll try to see how much I can add. Here's my thoughts:
Filling Out
1. I think the best way to include high school classes is to first ask the user if they took any dual enrollment classes, and then popular that in the GPA section with an extra field. I still have to add post-bacc here as well so that will also probably be another question to ask.
2. Cumulative GPA is what is used for most of the calculation but the individual semester ones are used for calculating the upward trend. I guess I could make it even more accurate by using the credits per year to appropriately weight the upward trend. For example, 10 credits of a 3.0 followed by 16 credits of a 4.0 are stronger than 16 credits of a 3.0 followed by 16 credits of a 4.0.
3. LOR is mainly in calculating research penalties for low research hour applicants and is essentially 0 impact for those that have enough research.
4. Yeah eventually I want to expand the publication section to include things like impact factor by selecting the journal itself (as well as differentiating between CNS journals and others, etc) and including abstracts/presentations, etc.
5. Leadership is really hard to quantify because I think it has more of an impact on interviewing and converting interviews to acceptances in committee rather than getting interviews after an application. I think it makes sense for non-trads, perhaps in overcompensating lower GPAs, but this will take time to think about to see how this can be done accurately. I leaned on the conservative side with what inputs were taken because I wanted to ensure 100% accuracy and slowly add more features as I get feedback.
6. Also I guess similar to #5 where projected hours are a bit of a black box. It will take time for me to quantify what it means, how much they are worth in what sections, and what it impacts.
Results
1. UCSF gets placed in targets for certain X-factor applications, I'll have to look back at the logic to see what it exactly was. I might just default it to Reach though.
2. In a stellar application like yours, I didn't see the need to overly apply to baseline schools because there's a high probability you get lots of interviews from reach and target. The baselines that were chosen are mainly non-state school and high tier baselines I guess.
3. For now all Texas schools are reserved to Texans. Eventually I want to add an icon that shows people what schools are not recommended but still able to apply (in the case of Baylor and UTSW). The main thing with UTSW is that it's a stat lover as far as OOS (520 median) but also most applicants with those medians are not looking to go to UTSW for one reason or another. Will try to fix.
4. UWashington is reserved for WWAMI states only right.
5. In this case with high stat applicants, the state school gets removed (it has to be extremely high though). Do you think it should be default added regardless?
6. Awesome nice
🙂
Thoughts
1. Yeah eventually I want to start asking more customizability focused questions (religion, primary care, surgery, research, teaching, etc) - this will allow me to tailor the schools that show up in the main list. For example, religion-focused applications would apply to Loma Linda.
2. Isn't this a subsection of CWRU?
3. Yes HBCU's get added
4. I don't really know anything specific about MD/PhD so they're left out
🙁 It's extremely holistic, research based, more stat forgiving, way more qualitative than MD admissions.
5. Yeah so state ties is going to be pretty difficult because every school has different requirements. Some schools accept applicants who went to high school or college in that state, even if they are not a resident, while others have more strict rules. Eventually I'll just look up the schools one by one, find all the rules, and then add it
😀
6. Yeah agree, will try to see what can be changed.
