Methodology/research question/duties

Methodology/data

Welch shared with me an example of the dataset he can gather. The EADA data provides total athletically related student aid, total revenues by institution, total operating expenses by institution, and total expenses by institution. At IPEDS, we can obtain total cost of attendance, per capita. However, we do not have athletically related student aid by gender, by team, by race, etc. It is only total per institution. So the idea is that Welch would crunch those numbers and provide a comparison of athletically related student aid to cost of attendance -- by region or by conference. This specifically answers the wider question we discussed out of the NY Times articles.

Research Question

1. Following from Welch's data and the NY Times piece, it seems that a research question could be: "What percentage of the cost of attendance does an athletic scholarship cover?"

2. One other potential question could be: "How much financial aid do colleges award on the basis of athletic talent?" -- with "talent" being the operative word here to tackle.

3. Another potential question with qualitative research could be: "What is athlete's perceived access to college through athletics"

4. Finally, a final question would be: developing a predictive model (e.g., considering whether athletic aid predicts persistence and graduation)?

My comments:

Qualitative - I'm not sure we will have time to gather qualitative data of athletes in time to analyze for the May 1 deadline. The symposium doesn't necessarily require completed research, but I don't know if/how we can include whatever we might gather in our thematic approach. That would also likely require IRB approval as opposed to the existing dataset out there; not to mention getting access to athletes. I agree that may make it a more substantial discussion, but maybe we should follow the KISS principle here and keep with quantitative research questions? If we go mixed methods, maybe Aaron or Jennifer can examine one of these qualitative issues to relate to access.

I certainly proposed we proceed with #1. That seems the most straightforward, and Welch may be willing to be our data/methodology man. As for #4, I believe the predictive course could be of some value -- a look at The Game of Life for some related findings of academic underperformance between athletics/non-athletes, post-graduation earnings... and a quick google search looks at SES, race, and college GPAs -- but not at athletic aid as a predictive model. It would be interesting to see if a higher athletic aid vs cost of attendance per capita led to a higher retention rate. If this is the case, Troy you may need to assist Welch with your thoughts on where you are going on this.

In the essence of time and work, I believe we should proceed with #1, and possibly with #4.

As for duties, I can tackle some literature review, the introduction, will work on editing the proposal, and can work on some theoretical framework.

Thoughts? -- Thanks! Scott