We calculate whether a characteristic/factor is attributed to risk or success based on the historical performance for students with that factor at your institution. Most often, this analysis of historical data comes to the same conclusion that we intuitively believe. However, there are times when the historical data does not agree with human intuition, and, in an effort to not introduce human bias, we display those factors as calculated in your data.
There are a couple reasons why our factor analysis might disagree with human intuition
- Most often, factors that go against human intuition are fairly weak indicators, where the effect is not strong in either direction (but is still statistically significant). In those cases, the only students who have those factors displayed are those with very weak risk/success characteristics.
- It could also be the case that there are compounding effects of other characteristics tied to that factor which are a larger influence on risk than the factor itself. For example, based on student success literature, having a low Expected Family Contribution on their FAFSA should be considered a risk factor. However, if the subset of students who fill out a FAFSA are more successful than those who do not, the students with a lower Expected Family Contribution may be slightly more successful on average in general because filling out a FAFSA is a larger indicator of success than the details within the FAFSA. Again though, we display all factors by default so as to not introduce human bias in our analyses. Note that within the SS&E solution, your administrator can turn on/off the factors that are displayed within the solution.