I will admit to being just a hair about a novice when it comes to stats, but I feel like I have a decent working knowledge of things such as normal distribution, linear curves, standard deviations, etc. That said, I have a colleague who is proposing something that just doesn't make sense to me, and I'd like some input from people who know better:
I work in education, and my department recently gave midterm exams. This year, we used new assessments, and as such, we didn't know exactly what to expect in terms of how the students would perform.
The grades for some classes were about what we might have anticipated, but for several classes, the students performed much lower than similar cohorts have on past midterms. So, as a department, we agreed to apply a curve to these scores to account for the different and give a boost to the groups that struggled.
My colleague took it upon herself to spearhead the curving. While I think applying a linear curve would have been best, she felt that applying a normal distribution curve made more sense. In explaining her methodology, she writes:
"I set the standard deviation on the curve to mirror how similarly each particular group performed on each exam. However, if the top score was pushed over 100, then I modified the number slightly until the top score was at or less than 100. This, too, can be altered. If we decide that the top student should always earn a perfect/nearly perfect score, then the standard deviation can be altered to push that top score closer to 100."
Am I missing something? I didn't think standard deviation was something that could be "set," as I understood it to be a reflection of the raw data available in the sample set.
I can't find evidence anywhere online of anyone changing or modifying a standard deviation to make a curve fit a desired outcome.
Can anyone clarify what might be going on here?