Hard data on students using W's to enhance their GPAs?

Question

I teach at a community college in California, where students can drop a course with a grade of "W" up until the 12th week of the semester. Within the last year or so, I seem to be seeing an increase in the number of students who find themselves passing the course at the 12th week, but who decide to drop because they want a better grade and are willing to take the course again later. However, I'm not sure that this increase is real, since my sample size is small. And if it is real, I don't know how widespread the phenomenon is or how to probe for possible causes for the change, since a number of different variables have changed in this time frame (including changes in state law and school policy).

Is there any source of hard data or method for getting data on this? I think there's a pretty big literature on student success and persistence, but the impression I get is that a lot of the literature takes it as a matter of definition that if the student doesn't pass the course with a C, it's because the student didn't "succeed," i.e., the student's academic performance wasn't passing. It seems like it would be difficult to gather statistically robust data to measure the phenomenon of drops due to grade dissatisfaction, since instructors aren't systematically asked to submit or retain the grade records of students who are no longer enrolled at the end of the term.

Answer 1

I've just done 15 minutes of moderately focused research, and found nothing. It looks like in most exit surveys students claim to have dropped because of family or work conflicts, which may be true but is not the acute reason for the drop for your students.

A Google search for "drop and retake" finds dozens of recommendations like this for pre-med and other highly grade-motivated students.

I'm rather intrigued, actually. If these students could be motivated to stay and get the grade, it would save the state a lot of money. And if they couldn't drop after Week 2, they might work much harder much earlier.

I sense a possible research project...

Answer 2

As far as method goes, it surely could make for an interesting study! In my recent literature review of factors predicting student success I didn't find anything about this phenomenon - but I wasn't looking for it directly, so that doesn't prove there aren't good studies about it!

But as a data point, I've regularly had professors explicitly tell students before a withdraw deadline to review their grade and if you aren't doing well or just unhappy with your performance so far, they strongly suggest you consider withdrawing from the class! I myself did it for a comm class where I unavoidably missed a few early days that guaranteed I couldn't do better than a B+ even with perfect performance, so I retook it later once I had a more stable schedule.

Now as for systematic gaining of data, you are quite right that it is difficult. A number of factors make this hard, even if we assume that the withdraw deadline is half-way through the course:

• Is the first-half of material, and performance on it, an accurate reflection of the rest of the material?
• Do later projects/papers/tests disproportionally skew one's final grade for a class, such as having the final project be worth more than the entire first half of the semester?
• Are "worst-grade drop" provisions available in the course, as when some professors give five exames but only count your four highest?
• Is the class cumulative or "increasingly difficult" in nature, where if you can not master early material you are sure to do even worse on later material? (Math classes are often this way, in my experience)
• Since students are dropping the class, by definition you don't know how they would have done had they stayed in the course!
• Can missed/failed early work be made up for, without major penalty?

Most studies I've seen simply consider those who drop or withdraw as experiment mortality and ignore it completely. On drop and/or withdraw forms at institutions I've attended they also generally don't even ask you why you are dropping, so this data might not yet be retained in any way and would have to be done as part of the experiment.

One could certainly conduct studies where simply drop/add forms are given options to indicate reason for dropping, and then use that data to try to determine if the problem is reported widely enough to merit further research?