As many of you know, last month BLSCI applied for external funding from an organization that recognizes exceptional faculty development programs focussed on enhancing undergraduate teaching and learning. In order to make our case for the award, we included some preliminary results from the Writing Diagnostic Assessment data. I’d like to use this post as an opportunity to share some of these results with readers to demonstrate the effectiveness of the work that many have been doing over the years and get some feedback regarding ideas for future analyses.
When looking at the data, on average, students start the semester with scores on both the expectations and writing quality variables in the “middle” range (scores around 3). When we then looked to see if students’ scores significantly improved over the course of one semester in a CIC, there were no major findings. This was because many students started the semester out scoring high (scores from 4 to 5) on many of the variables, and thus did not have any room for improvement (as measured by the diagnostic scoring criteria).
However, when we looked at students who scored in the “low” to “middle” range on all of the variables (thanks Diana for this suggestion!) we observed statistically significant increases from the beginning to the end of the semester on all variables. These increases were consistent across disciplines and schools as well. The figures below illustrate the changes we observed in the data separately for the Weissman and Zicklin Schools.
Although these results are based only on a subset of the data we’ve been able to clean, match, and analyze (~ 5,000 students), they nonetheless illustrate that the work of BLSCI in creating and implementing CICs seems to be paying off for students across the board. Although most probably knew or were able to sense this already, it’s always great to have “hard data.” We would love to hear readers’ thoughts on these findings and how you see these data stacking up next to the work you’re doing with students in your own classes. Also, as always, any general thoughts and/or questions on the assessment data are welcome.
Well, maybe not a million but a lot.
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