Opt-out option for project to develop ML/AI based summary of teaching evaluation comments

Colleagues,

Student evaluations of courses are an important element in our “continuous improvement process”.  While the questions give easily quantified data, the numbers don’t always capture the full breadth of student’s experience.  For that, the comments are commonly far more valuable.

For a small class, it is not difficult to read all the comments and get a reasonably good perspective.  But for large classes, the sheer number of comments can be overwhelming and often there is insufficient time to fully digest the data.

Kathy Dimiduk and Madeleine Udell are exploring development of a supporting tool that would provide a “summary” of the comments, looking for common threads and prioritizing the positives and the concerns.  Ultimately, such a tool might provide a bulleted list of actionable summaries that would facilitate improvements, as well as help guide a more comprehensive reading of the comments.

A group of students this semester will be working to develop first prototypes of this tool.  Past course evaluations, anonymized to remove faculty names and course numbers, will be used as the training data and to assess the effectiveness of the program.  Kathy and I met with the IRB (Institutional Review Board) to confirm that this would not be classified as a “human participatory research” project.

However, there is the potential for some personally identifiable data making it through the anonymizing filters (badly misspelled names for example).  As course evaluations can at times be sensitive issues for faculty, we wanted to give you the opportunity to opt-out and not have your prior evaluations included in the training data.  To opt-out, please fill out the Qualtrics survey at https://cornell.qualtrics.com/jfe/form/SV_3Vr8uDkxPpJEOXj

I believe that this project has the potential to be extremely valuable to all of us, providing actionable recommendations from the evaluations, and helping us do our jobs well with less effort.  I hope you agree and are willing to have your data included in the training and evaluation.  We will keep you posted with results of the initial studies.