The Harriet W. Sheridan Center for Teaching and Learning
Large Class Early Student Feedback
This confidential process, which aims to gather qualitative student feedback early to mid-semester, provides instructors of large courses (i.e., 35 or more students) with actionable, learner-centered data to help inform teaching practices and classroom engagement when the insights can still be used to improve student learning.
Brown faculty who have participated in the pilot program have expressed high praise for the efficacy and ease of this process, as well as the positive impact on student performance and morale:
"While I have used Canvas-based mid-semester feedback surveys in the past, I appreciated the more granular responses provided by the Sheridan team's facilitation. I believe that the very act of undertaking this more structured approach demonstrated to students my seriousness of intent with respect to seeking candid, actionable feedback and thus, they were more vested in the process." (Social Science faculty member at Brown)
To request Early Student Feedback for Large Courses, please complete this Google form. Please note that, in the event of limited space, priority will be given to those who apply soon after the end of shopping period (September 20, 2024).
Briefly, this is a four-step process:
Early in the semester (after the first major assignment is an ideal time), a Sheridan staff member will meet or talk by phone with you to hear more about how your class is going, key goals, and questions you have. We will then talk through the process for gathering feedback and the date that we will visit your class.
On the date of your choosing, a Sheridan staff member will come to the first 10 minutes of your class. After explaining the process to your students, the staff member will prompt them to provide electronic feedback to three broad, qualitative questions: What is really helping you learn in this course? What could be improved in this course to support your learning? What could you do to improve your learning?
Over the course of the next few days, we will use a Python Notebook---a language processing tool---to generate a report of the major themes that emerged from the high volume of written responses. Leveraging this data, we will then develop a highly tailored set of class-specific statements with which your students will rate their level of agreement. This subsequent survey will be administered by a Sheridan staff member in the first 10 minutes of class one week after the first visit.
Within a week of the second visit, a Sheridan staff member will provide you with a data packet that includes a Qualtrics report, i.e., visualizations of the major patterns, including key areas of consensus and disagreement, in student responses to the survey questions administered. Along with the summary statistics from the second survey, you will receive a spreadsheet with all the raw student data collected.
After discussing this diagnostic tool and its results and implications, we will strategize ways you might “close the loop,” e.g., thank students for their feedback, note 1-2 things you could address in response, or discuss what you can’t change (and why). The individual report goes just to you, although you are welcome to share as you like.