As opposed to end-of-term evaluations, mid-course (or early course) feedback allows the instructor and students to pause to take stock and make necessary adjustments to the remainder of the semester. To provide the most comprehensive insights, mid-course feedback should occur in the 4-7 week window of a 16-week course and after the first exam. Implementing effective mid-course feedback requires (1) transparent communication about the purpose of the feedback, (2) meaningful questions, and (3) changes to the course based on the feedback.

Studies demonstrate that students feel more responsibility for learning and have overall higher levels of satisfaction when an instructor effectively implements mid-course feedback (Holt & Moore, 1992; Keutzer, 1993; Peterson, 2016). Impacts on learning due to the use of mid-course feedback are difficult to measure, but the literature is clear that student affect and autonomy play an important role in readiness to learn (Engle, 2012; Tucker et al., 2003). Building a growth mindset classroom culture can alleviate some stressors and empowers students as drivers of their own learning trajectory (Fredericks, 2022). Effective mid-course feedback is one strategy in the vast array for fostering a growth mindset culture.

Capturing student feedback

If you are undertaking a significant course revision or implementation of a new teaching approach or are new to teaching, a more involved, facilitated feedback session may be warranted. In most instances, a mid-course feedback form is sufficient for identifying student perceptions, frustrations or weaknesses of the course, and what is going well. This section addresses the construction of a feedback form.

Item selection

Asking “good” questions is a crucial step to capturing meaningful feedback from your students. A combination of open-ended and close-ended (or scaled) questions will help to focus feedback and provide students with the flexibility to express ideas you may not have anticipated. You will have a higher response rate if there are fewer items, 4-5 items is an ideal length. Below you will find a list of example questions. Use and modify these as appropriate for your course and students. Items with an asterisk are taken or adapted from Yale’s Poorvu Center for Teaching and Learning.

Open-ended items

What is going well for you in this class? What are you struggling with? *
What class components are helping you learn? What is not working?*
What could you do differently to improve your learning experience in this class?*
What could the instructor change to improve your learning experience in this class?*
What have the course instructors done during lecture/lab that helped you understand the course content?
What else could the course instructors do during lecture/lab or provide in Canvas that would support your learning?
What course topics do you feel confident in? What areas are you struggling in?
What have you done to resolve these areas of misunderstanding in this course?
If you are viewing the lecture recordings, how are you using them?
What is going well in your small group work? What challenges are you encountering in your small group work?

Close-ended items

The first five items may use a 4 or 5-point Likert scale of agreement.

I am engaged in this class.*
I am doing my personal best in this course.
I am learning from the [course component]* (e.g., lectures, readings, homework exercises)
I understand what I need to do to do well in this class.*
I am concerned about my performance in this course.*
Approximately, how many hours per week are you spending on this course outside of scheduled lecture and lab?
Which of the following resources are you making use of in your study time? [Check all that apply list] E.g., AI review sessions, lecture recordings, notetaking app, printed lecture outlines
How often do you engage in the following [course component or resource]? Use relative frequency scale (i.e., Always • Very Often • Sometimes • Rarely • Never) or daily frequency scale (i.e., Every day • Most days of the week • 2-3 days a week • Once a week • Once before exams • Not at all • I’m not sure)

Technology for distribution

The table below outlines the features and limitations of available IU technologies for distributing your mid-course feedback survey. If you’re not sure which is best for you, select the technology you are most familiar with. There is one caveat: if you do not have an AI for data entry of paper surveys, do not select this method. It will take too much of your time to tabulate and then interpret student responses.