Yesterday I reviewed the feedback from my undergraduate data modeling class and summarized the results to present back to the students. I was very impressed by the maturity of their responses. The students were really concerned with their ability to learn the material and this was reflective of their feedback. They responded favorably to the rigor required for the class and the value they are gaining from the course. Students enjoy the in-class practice exercises and going through the "answer key" in class so they understand their gaps.
I also received contradicting suggestions for improvement that I will have to ask the class about. Some students wanted me to spend more time discussing the material in the book while others wanted to spend more time working on in-class exercises. Also, similar to what I typically see, there were disagreements from students in the pace of the class where some students liked the pace, some wished that I go through the material quicker, and others would like for me to go slower.
There are two things I found that I need to work on in this class. The first is the students feel that some of the data models we work on in class are unrealistic and would like to have more real life examples. The second is they would like more interactive lectures and have me make them answer the questions I pose to the class. Both of these are valuable lessons that I hope to improve upon in the second half of the class.
I learned a lot from this survey. I'm glad I asked the students their opinions. While some of their suggestions I did not mention here were counter to productive learning, most of their feedback was very useful and I plan to adjust to help the students learn and apply the material from the class.
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