I have data from ~3500 students regarding their experiences taking an online class last year. The class consisted of a unified on-demand component and several sessions on Zoom with instructors. I didn't design the survey, but I've been given the results in a spreadsheet to analyze.
The data looks like this (each row represents a student's response):
|Instructor Name||I found the software easy to use (1-5 Likert scale response)||More Likert scale questions...||Did you use a smartphone or tablet for the course (answer can be 1 or 0)||Did you use a laptop?||Did you use a desktop?||More Likert scale questions...(This time about the live classes)||What did you find helpful about the course (long answer questions which I've coded into five categories)||What could be improved about the course? (Similarly, I've coded these into five broad categories)|
|Alex Alehead||3||2||1||1||0||4||I liked discussing the issues in breakout rooms. (Coded as 1 - online discussions)||I felt the instructor could have more clearly outlined the syllabus (Coded as 3 - instructor communication)|
I have no real experience with statistics, but it seems to me like there are things that could be discovered from this data apart from the averages and counts.
Is there a way, for example, to account for the differences between instructors when looking at course satisfaction? (My instinct tells me that a poor instructor will drag all the numbers down)
Another example: is there a way I can see if the type of, or the number of devices used affects the student's perception of the software used in the course?
Sorry for the barrage of questions! My main question is: How would you approach this data set? What tests would you run on it?