  Student evaluations of teaching (SET) are commonly used in universities for
assessing teaching quality. However, previous literature shows that in software
engineering students tend to rate certain topics higher than others: In
particular students tend to value programming and software construction over
software design, software engineering models and methods, or soft skills. We
hypothesize that these biases also play a role in SET responses collected from
students. The objective of this study is to investigate how the topic of a
software engineering course affects the SET metrics. We accomplish this by
performing multilevel regression analysis on SET data collected in a software
engineering programme. We analyzed a total of 1295 student evaluations from 46
university courses in a Finnish university. The results of the analysis
verifies that the student course evaluations exhibit similar biases as
distinguished by previous software engineering education research. The type of
the course can predict a higher SET rating. In our dataset, software
construction and programming courses received higher SET ratings compared to
courses on software engineering processes, models, and methods.
