In this paper, we perform a sentiment analysis on a large set of open-ended course feedback from university courses collected between 2016 and 2019. We used the R programming language and environment for statistical computing to categorize feedback texts by their sentiment values (positive, negative). Additionally, we calculate the NRC Emotion values, which categorize the feedback according to eight basic emotions. We present analysis on the trends of how the feedback evolved through the years. Finally we compare the findings from our data to existing literature.