In the project, we explore the relationship between CEQ scores and course plans for similar courses on machine learning offered by different departments at LTH. We also looked at the effects of student background on CEQ scores. The courses chosen are FMAN45 from the mathematics department and EDAN95 from the computer science department. We found that FMAN45 has an overall higher CEQ score than EDAN95 even though both courses are popular with large student registrations. While the courses have very similar names and a high similarity in the course contents and assessment methods, the course plans and CEQ scores have clear differences. We attempted to establish a link between them, but failed to establish a clear one based on the available data. Moreover, we notice that student background can be a potential source of `stereotype threats'. Our exploratory study can form the starting point to further evaluate the courses using other aspects like student and teacher interviews etc.
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