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- W3135850294 abstract "Recently, Computer Science (CS) education has experienced a renewed interest, driven by the demand in the fast-changing job market. This renewed interest created an uptick of enrollment in computer science courses. Increased number of students search for information about CS courses and professors. Often times, students turn to a professor's profile on online sites, e.g. RateMyProfessor.com (RMP), to read feedback and assessments made by other students. Student Evaluations of Teaching (SETs), conducted online or on paper, are widely used to assess and improve the teaching quality of professors, and to provide critical assessment of the teaching material and content. This paper studies the role of race and gender of computer science professors on their teaching evaluation by analyzing the publicly available data of over 39,000 CS professors on RateMyProfessor. We found that women are generally rated lower then men in overall teaching quality. They are also perceived lower in personality-related student feedback ratings, i.e. they perceived less humorous, and less inspirational. We also found that Asian professors are perceived to be tough graders and lecture heavy. They are also perceived to be more difficult in general." @default.
- W3135850294 created "2021-03-15" @default.
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- W3135850294 date "2021-03-03" @default.
- W3135850294 modified "2023-09-30" @default.
- W3135850294 title "The Role of Race and Gender in Teaching Evaluation of Computer Science Professors: A Large Scale Analysis on RateMyProfessor Data" @default.
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- W3135850294 doi "https://doi.org/10.1145/3408877.3432369" @default.
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