An empirical study of teaching qualities of popular computer science and software engineering instructors using RateMyProfessor.com data

Aliaksei Kavalchuk, Alec Goldenberg, Ishtiaque Hussain

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

The employment opportunity for Computer Science (CS), Information Technology and Software Engineering and Development (SE) related occupations is projected to grow much faster than the average of all other occupations. Therefore, increase in student enrollment, retention and graduation rate is becoming very important, so is the need for effective teaching in these subjects. Many universities commonly use formal, institutional Student Evaluation of Teaching (SET) systems to measure the teaching effectiveness. After each semester, through SET, students provide feedback and comments for their courses and instructors. However, evaluations are private and only a handful people have access to these. Therefore, these evaluations cannot be utilized to create a common understanding of the students' expectations, perspective, desired characteristics of the courses and instructors. On the other hand, third party online platforms like RateMyProfessor.com (RMP) are public, solicit anonymous student feedback and host tremendous amount of data about the instructors and their courses. These platforms are also popular among students. We mined and analyzed the RMP data for some research questions, e.g.: What are the common characteristics of the popular CS instructors? How different are they for the SE instructors? Are there any examples of special characteristics, tools and techniques popular CS instructors use? We captured and analyzed more than 9,000 students' comments for over 300 CS instructors for the top 20 universities in the U.S. and Canada. The paper contributes by presenting the findings for the research questions and making the data and the scripts available for public use for future research.

Original languageEnglish (US)
Title of host publicationProceedings - 2020 ACM/IEEE 42nd International Conference on Software Engineering
Subtitle of host publicationSoftware Engineering Education and Training, ICSE-SEET 2020
PublisherIEEE Computer Society
Pages61-70
Number of pages10
ISBN (Electronic)9781450371247
DOIs
StatePublished - Jun 27 2020
Event42nd ACM/IEEE International Conference on Software Engineering: Software Engineering Education and Training, ICSE-SEET 2020 - Virtual, Online, Korea, Republic of
Duration: Jun 27 2020Jul 19 2020

Publication series

NameProceedings - International Conference on Software Engineering
ISSN (Print)0270-5257

Conference

Conference42nd ACM/IEEE International Conference on Software Engineering: Software Engineering Education and Training, ICSE-SEET 2020
Country/TerritoryKorea, Republic of
CityVirtual, Online
Period6/27/207/19/20

All Science Journal Classification (ASJC) codes

  • Software

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