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Erschienen in:
How Well Do Doodle Polls Do? Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

Analysing RateMyProfessors Evaluations Across Institutions, Disciplines, and Cultures: The Tell-Tale Signs of a Good Professor

verfasst von : Mahmoud Azab, Rada Mihalcea, Jacob Abernethy

Erschienen in: Social Informatics

Verlag: Springer International Publishing

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Abstract

Can we tell a good professor from their students’ comments? And are there differences between what is considered to be a good professor by different student groups? We use a large corpus of student evaluations collected from the RateMyProfessors website, covering different institutions, disciplines, and cultures, and perform several comparative experiments and analyses aimed to answer these two questions. Our results indicate that (1) we can reliably classify good professors from poor professors with an accuracy of over 90 %, and (2) we can separate the evaluations made for good professors by different groups with accuracies in the range of 71–89 %. Furthermore, a qualitative analysis performed using topic modeling highlights the aspects of interest for different student groups.

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Vorheriges Kapitel Identifying Stereotypes in the Online Perception of Physical Attractiveness
Nächstes Kapitel Detecting Coping Style from Twitter
Fußnoten
2
The feature selection methods and the machine learning algorithms used in this study have been implemented in Python using the Sci-kit Learn machine learning library [16]. We use a maximum document frequency of 0.5 and lowercased text. We also experimented with stemming but it was found to degrade performance.
 
3
In each of these figures, the topic distributions for a group add up to 100 % (e.g., the blue/dark and yellow/light columns in Fig. 3 each add up to 100 %).
 
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Metadaten
Titel
Analysing RateMyProfessors Evaluations Across Institutions, Disciplines, and Cultures: The Tell-Tale Signs of a Good Professor
verfasst von
Mahmoud Azab
Rada Mihalcea
Jacob Abernethy
Copyright-Jahr
2016
Buch
Social Informatics

Print ISBN: 978-3-319-47879-1

Electronic ISBN: 978-3-319-47880-7

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-47880-7_27

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