Correlates of monotonic response patterns in online ratings of a university course

Park, Hyesook; Cheong, Yuk Fai

doi:10.1007/s10734-017-0199-9

Cited by 4 publications

(3 citation statements)

References 41 publications

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“…SRIs are also influenced by the quality of responses to SRI items. H.-S. Park and Cheong (2018) described the prevalence of monotonic (straight line) response patterns among first-year students with lower grades. This response pattern was attributed to "lower level of motivation, lack of familiarity with the course evaluation process, and/or inadequate understanding of the importance of course assessment to university decisions" (H.-S. Park & Cheong, 2018, p. 109).…”

Section: Types Of Biasmentioning

confidence: 99%

Bias in Student Ratings of Instruction: A Systematic Review of Research from 2012 to 2021

Stoesz

Jaeger

Quesnel

et al. 2023

cjeap

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Student ratings of instruction (SRI) are commonly used to evaluate courses and teaching in higher education. Much debate about their validity in evaluating teaching exists, which is due to concerns of bias by factors unrelated to teaching quality (Spooren et al., 2013). Our objective was to identify peer-reviewed original research published in English from January 1, 2012, to March 10, 2021, on potential sources of bias in SRIs. Our systematic review of 63 articles demonstrated strong support for the continued existence of gender bias, favoring male instructors and bias against faculty with minority ethnic and cultural backgrounds. These and other biases must be considered when implementing SRIs and reviewing results. Critical practices for reducing bias when using SRIs include implementing bias awareness training and avoiding use of SRIs as a singular measure of teaching quality when making decisions for teaching development or hiring and promotion.

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Section: Types Of Biasmentioning

confidence: 99%

Bias in Student Ratings of Instruction: A Systematic Review of Research from 2012 to 2021

Stoesz

Jaeger

Quesnel

et al. 2023

cjeap

View full text Add to dashboard Cite

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“…( 2020 ); Amendola and Restaino ( 2017 )); the teaching activities (see for instance Becher ( 2022 )) and the quality of the services and the students’ satisfaction (see for instance Trisihnyo and Harun ( 2021 )). Particularly important to improving education quality are the studies related to evaluating academic teaching activity and of university courses (Park and Cheong 2018 ; Guo and Yu 2020 ). They represent constructive feedback that could enhance the future student learning outcomes (Baddam et al.…”

Section: Introductionmentioning

confidence: 99%

“…Universities have defined tools able to collect information about the needs of students through which improving their satisfaction and the sentiment felt in attending the courses (Park and Cheong 2018 ). All this information are then elaborated by specific tools for defining overall ratings of courses and/or lecturers’ effectiveness (Nikolaidis and Dimitriadis 2014 ).…”

Section: Introductionmentioning

confidence: 99%

Topic based quality indexes assessment through sentiment

Frigau

Contu

2022

Comput Stat

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This paper proposes a new methodology called TOpic modeling Based Index Assessment through Sentiment (TOBIAS). This method aims at modeling the effects of the topics, moods, and sentiments of the comments describing a phenomenon upon its overall rating. TOBIAS is built combining different techniques and methodologies. Firstly, Sentiment Analysis identifies sentiments, emotions, and moods, and Topic Modeling finds the main relevant topics inside comments. Then, Partial Least Square Path Modeling estimates how they affect an overall rating that summarizes the performance of the analyzed phenomenon. We carried out TOBIAS on a real case study on the university courses’ quality evaluated by the University of Cagliari (Italy) students. We found TOBIAS able to provide interpretable results on the impact of discussed topics by students with their expressed sentiments, emotions, and moods and with the overall rating.

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Research on Online Physical Education Micro Course System Based on Improved Machine Learning

Zhang

2020

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Correlates of monotonic response patterns in online ratings of a university course

Cited by 4 publications

References 41 publications

Bias in Student Ratings of Instruction: A Systematic Review of Research from 2012 to 2021

Bias in Student Ratings of Instruction: A Systematic Review of Research from 2012 to 2021

Topic based quality indexes assessment through sentiment

Research on Online Physical Education Micro Course System Based on Improved Machine Learning

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