The language of praise and criticism in a student evaluation survey

Stewart, Martyn

doi:10.1016/j.stueduc.2015.01.004

Cited by 22 publications

(22 citation statements)

References 29 publications

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“…means of teaching, teaching results). It aligns with Stewart's (2015) research and proves that an effective teacher plays a very important role in student achievement.…”

Section: Discussionsupporting

confidence: 84%

“…For instance, Zaitseva, Milsom, and Stewart (2013) interpreted the qualitative data from student satisfaction surveys utilizing concept mapping software. Stewart (2015) analysed the extent to which students managed language through intensification or moderation of views and highlighted the asymmetry between positive and negative feedback. Rajput, Rajput, Haider, and Ghani (2016) presented a lexicon-based sentiment analysis of students' open-ended textual feedback using word clouds visualization techniques.…”

Section: The Language Of Praise In Russian Students' Evaluation Of Tementioning

confidence: 99%

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The Language of Praise in Russian Students’ Evaluation of Teaching

Morozova

Chusovlyankin²,

Smolianina

et al. 2020

JLE

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Recent decades have seen a dramatic rise in student evaluation of teaching (SET). However, they have overwhelmingly focused on quantitative ratings, neglecting students’ written feedback. This study addresses the lack of qualitative research on SET by applying a semantic theory and computational methods for analysing the language of positive feedback comments provided by students of the Higher School of Economics (HSE) in Russia. Analysing a corpus of student commentary about teaching also contributes to the theory of pragmatics as the approach to analysing qualitative evaluations of teaching is based on the premise that students’ positive feedback can be treated as a sort of the compliment/praise speech act reflecting cultural specificity. Our findings showed that quantitatively the most common semantic pattern used by HSE students is ACTOR + (AUGMENTOR) EVALUATOR + PHYSICAL/MENTAL ACTION PERFORMED BY THE ACTOR + (AUGMENTOR) EVALUATOR. Thus, HSE students tend to praise the teacher more often than the other components of the teaching process and the teacher’s behaviour, thoughts, and feelings are viewed as more important than skills and speech.

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“…means of teaching, teaching results). It aligns with Stewart's (2015) research and proves that an effective teacher plays a very important role in student achievement.…”

Section: Discussionsupporting

confidence: 84%

Section: The Language Of Praise In Russian Students' Evaluation Of Tementioning

confidence: 99%

The Language of Praise in Russian Students’ Evaluation of Teaching

Morozova

Chusovlyankin²,

Smolianina

et al. 2020

JLE

View full text Add to dashboard Cite

show abstract

“…One interesting recent study by Stewart (2015) analyzes students' written comments in course evaluations, from a quantitative point of view, and using the Appraisal framework (Martin & White 2005). I am not aware of any large-scale automatic analysis of student evaluations.…”

Section: A Small Sample Of Interesting Projects In Sentiment Analysismentioning

confidence: 99%

Sentiment Analysis: An Overview from Linguistics

Taboada

2016

Annu. Rev. Linguist.

184

133

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Sentiment analysis is a growing field at the intersection of linguistics and computer science that attempts to automatically determine the sentiment contained in text. Sentiment can be characterized as positive or negative evaluation expressed through language. Common applications of sentiment analysis include the automatic determination of whether a review posted online (of a movie, a book, or a consumer product) is positive or negative toward the item being reviewed. Sentiment analysis is now a common tool in the repertoire of social media analysis carried out by companies, marketers, and political analysts. Research on sentiment analysis extracts information from positive and negative words in text, from the context of those words, and from the linguistic structure of the text. This brief review examines in particular the contributions that linguistic knowledge can make to the task of automatically determining sentiment.

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“…Otherwise they would have classified for offensive comments. Stewart (2015) showed evidence that the praising tendency is generally directed to the teacher's person (t+) and criticism to the product of the teacher's actions (a-). E.g.…”

Section: Written Feedback Addressing the Teacher As A Person Is Primamentioning

confidence: 99%

“…Among the few studies dealing with written comments, Alhija&Fresko (2009) and Brockx et al (2012) offer some valuable insight into quantitative aspects of free-text comments. Moreover, open-ended comments have been subject to linguistic analysis (Stewart, 2015) and were used for exploratory considerations (Hodges&Stanton, 2006;Stupans et al, 2016).…”

Section: Introductionmentioning

confidence: 99%