2019
DOI: 10.1080/15420353.2020.1719266
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Reactions vs. Reality: Using Sentiment Analysis to Measure University Students’ Responses to Learning ArcGIS

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Cited by 7 publications
(1 citation statement)
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“…SA was used because it provides a non-invasive method to gather information on students' emotional states by investigating behavioural traces in a learning environment based on comments and reflections (Dolianiti et al, 2019). Accordingly, complementing SA with a qualitative approach is imperative in educational research (Chauhan et al, 2019;Sivakumar and Reddy, 2017) mainly to validate and discover emotional motivation, explicit sentiment reasons (Zhou and Ye, 2020), and emotional polarity when dealing with new technology (Hixson, 2019). Whilst it is straightforward to classify students' discourse based on polarity or emotional valence, it is also imperative to determine specific emotional states such as happy, sad, and fear deemed complex (Kim and Ketenci, 2020;Al Marouf et al, 2019) to explain the findings.…”
Section: Methodsmentioning
confidence: 99%
“…SA was used because it provides a non-invasive method to gather information on students' emotional states by investigating behavioural traces in a learning environment based on comments and reflections (Dolianiti et al, 2019). Accordingly, complementing SA with a qualitative approach is imperative in educational research (Chauhan et al, 2019;Sivakumar and Reddy, 2017) mainly to validate and discover emotional motivation, explicit sentiment reasons (Zhou and Ye, 2020), and emotional polarity when dealing with new technology (Hixson, 2019). Whilst it is straightforward to classify students' discourse based on polarity or emotional valence, it is also imperative to determine specific emotional states such as happy, sad, and fear deemed complex (Kim and Ketenci, 2020;Al Marouf et al, 2019) to explain the findings.…”
Section: Methodsmentioning
confidence: 99%