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Exploring values affecting e-Learning adoption from the user-generated-content: A consumption-value-theory perspective
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DOI：10.1080/0965254X.2020.1749875.png)
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摘要
En 中文
The aim of this study is to utilise the user-generated content from social media platforms and merchandise websites to explore various values affecting behavioural intention in context of e-Learning services from the consumption-value-theory perspective. This study has utilised a novel mixed-method approach based on natural language processing (NLP) techniques for the both the qualitative and quantitative analysis. This study has used user-generated content of Coursera (an e-Learning service) consisting of online reviews from Coursera-100 k-dataset and tweets about Coursera. Some of the important themes generated from the thematic-based analysis of tweets are 'value addition', 'course content', 'topic cover', 'reliability of course', 'course quality', 'enjoyed course', 'recommend the course', 'value for money', 'facilitator skills', etc. Results of the empirical study reveal that offers and deals, emotional connect, facilitator quality, course reliability, platform innovativeness, and compatibility are important predictors of behavioural intention. This study concludes with the various limitations and future directions.
Keyword:
e-Learning services
consumption value theory (CVT)
latent dirichlet allocation (LDA)
natural language processing (NLP)-based approach
topic-modeling
user generated data
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3.1
论文数:
429
被引数:
2.6K
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