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nderstanding AI tool engagement: A study of ChatGPT usage and word-of-mouth among university students By PLS Algorithm

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dc.contributor.author Toma, Hozaifa Afroz
dc.date.accessioned 2026-05-23T09:55:49Z
dc.date.available 2026-05-23T09:55:49Z
dc.date.issued 2025-01-11
dc.identifier.citation SWT en_US
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/17228
dc.description Thesis Report en_US
dc.description.abstract This study examines how university students use ChatGPT, focusing on factors including system quality, personalization, trust, and satisfaction. This study examines the effects of these factors on students' behavioral intentions and word-of-mouth recommendations. Partial Least Square (PLS, is a method for survey and data analysis. The results show how crucial customisation and trust are to increasing user satisfaction and encouraging repeat use. Word-of-mouth is discovered to have a substantial impact on this adoption. Even with ChatGPT's many benefits, Data privacy issues still remain despite ChatGPT's several advantages. It provides suggestions for enhancing AI driven educational resources, notably around the user interface, ensuring it is safe, visualised, relevant and of great quality. en_US
dc.description.sponsorship DIU en_US
dc.language.iso en_US en_US
dc.publisher Daffodil International University en_US
dc.subject Student Engagement en_US
dc.subject ChatGPT Usage en_US
dc.subject Word-of-Mouth (WOM) en_US
dc.subject PLS-SEM (Partial Least Squares) en_US
dc.title nderstanding AI tool engagement: A study of ChatGPT usage and word-of-mouth among university students By PLS Algorithm en_US
dc.type Thesis en_US


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