Understanding key drivers affecting students’ use of artificial intelligence-based voice assistants

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dc.contributor.authorHamad Al Shamsi, Jawaher
dc.contributor.authorAl-Emran, Mostafa
dc.contributor.authorShaalan, Khaled
dc.date.accessioned2025-05-13T13:46:10Z
dc.date.available2025-05-13T13:46:10Z
dc.date.issued2022
dc.description.abstractArtificial intelligence (AI)-based voice assistants have become an essential part of our daily lives. Yet, little is known concerning what motivates students to use them in educational activities. Therefore, this research develops a theoretical model by extending the technology acceptance model (TAM) with subjective norm, enjoy ment, facilitating conditions, trust, and security to examine students’ use of AI based voice assistants for instructional purposes. The developed model was then validated based on data collected from 300 university students using the PLS-SEM technique. The results supported the role of enjoyment, trust, and perceived ease of use (PEOU) in affecting the perceived usefulness (PU) of voice assistants. The empirical results also showed that facilitating conditions and trust in technology strongly influence the PEOU. Contrary to the extant literature, the results indicated that subjective norm, facilitating conditions, and security did not impact PU. Simi larly, subjective norm and enjoyment did not affect PEOU. This research is believed to add a holistic understanding of the key drivers affecting students’ use of voice assistants for educational purposes. It offers several theoretical contributions and practical implications on how to successfully employ these assistants.
dc.identifier.citationUsman Javed Butt et al. (2023) “Predicting the Impact of Data Poisoning Attacks in Blockchain-Enabled Supply Chain Networks,” Algorithms, 16(12), p. 549.
dc.identifier.doihttps://doi.org/10.3390/a16120549.
dc.identifier.issn1999-4893
dc.identifier.urihttps://bspace.buid.ac.ae/handle/1234/2991
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofseriesAlgorithmsv16 n12 (2023): 549
dc.subjectArtificial intelligence · Voice assistant · Human-AI interaction · Technology acceptance · Drivers · Education
dc.titleUnderstanding key drivers affecting students’ use of artificial intelligence-based voice assistants
dc.typeArticle
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