Understanding key drivers affecting students’ use of artificial intelligence-based voice assistants
Artificial 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...
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2022
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| Online Access: | https://bspace.buid.ac.ae/handle/1234/2991 https://doi.org/10.3390/a16120549. |
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| _version_ | 1862980617543614465 |
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| author | Hamad Al Shamsi, Jawaher |
| author2 | Al-Emran, Mostafa Shaalan, Khaled |
| author2_role | author author |
| author_facet | Hamad Al Shamsi, Jawaher Al-Emran, Mostafa Shaalan, Khaled |
| author_role | author |
| dc.creator.none.fl_str_mv | Hamad Al Shamsi, Jawaher Al-Emran, Mostafa Shaalan, Khaled |
| dc.date.none.fl_str_mv | 2022 2025-05-13T13:46:10Z 2025-05-13T13:46:10Z |
| dc.identifier.none.fl_str_mv | Usman Javed Butt et al. (2023) “Predicting the Impact of Data Poisoning Attacks in Blockchain-Enabled Supply Chain Networks,” Algorithms, 16(12), p. 549. 1999-4893 https://bspace.buid.ac.ae/handle/1234/2991 https://doi.org/10.3390/a16120549. |
| dc.language.none.fl_str_mv | en |
| dc.publisher.none.fl_str_mv | Springer |
| dc.relation.none.fl_str_mv | Algorithmsv16 n12 (2023): 549 |
| dc.subject.none.fl_str_mv | Artificial intelligence · Voice assistant · Human-AI interaction · Technology acceptance · Drivers · Education |
| dc.title.none.fl_str_mv | Understanding key drivers affecting students’ use of artificial intelligence-based voice assistants |
| dc.type.none.fl_str_mv | Article |
| description | Artificial 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. |
| id | budr_9df854873e971a5475d1032cf3e8a752 |
| identifier_str_mv | Usman Javed Butt et al. (2023) “Predicting the Impact of Data Poisoning Attacks in Blockchain-Enabled Supply Chain Networks,” Algorithms, 16(12), p. 549. 1999-4893 |
| language_invalid_str_mv | en |
| network_acronym_str | budr |
| network_name_str | The British University in Dubai repository |
| oai_identifier_str | oai:bspace.buid.ac.ae:1234/2991 |
| publishDate | 2022 |
| publisher.none.fl_str_mv | Springer |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Understanding key drivers affecting students’ use of artificial intelligence-based voice assistantsHamad Al Shamsi, JawaherAl-Emran, MostafaShaalan, KhaledArtificial intelligence · Voice assistant · Human-AI interaction · Technology acceptance · Drivers · EducationArtificial 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.Springer2025-05-13T13:46:10Z2025-05-13T13:46:10Z2022ArticleUsman Javed Butt et al. (2023) “Predicting the Impact of Data Poisoning Attacks in Blockchain-Enabled Supply Chain Networks,” Algorithms, 16(12), p. 549.1999-4893https://bspace.buid.ac.ae/handle/1234/2991https://doi.org/10.3390/a16120549.enAlgorithmsv16 n12 (2023): 549oai:bspace.buid.ac.ae:1234/29912025-05-13T13:59:39Z |
| spellingShingle | Understanding key drivers affecting students’ use of artificial intelligence-based voice assistants Hamad Al Shamsi, Jawaher Artificial intelligence · Voice assistant · Human-AI interaction · Technology acceptance · Drivers · Education |
| title | Understanding key drivers affecting students’ use of artificial intelligence-based voice assistants |
| title_full | Understanding key drivers affecting students’ use of artificial intelligence-based voice assistants |
| title_fullStr | Understanding key drivers affecting students’ use of artificial intelligence-based voice assistants |
| title_full_unstemmed | Understanding key drivers affecting students’ use of artificial intelligence-based voice assistants |
| title_short | Understanding key drivers affecting students’ use of artificial intelligence-based voice assistants |
| title_sort | Understanding key drivers affecting students’ use of artificial intelligence-based voice assistants |
| topic | Artificial intelligence · Voice assistant · Human-AI interaction · Technology acceptance · Drivers · Education |
| url | https://bspace.buid.ac.ae/handle/1234/2991 https://doi.org/10.3390/a16120549. |