Predicting the actual use of artificial intelligence features of Apple Vision Pro using PLS-SEM.
Saved in:
| Title: | Predicting the actual use of artificial intelligence features of Apple Vision Pro using PLS-SEM. |
|---|---|
| Authors: | Al-Maroof, Rana Saeed1, Tawafak, Ragad M.2, Al-Rahmi, Waleed Mugahed3 waleed.alrahmi@dau.edu.sa, Alhashmi, Khadijah Amru4, Alyoussef, Ibrahim Yaussef5 |
| Source: | Contemporary Educational Technology. Jul2025, Vol. 17 Issue 3, p1-20. 20p. |
| Subject Terms: | *Artificial intelligence, *Educational technology, Innovation adoption, Wearable technology, Mathematical models |
| Abstract: | Despite the spread of artificial intelligence (AI) tools and applications, the Apple Vision Pro (AVP) stands out for its innovative features compared to other types of wearable technology. Moreover, traditional glasses have been deficient in incorporating many AI innovations that could enhance user experiences and pose new challenges. In response to these innovative aspects, this study aims to develop a theoretical model by integrating constructs from the expectation confirmation model (ECM) (expectation confirmation and satisfaction [SAT]) and aspects from the Uses and Gratifications (U&G) theory. The perceived human likeness of AI mediates the model. This study focuses on the educational domain, aiming to assess how this technology enhances the academic environment and improves learning outcomes. The method used was a survey distributed among 134 participants from Al Buraimi University College, Oman, for two departments: English, linguistics, and information technology. The study consists of seven hypotheses to emphasize the conceptual model. The findings significantly impact predicting the actual use (AU) of AI features of AVP, indicating that users' expectations and SAT play a pivotal role in technology adoption and are closely linked to the variable human likeness. Similarly, factors such as entertainment value, informativeness, and the lack of web irritations significantly influence technology adoption and are associated with the human likeness variable. However, Informativeness gratification failed to pass the proposal and showed a negative indicator for predicting the AU of AI. The implications drawn from these results suggest that educational institutions should tailor their courses and curricula to promote the effective use of AI. [ABSTRACT FROM AUTHOR] |
| Copyright of Contemporary Educational Technology is the property of Bastas Publications and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
Be the first to leave a comment!
