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Artificial intelligence technologies in Emirati private universities: challenges and effectiveness in improving the quality of education

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  • Khaled Younis Alderbashi

Abstract

This study aimed to explore the effectiveness of using artificial intelligence (AI) technologies in improving the quality of education in Emirati private universities. It also explored the challenges hindering the use of AI technologies in Emirati private universities. It aimed to offer suggestions to handle such challenges. The researcher adopted the qualitative, quantitative and descriptive analytical approach. He used two data collection methods which are: a questionnaire and an interview. He shared the questionnaire on several WhatsApp groups that target faculty members in five Emirati private universities. 164 faculty members filled in the questionnaire. Thus, they were chosen purposively. The researcher conducted interviews with thirteen (13) faculty members chosen purposively from the latter universities. SPSS software was used to process the collected data. Based on the analysis, it was found that using AI technologies improves the quality of education in in Emirati private universities. Such use reduces the students’ dependency on faculty members for acquiring knowledge and improves the teaching methods used by faculty members. Based on the interviews, it was found that such challenges include: having concerns about the security of data and facing difficulty in developing special AI software and applications for students and faculty members. Regarding the implications of this study, the results of this study contribute to improving the quality of education in Emirati private universities because they encourage the developers of curricula in such universities to add AI-based activities to those curricula.

Suggested Citation

  • Khaled Younis Alderbashi, 2024. "Artificial intelligence technologies in Emirati private universities: challenges and effectiveness in improving the quality of education," Edelweiss Applied Science and Technology, Learning Gate, vol. 8(6), pages 2619-2640.
  • Handle: RePEc:ajp:edwast:v:8:y:2024:i:6:p:2619-2640:id:2518
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