International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

Frequency: 12
line decor
  
line decor

 Volume 11, Issue 11 (November 2024), Pages: 19-27

----------------------------------------------

 Original Research Paper

Future expectations for faculty roles at Yarmouk University in light of AI-based learning

 Author(s): 

 Miesam Fawzi Motiar Al Azam *

 Affiliation(s):

 College of Education, University of Hail, Hail, Saudi Arabia

 Full text

  Full Text - PDF

 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0009-0005-1197-944X

 Digital Object Identifier (DOI)

 https://doi.org/10.21833/ijaas.2024.11.003

 Abstract

This study aimed to examine future expectations for faculty roles at Yarmouk University in the context of artificial intelligence (AI)-based learning. Using a descriptive approach, the researchers employed a questionnaire as the primary tool, with a sample of 140 faculty members from the College of Education. Results indicated that the first category, related to teaching methods, received a weighted average of 4.55, indicating strong agreement. Similarly, the second category of communication scored a weighted average of 4.57, which also reflects strong agreement. The third category, focusing on technical performance, achieved a weighted average of 4.59, showing strong agreement, while the fourth category, addressing educational activities, received a weighted average of 4.58, indicating strong agreement. Overall, the combined categories had an average weighted score of 4.58, suggesting strong agreement on the roles of faculty members at Yarmouk University within an AI-based learning environment. Additionally, significant differences emerged among respondents based on gender, college affiliation, and years of experience; however, no significant differences were found based on academic rank.

 © 2024 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

 Faculty roles, Artificial intelligence, Teaching methods, Technical performance, Educational activities

 Article history

 Received 13 June 2024, Received in revised form 12 October 2024, Accepted 19 October 2024

 Acknowledgment

The author extends their gratitude to the Faculty of Education, University of Hail, Saudi Arabia, for their support. Special thanks to the study participants at Yarmouk University whose insights and feedback enhanced this research.

 Compliance with ethical standards

 Ethical considerations

Informed consent was obtained from all participants, and their anonymity and data confidentiality were ensured throughout the study.

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Al Azam MFM (2024). Future expectations for faculty roles at Yarmouk University in light of AI-based learning. International Journal of Advanced and Applied Sciences, 11(11): 19-27

 Permanent Link to this page

 Figures

 No Figure

 Tables

 Table 1 Table 2 Table 3 Table 4 Table 5 Table 6 Table 7 Table 8 Table 9 Table 10 Table 11 Table 12 Table 13 Table 14 

----------------------------------------------   

 References (17)

  1. Albasalah A, Alshawwa S, and Alarnous R (2022). Use of artificial intelligence in activating the role of Saudi universities in joint scientific research between university teachers and students. PLOS ONE, 17(5): e0267301. https://doi.org/10.1371/journal.pone.0267301   [Google Scholar] PMid:35507571 PMCid:PMC9067665
  2. Aldosari SAM (2020). The future of higher education in the light of artificial intelligence transformations. International Journal of Higher Education, 9(3): 145-151. https://doi.org/10.5430/ijhe.v9n3p145   [Google Scholar]
  3. Almasri F (2024). Exploring the impact of artificial intelligence in teaching and learning of science: A systematic review of empirical research. Research in Science Education, 54: 977-997. https://doi.org/10.1007/s11165-024-10176-3   [Google Scholar]
  4. Chang WY (2019). A data envelopment analysis on the performance of using artificial intelligence-based environmental management systems in the convention and exhibition industry. Ekoloji Dergisi, 28(107): 3515-3521.   [Google Scholar]
  5. Chiu TK (2024). Future research recommendations for transforming higher education with generative AI. Computers and Education: Artificial Intelligence, 6: 100197. https://doi.org/10.1016/j.caeai.2023.100197   [Google Scholar]
  6. Çiftci S, Güneş E, and Üstündağ MT (2010). Attitudes of distance education students towards web based learning–A case study. Procedia-Social and Behavioral Sciences, 2(2): 2393-2396. https://doi.org/10.1016/j.sbspro.2010.03.343   [Google Scholar]
  7. Guttman L (1945). A basis for analyzing test-retest reliability. Psychometrika, 10: 255-282. https://doi.org/10.1007/BF02288892   [Google Scholar] PMid:21007983
  8. Haenlein M, Kaplan A, Tan CW, and Zhang P (2019). Artificial intelligence (AI) and management analytics. Journal of Management Analytics, 6(4): 341-343. https://doi.org/10.1080/23270012.2019.1699876   [Google Scholar]
  9. Kazanidis I and Pellas N (2024). Harnessing generative artificial intelligence for digital literacy innovation: A comparative study between early childhood education and computer science undergraduates. AI, 5(3): 1427-1445. https://doi.org/10.3390/ai5030068   [Google Scholar]
  10. Muqeeti S (2021). The reality of employing artificial intelligence and its relationship to the quality of performance of Jordanian Universities from the faculty's perspectives. M.Sc. Thesis, Middle East University, Amman, Jordan. 
  11. Ng DT, Leung JK, Su J, Ng RC, and Chu SK (2023). Teachers’ AI digital competencies and twenty-first century skills in the post-pandemic world. Educational Technology Research and Development, 71: 137-161. https://doi.org/10.1007/s11423-023-10203-6   [Google Scholar] PMid:36844361 PMCid:PMC9943036
  12. Ocaña-Fernández Y, Valenzuela-Fernández LA, and Garro-Aburto LL (2019). Artificial intelligence and its implications in higher education. Propositos Y Representaciones, 7(2): 553-568. https://doi.org/10.20511/pyr2019.v7n2.274   [Google Scholar]
  13. Pearson K (1895). VII. Note on regression and inheritance in the case of two parents. Proceedings of the Royal Society of London, 58(347-352): 240-242. https://doi.org/10.1098/rspl.1895.0041   [Google Scholar]
  14. Popenici SA and Kerr S (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12: 22. https://doi.org/10.1186/s41039-017-0062-8   [Google Scholar] PMid:30595727 PMCid:PMC6294271
  15. Rahiman HU and Kodikal R (2024). Revolutionizing education: Artificial intelligence empowered learning in higher education. Cogent Education, 11(1): 2293431. https://doi.org/10.1080/2331186X.2023.2293431   [Google Scholar]
  16. Seo K, Tang J, Roll I, Fels S, and Yoon D (2021). The impact of artificial intelligence on learner–instructor interaction in online learning. International Journal of Educational Technology in Higher Education, 18: 54. https://doi.org/10.1186/s41239-021-00292-9   [Google Scholar] PMid:34778540 PMCid:PMC8545464
  17. WEF (2020). Annual report 2019-2020. World Economic Forum. Available online at:  https://www.weforum.org/publications/annual-report-2019-2020/