"Graduates' Perspectives on AI Integration
This study aims to explore artificial intelligence's (AI) significance for graduating students and its impact on their future skills. Through a survey of Bachelor's and master’s students across diverse departments in Saudi Arabian public and private universities, we gathered 465 responses from 500 questionnaires distributed in various regions. Employing a 5-point Likert scale, the survey covered nine dimensions, including AI's influence on future skills, its integration into education, student preparedness, real-world exposure, exploration, ethical considerations, global perspectives, curricular adaptation, and communication and collaboration. To evaluate the research aim, we employed a one-sample t-test and correlation coefficients across different dimensions. This paper contributes by extensively examining the influence of artificial intelligence (AI) on graduating students in Saudi Arabia. Through a robust survey methodology, it elucidates students' perceptions of AI's impact on their future skills and education. The findings accentuate the positive attitude towards AI, recognizing its potential to enhance problem-solving, critical thinking, and adaptability. Moreover, it highlights the importance of integrating AI into education to prepare students for evolving career opportunities in a technologically advanced society. Furthermore, they believe that AI can provide them with opportunities to gain real-world experience and exposure to AI-driven industries, which can enhance their learning and future career prospects. Students express a strong interest in exploring AI-related projects and activities to build their future skills, particularly in data analysis and interpretation, which are in high demand in the job market.
Authors
- Musrrat Parveen (ORCID: https://orcid.org/0000-0002-3796-8061)
- Yusra Mohammed Alkudsi
Institutions
- King Abdulaziz University (SA)
Publication Details
- Journal
- IJERI International Journal of Educational Research and Innovation
- Published
- 2024-12-03
- DOI
- https://doi.org/10.46661/ijeri.10651
- Citations
- 5
- Primary Topic
- Online Learning and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 2.06