The Influence of AI on Training and Development among Teachers in Private Colleges: The Mediating Effect on Learning Agility on Skill Acquisition
Oman's education sector success relies on teacher quality, which requires continuous improvement in teaching and learning experiences. In this context, it is necessary to investigate the influence of artificial intelligence (AI) in training and development among teachers in private colleges on skill acquisition to achieve optimal performance for teachers, thereby enhancing student outcomes. The study's main goal was to explore the relationship between AI-driven training programs and how they influence skill acquisition, with learning agility mediating the relationship. The specific objectives were: 1) to assess the level of AI usage in training and development programs for skill acquisition among teachers working in Oman's private colleges; 2) to evaluate the mediating role of learning agility in the relationship between AI-based training and development and skill acquisition among teachers; and 3) to explore the perception of college teachers on AI tools in enhancing their ability to acquire skills through training. The study surveyed 200 teachers at 19 private colleges in Muscat, Oman, using quota sampling, focusing on 100 teachers with less than one year of experience and another 100 with more than one year of experience. The study uses a structured questionnaire with 28 demographic and Likert-scale questions and three open-ended questions and uses statistical analysis such as quartile analysis, mediation, and sentiment analysis. This study shows that the current level of AI use in college training programs is moderate. Mediation analysis revealed that AI training significantly improved the quality of skill acquisition through learning agility. Based on the knowledge gained from the results and conclusions, several recommendations were made.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-05-31
- DOI
- https://doi.org/10.5281/zenodo.15559858
- Primary Topic
- HVDC Systems and Fault Protection
- Type
- article
- Field-Weighted Citation Impact
- 0.00