Employing Artificial Intelligence Applications to Evaluate Faculty Development Programs by Kirkpatrick's Model

Objectives: This study aims to explore the level employing artificial intelligence (AI) applications to evaluate faculty's reaction, learning process, behavior change process and the impact of the faculty development programs at University of Tabuk by Kirkpatrick's Model. Methodology: The researcher used the descriptive method and developed a questionnaire which was distributed to a study sample of (492) faculty members working at University of Tabuk in Saudi Arabia in 2024. Results: The results showed that the effectiveness of faculty development programs based on Kirkpatrick's Model, with varying outcomes across its evaluation levels. The Impact of the Training Program on the Organization ranks highest (Mean = 2.4501, SD = 0.59333) with a "High Possibility" rating, suggesting strong perceived organizational benefits. Reactions (Mean = 2.3963, SD = 0.59170) and Learning Process (Mean = 2.3670, SD = 0.62103) also fall into the "High Possibility" category, reflecting positive participant feedback and effective knowledge acquisition. However, Behavior Change (Mean = 2.2894, SD = 0.66252) is rated as "Medium Possibility," indicating challenges in translating learning into sustained workplace behavior. Conclusions: The findings suggest that AI provides a powerful tool for overcoming the limitations of traditional evaluation methods, offering more precise, detailed, and dynamic insights into the effectiveness of professional development initiatives. By addressing the challenges associated with data quality, algorithmic bias, and ethical considerations, University of Tabuk can harness the full potential of AI to enhance their faculty development programs, ultimately contributing to the broader objectives of educational excellence and national development outlined in Vision 2030.