Integrating Generative Artificial Intelligence, Experiential Teaching, and Learning in Higher Learning: Performance Management Course

Abstract

This study investigates how adopting Generative Artificial Intelligence (Gen AI) and experiential teaching, driven by industry participation, improved third-year undergraduate students' performance in the performance management course. It aims to integrate student participation through AI tools and industry involvement. As the industry rapidly demands multitasking graduates with creative thinking and strong ethical standards, educators must adapt their teaching methods accordingly. The approach is based on best practices in teaching and classroom assessment, helping to bridge the gap between the Performance Management syllabus, teaching strategies, and industry requirements. By integrating Klob's Experiential Learning Theory, practitioners' engagement, and Gen AI, this approach enhances real-time performance assessment, personalized learning, and feedback-based evaluation, creating a more flexible and responsive educational environment. A classroom action research approach was used to embed industry practices into assessments. Sixty-two (62) participants volunteered for the project. The study plays a crucial role in promoting collaboration between educators and industry, ensuring that curriculum content and skill development are constantly aligned with market needs. This partnership has improved academic performance and increased students' employability and preparedness for future challenges. The findings emphasize the value of an adaptive, innovative educational system that combines teaching approaches with effective performance management to foster organizational growth.