Smarter Instructional Design using Data

In an era of rapid change and data overload, professors face mounting pressure to adapt their teaching strategies to meet the evolving demands of both students and the job market. This paper introduces an innovative approach to support instructional design engineers by using the Cumulative Accuracy Profile (CAP) curve to evaluate, retrain, and optimize instructional models. The proposed framework provides objective decision-making tools for improving course design and educational resource management, ensuring that learning experiences remain relevant and effective. Through real-time data analytics, this approach helps educators respond to dynamic educational needs, offering a streamlined method for continuous improvement in course development.