Adaptive AI-Driven Assessment for Competency-Based Learning Scenarios

Abstract

In the realm of competency-based education, the integration of adaptive AI-driven assessment strategies brings forth a paradigm shift in evaluating learner mastery. This chapter delves into the intricacies of designing learning scenarios that seamlessly blend pedagogy with AI algorithms to offer personalized, data-informed assessments. By meticulously selecting objectives, designing pedagogical approaches, and orchestrating learner activities, educators create a foundation for adaptive assessment. The integration of AI algorithms enhances evaluation precision, enabling real-time identification of learning gaps and strengths. This chapter delves into the application of machine learning algorithms for tailored feedback, remediation, and ongoing supervision, fostering a learner-centric environment. Through real-world cases and innovative practices, educators gain insights into crafting assessment systems that empower learners to excel in a competency-driven landscape.