3. Learner-Centered Recommendation Framework

Overview

A key challenge in today’s evolving job market is guiding individuals to expand their skills and transition into job roles that align with their career aspirations. However, providing such personalized guidance automatically remains a complex task. Our goal is to support learners in making informed decisions about up-skilling and re-skilling through an automated, responsible recommendation framework that identifies relevant job roles, matches learners to optimal career paths, and generates personalized course sequences to bridge skill gaps. We developed two recommendation models that deliver personalized and explainable course suggestions and conducted a comprehensive user study evaluating perception, quality, understanding, relevance, and trust. Furthermore, we validated our approach on real-world job market data and simulated learner scenarios, showing that targeted course recommendations significantly increase applicants’ attractiveness in the job market.

Artifacts