Enhancing Hiring Processes With E-Learning and Recommendation Systems

This chapter presents a data-driven framework for modernizing recruitment through the utilisation of artificial intelligence and e-learning analytics. The proposed 7-stage methodology leverages behavioral data from online learning platforms to assess candidate skills, motivation, and adaptability more objectively than traditional methods. Key components include automated candidate profiling, multi-source data integration, AI-powered interviews, and continuous improvement mechanisms. The approach addresses critical limitations of conventional recruitment, including human bias, inefficiency in evaluating soft skills, and information overload. While offering benefits such as improved candidate-job matching and reduced subjectivity, the chapter also examines implementation challenges, including the issue of algorithmic bias, data privacy concerns, and ethical considerations. The framework contributes to emerging research at the intersection of HR technology, educational data mining, and responsible AI