Learning Through a “Route Planner”: Human-Computer Information Retrieval for Automatic Assessment

This chapter presents innovative technologies for enhancing web-based strategies available to educators willing to enhance students’ self-paced and self-regulated learning processes for scientific education. Various strategies for clarifying and disseminating shared resources and structured domain models help human experts in planning appropriate educational paths for individual learners: the chapter focuses on methodologies for organizing automatic assessment resources on top of natural language metadata. Learning management systems enable interaction, content integration, and communication via collaboration tools; they are environments where instructors expand formative assessment and web-based teaching strategies in virtual communities of practice. System integrations enable to organize and dispatch digital contents: clustering techniques, formal concept analysis, natural language processing, and knowledge representation models are new means for adaptively providing students with online activities. Theoretical bases from up-to-date studies for augmenting human-computer interaction at community level start from a generic framework for e-learning systems, up to practical implications and potential of related researches.