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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.

This paper presents an ontological model for defining competency paths in STEM education, designed for the implementation of an adaptive system integrated in virtual communities. The model is applied for clustering materials for automatic assessment and the results are discussed.