The chapter presents our research aimed at providing teachers with fine-grained and contextualized feedback about students' activities in online learning environments. The rational is that teachers provided with such advanced feedback are able to better organize/revise the course content and customize that content to the students needs. Our approach is based on semantic technologies, namely ontologies and semantic annotation, which enable integration of data about students' interactions with e-learning environments, as well as interlinking of learning artifacts that were used or produced during those interactions. We have implemented this approach into a tool called LOCO-Analyst and first applied it in Learning Content Management Systems (LCMSs) as today's most often used e-learning environments. Subsequently, we further enhanced this approach (as well as the LOCO-Analyst tool) to leverage the features of advanced e-learning settings, i.e. LCMSs extended with tools for enhanced learning experience. In particular, we have studied the benefits for educational feedback provisioning that stem from integrating tools for collaborative content annotation (such as tagging, highlighting and commenting) into LCMSs. This enabled us to provide teachers with course ontology maintenance and evolution features.