There have been a number of frameworks and models developed to support different aspects of interactive learning. Some were developed to deal with course design through the application of authoring tools, whereas others such as conversational, advisory, and ontology-based systems were used in virtual classrooms to improve and support collaborative activities. Although these methodologies have brought new processes and practices to interactive learning systems, current applications have not fully capitalized on the rising power of social computing to discover and explore the wealth of social-based information derived from the communities of practice that are formed. This article presents a comprehensive social computing framework for web-based learning environments that aims at representing a systematic means of acquiring, sharing, and using relationships effectively within an interactive learning environment so that participants can use them to create opportunities to work cooperatively in learning communities with other students. The proposed framework integrates several aspects of those relations into a decision-making criteria engine that is based on social networks and reputation systems. A description of the proposed methodology and its implementation are presented along with an example application. This research is expected to assist participants of online learning classrooms to make decisions that facilitate the exploration and discovery of co-learners while promoting increased awareness of the virtual classroom structure and information exposure given by their social presence. (Contains 3 figures, 2 tables and 2 notes.)