Learning in structured instructional settings has been researched a great deal. As learner needs change, educators have developed a number of alternatives to traditional education, such as correspondence courses, online courses, satellite broadcasts, intensive seminars, and other methods of instructor-facilitated distance education. Despite different delivery methods, distance education classes are often based upon an instructor-as-facilitator model, like that which prevails in face-to-face instruction, and suffer from the same limitations of "instructor bandwidth" (i.e., serious restrictions on scalability). The literature shows that the size of a class is limited by instructor-student ratios. Automated systems have been proposed as a way to circumvent instructor bandwidth issues while providing learners with individualized, just-in-time instruction using digital resources. Some researchers have pointed out that automated instruction, as it is currently conceived, is not pedagogically sound.; This study examined a model of instruction that was not restricted by the limitations of instructor bandwidth and provided individuals with resources that were contextualized in a meaningful way so as to support learning. Some researchers have proposed that informal online groups are capable of facilitating meaningful social and learning interactions among very large groups of people. Online self-organizing social systems, as they called the groups, allow large numbers of individuals to self-organize in a highly decentralized manner in order to solve problems and accomplish other goals, thus supporting each other's learning.; Because these online groups are a relatively new phenomenon, little research has been conducted related to the way learning takes place in them. These groups may provide a valuable source of information about how large numbers of individuals learn in a pedagogically (and androgogically) sound way, how these groups provide an environment that supports social interaction, and how peers use resources to support each other's learning.; This dissertation describes the characteristics of Online Self-Organizing Social Systems, presents a taxonomy of types of resources that are used in Online Self-Organizing Social Systems, proposes a coding scheme for message coding of group discussion threads, offers the results of four case studies, and lays a pedagogical foundation for peer-to-peer resource supported learning.
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