Ubiquitous learning involves a large-scale service network organized as a social infrastructure. These environments weave together context service dissemination, learner profiling as well as autonomic control of the induced network traffic. The objective of the research presented in this paper is to derive a Quality of Service aware model of ubiquitous learning services based on typical learning schemes. These pedagogical patterns are designed to match various learning situations in terms of learning context, learner profile and network infrastructure. They particularly represent classes of services in ubiquitous learning environments to prioritize traffic so that less important traffic does not consume network bandwidth and slow down or halt the delivery of more important traffic. We analyze formally and empirically the network traffic requirements of a proposed learning service quality controller to support providers of learning services allocating resources in a pervasive learning environment.