Collaborative Learning Flow Patterns (CLFPs) formulate best practices for the orchestration of activity sequences and collaboration mechanisms that can elicit fruitful social interactions. Mobile technology features offer opportunities to support interaction mediation and content accessibility. However, existing mobile collaborative learning research has mostly focused on simple activity orchestrations from the perspective of collaborative flow orchestration and flexibility requirements, predominantly in face-to-face pre-university educational contexts. This paper proposes a particularization of the Pyramid CLFP to support flexible face-to-face and distance mobile learning scenarios in which learners interact in increasingly larger groups along a sequence of activities (Pyramid levels). PyramidApp implements this Pyramid particularization that provides both a web-based authoring tool and an enactment tool accessible through web or mobile devices. The authoring tool was evaluated in workshops where teachers appreciated its design and applicability to their educational contexts. PyramidApp flows were enacted in three higher education settings. Learners enjoyed the activities but usage and satisfaction varied depending on several design and contextual factors like the epistemic tasks given, the education level and application mode (face-to-face or distance). In this work, we present an analysis of three commonly used patterns (Pyramid, Jigsaw and TAPPS CLFPs) in small-scale settings in order to be adaptable in large learner communities. The methodology followed is analytical; more precisely, each pattern is analysed considering four dimensions, to inspect the level of pedagogical appealing within such contexts, how far it is scalable from both student and practitioner perspectives, how it is MOOC-adaptable considering much diverse and unpredictable nature of a MOOC, and finally how collaborations can be made further meaningful. As scalability we have considered the practicality and feasibility of managing the learning scenario by practitioners and the ability for learners to easily engage in the activity. We synthesise series of potential use cases expressing the applicability of CLFPs to large learner communities as a key result derived from the analytical study. Moreover, the results indicate that most encouraging prospects for scalability are from the cases of Pyramid CLFP. Consequently, Pyramid pattern is instantiated as a scalable model and technologically implemented as “PyramidApp” which has been evaluated in 13 experimentations across 4 higher educational levels varying from undergraduate to Masters’ levels including 2 studies in a MOOC. With accumulating collaborations while being scalable and preserving dynamism, PyramidApp received positive perceptions from participants. PyramidApp particularization is one example of scalable CSCL approach; yet this analytical study reveals more suggestions to design and implement scalable CSCL orchestration technologies inspired by the use cases synthesised.