Mass Collaboration and Learning: Opportunities, Challenges, and Influential Factors

Learning ecosystems can benefit from mass collaboration where large numbers of minds collectively drive intellectual efforts to learn in the form of knowledge building and sharing. Mass collaborative learning represents a significant shift away from traditional teacher-centered approach towards a self-directed model in virtual communities in which contributing members take on creative roles to maximize their learning and that of their peers. In order to design, implement, and exploit such a learning approach, influencing constituents should be identified, and appropriate conditions need to be provided. This study aims to systematically review recent literature with a view to identifying relevant affecting constituents and success factors for mass collaboration and learning—namely, the type of organizational structures, collaborative learning techniques, adopted technologies, and methods for evaluating the quality of both members’ performance, and co-created knowledge. Therefore, 100 related papers are collected, and their findings are critically evaluated. The results of evaluation are then addressed and discussed.

Creating Virtual Communities That Work

The use and import of virtual collaboration (VC) has increased at an exponential rate. Despite its potential advantages, however, VC continues to be hindered by feelings of distrust, detachment, and even isolation among virtual team members. For each of these reasons, the present study analyzed more than 1,500 survey responses to develop best practices for current users and developers of e-collaboration software. More specifically, this study used an expanded variation of Vorvoreanu's (2008) Website Experience Analysis (WEA) to explore participants' views of the seven most popular VC programs in use today: Basecamp, Dropbox, Google Drive, iDoneThis, Join.me, Skitch, and Skype. Qualitative results of this study revealed the significance of (1) name recognition, (2) interpersonal facilitation, (3) clarity/simplicity, (4) cost consideration, and (5) mobile accessibility. The study's results were then used to develop five corresponding implications for both users and developers: (1) increased integration, (2) expanded physicality, (3) supplemental training, (4) financial entrée, and (5) utilized flexibility.

How to Manage Virtual Communities and Teams using Adjacencies

This paper aims at responding to the need for specific management of virtual entities. It proposes a flexible process based on Functional Analysis and Adaptive Structuration Theory, called Virtual Entities Management Support (VEMS). Starting from environmental requirements analysis, the method helps to choose functions, attitudes, and tools based on a strategic vision in three dimensions: the virtual entity value addition, the members' satisfaction, and the entity flexible frontiers. It leverages the powerful concept of adjacent individuals and adjacent communities inside the 3-D model. The full process is detailed and applied to five virtual entities inside and outside the industry. It raised a common view of 21 best attitudes. The paper provides managerial guidelines to managers of virtual entities.

Towards an Affordance-Based Theory of Collaborative Action (CoAct)

Collaborative Action provides a novel approach to modeling interaction among users and machines and IT-mediated collaboration among people to solve problems. CoAct extends the notions of affordance and moves away from idiosyncratic, subjective mental models of the world to the notion that actors with similar capacities to act can potentially discern similar action possibilities in the world. It changes the direction from discovery and alignment of internal representations to mutual attunement of collaborators to build sufficient capabilities, share informational structures, and calibrate selectivity to achieve shared affordances. CoAct has the potential to influence such diverse areas as usability engineering, information overload, and group decision making. CoAct can be used at multiple levels of granularity, from fine granularity of a single interaction to tracking intermediate progress and results of a set of interactions. Propositions based on CoAct are presented. An initial experiment provides some support for an affordance-based approach to information sharing/design.