Understanding the affordances, effectiveness and applicability of new media in multiple contexts is usually a slow and evolving process with many failed applications, false starts and blind trails. As result, effective applications are usually much slower to arise than the technology itself. The global network based on ubiquitous Internet connectivity and its uneven application in both formal education and informal learning contexts demonstrates the challenges of effective use of new media. In this chapter the authors attempt to explicate the effective use of the Net for learning and teaching by differentiating three modes of networked social organization. These are defined as the Group, the Network and the Collective. The chapter explores the consequences of this perspective, observing that each has both strengths and weaknesses in different contexts and when used for different applications.
Web 2.0 technologies are becoming increasingly pervasive in e-learning, particularly those that might be characterised as social software. The motivation for using such systems is often pragmatic, the benefits they offer clear and intuitive often relating to increases in access. However, many existing uses of social software in education and informal learning contexts lack distinct theoretical foundations, instead drawing from work in computer mediated communication, science, psychology, sociology and related disciplines. We also note the confusion among communications and psychology theorists (Postmas, 2007) as to the extent to which the Net follows classical media theories such as clues-filtered-out (Short, Williams, & Christie, 1976) and the observations that deep personal relationships and affective interactions can and do develop (Walther, 1996). We suggest that this confusion results from trying to understand and explain the myriad forms of net-based social organization through a single lens. Rather, different forms of social organization have developed on the Net and each affords unique education and learning opportunity.
We also note that our interest in social software in education is grounded on an assumption that distributed education systems offer significantly enhanced forms and degrees of learner freedom in many dimensions. Paulsen (1993) itemized these dimensions in his Law of Cooperative Freedom. In it he postulated that systems that support learners’ freedom to negotiate not only the place of learning (as characterizes all forms of distance education) but also freedom to negotiate the time, the pace, the content, the technology and the media will more likely cater for emerging learner needs as the barriers between formal education and lifelong learning disintegrate. To these Anderson (2006) added the freedom for learners to negotiate the type of relationship with other learners and teacher, partially in response to the growing affordance of social software to support a variety of learning relationships. In our own context at Athabasca University we find these freedoms of particular relevance in that, unlike most other distance and open learning organizations, Athabacsa offers all of its undergraduate programming in unpaced, continuous intake model – affording freedom of time, space and pace. Bearing these concepts of learner freedom in mind we devised a definition of educational social software as ‘networked tools that support and encourage individuals to learn together while retaining individual control over their time, space, presence, activity, identity and relationship’ (Anderson, 2006). This and other broad definitions are perhaps a little over-encompassing, including such applications as email and traditional forums. However, the broadness of definition reminds us that social connectivity predates the Net and other communications technologies. There is a variety of other definitions of social software (see also Chapter X, this volume) but it is clear that the problems that social software addresses (meeting scheduling and documentation, building community, providing mentoring and personal learning assistance, working collaboratively on projects or problems, reducing communication errors and supporting complex group functions) have application to education use, and especially to those models that maximize individual freedom by allowing self pacing and continuous enrolment.
Social software may have the capacity to effectively leverage the knowledge contained in the minds of others in ways that easily adapt to individual and collective needs. As Bryant (2003) notes “the value of Social Software is its embedded economies of scope. The ability for an asset to adapt to new uses (its environment) without large transaction costs.” With a lower overhead in terms of top-down design, it develops a structure through the interactions and activities of its participants. For example, the use of profiles makes it easy to find like-minded people, link sharing and tagging leverages the collective discoveries of the crowd, blog posts supply a natural structure to discourse surrounding them and wikis can grow into complex documents with relatively little input from a central designer. Because the structure is determined by individuals within the community, it naturally adapts to that community’s needs and interests, at least as long as communities are not too large and diverse or where their members have poorly aligned foci.”
Key Terms in this Chapter
Web 2.0: A term referring to the trend to more interactive, user-generated Web sites. No different technologically from Web 1.0, it is about the ubiquity of user involvement rather than any particular technological change.
Group: The traditional kind of Many used in education, exemplified in the classroom. Many: A generic term describing a collection of individuals.
Network: A looser aggregation of the Many, with weaker ties and ever shifting membership, common across the Internet. Social Software: Software enabling communicaion between people in which the Many plays an active role in structuring the environment.
E-Learning: Learning mediated through electronic means, usually over the Internet.
Collective: The loosest aggregation of the Many, an amalgam of algorithm and individual activities, exemplified in tag clouds, collaborative filters and rating systems.