The Internet has long been touted as an answer to the needs of adult learners, providing a wealth of resources and the means to communicate in many ways with many people. This promise has been rarely fulfilled and, when it is, often by mimicking traditional instructor-led processes of education. As a large network, the Internet has characteristics that differentiate it from other learning environments, most notably due to its size: the sum of the value of a network increases as the square of the number of members (Kelly, 1998), even before aggregate effects are considered. Churchill (1943) said, “We shape our dwellings and afterwards our dwellings shape us.” If this is true of buildings then it is even more so of the fluid and ever-changing virtual environments made possible by the Internet. Our dwellings are no longer fixed but may be molded by the people that inhabit them. This article discusses a range of approaches that make use of this affordance to provide environments that support groups of adult learners in their learning needs.
Darby (2003) identifies three generations of networked learning environments used in adult education. First-generation systems are direct analogues of traditional courses, simply translating existing structures and course materials. Like their traditionally delivered forebears, they are dependent on individual authors. Second-generation systems tend to be team-built and designed for the medium from pedagogical first principles, but still within a traditional course-based format. Third-generation systems break away from such course-led conventions and provide such things as just-in-time learning, guided paths through knowledge management systems, and personalized curricula. This article is concerned primarily with such third-generation environments.
Saba’s interpretation of Moore’s theory of transactional distance predicts that in an educational transaction, as structure increases, dialogue decreases and vice versa (Moore & Kearsley, 1996; Saba & Shearer, 1994). What is significant in differentiating learning experiences is not the physical distance between learners and teachers, but the transactional distance, measured by the degree of interaction between them. Highly structured educational activities have a high transactional distance, while those involving much discussion have a lower transactional distance.
In a traditional learning environment, the structure of the experience is provided by the teacher or the instructional designer. However, learners will not benefit equally from any given structure, as different learners learn differently. It would be better if learners could select appropriate approaches for their needs—to choose whether or not to choose, to control or to be controlled (Dron, 2007a). Without a teacher, help with this might be provided by the opinions of other learners. However, eliciting those opinions, assessing their reliability/relevance, actually finding the resources in the first place, and once found, fitting them into a structured learning experience is difficult. Several approaches to these problems are available, but first it is necessary to introduce a few concepts of self-organization.Top
Self-organization processes are emergent: the interactions of many autonomous agents lead to structure, not due to central control, but to the nature of the system itself. Such processes are very common in nature and in human social systems. Two in particular are of interest here, evolution and stigmergy.
Based primarily on work following that of Darwin (1872), evolution is one of the most powerful self-organizing principles, whereby a process of replication with variation combined with natural selection (survival of the fittest) leads to a finely balanced self-adjusting system. It is important to note that “fittest” does not mean “best” by any other measure than the ability to survive in a given environment.
Key Terms in this Chapter
Transactional Distance: A measure of the relative amounts of dialogue and structure in an educational activity. Of necessity, as one increases, the other decreases and vice versa. More autonomous learners require less dialogue than more dependent learners.
Emergent Behavior: Behavior that arises out of the interactions between parts of a system and which cannot easily be predicted or extrapolated from the behavior of those individual parts.
Social Navigation: The transformation of an interface (usually Web based) by using the actions of visitors.
Recommender system: A computer program that recommends some sort of resource based on algorithms that rely on some sort of user model, some sort of content model, and some means of matching the two.
Latent Human Annotation (LHA): The unintentional communication of a recommendation or other information as a by-product of another process, for example the provision of hyperlinks in a Web page that are then used by search engines to provide rankings of the linked pages.
Social Software: Software in which the group is a distinct entity within the system.
Stigmergy: A form of indirect communication whereby signs left in the environment influence the behavior of others who follow.