elektronická verzia publikácie - FIIT STU - Slovenská technická ...
elektronická verzia publikácie - FIIT STU - Slovenská technická ...
elektronická verzia publikácie - FIIT STU - Slovenská technická ...
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258 Selected Studies on Software and Information Systems<br />
(Backstrom, 2006) analyzed the evolution and growth of communities on huge Live-<br />
Journal community of more than 10 million users with a significant fraction of the users<br />
being very active with about 300,000 profile updates in 24-hour period, and arrived at an<br />
interesting observation that not only the number of existing ties – friends that are already<br />
members – determines the probability of joining the community but also by how these<br />
friends are connected to one another with strong ties between these friends to be more<br />
favorable.<br />
If the groups are not yet established they can be created trivially either randomly or<br />
self-selected by students according to learner profiles. Another way is to use computersupported<br />
approaches. The research on algorithms for creating groups seems to divide<br />
into two principally different strands:<br />
1. One-time formation methods produce a single assignment of participants into groups<br />
according to pre-defined criteria. Groups are created in this process only once and<br />
thus it cannot possibly take future collaboration outputs into account during<br />
the group creation process. Different methods of this type are used:<br />
a. constraint-based, where the allocation problem is expressed as a Constraint Satisfaction<br />
Problem (Kumar, 1992) and the negotiation problem can then be handled by<br />
a constrain satisfaction solver,<br />
b. statistical methods which represent students’ features using a vector-based approach<br />
and generate assignments into groups employing various statistical or optimization<br />
algorithms.<br />
2. Repeated formation methods assume that multiple rounds of collaboration will happen<br />
and take feedback on previous assignments into account during the creation of next<br />
assignment of students into groups. In effect, these methods are self-optimizing as the<br />
creation process is set up in such a way that the benefits of the current allocation are<br />
evaluated after the collaboration completes and further reused, thus rewarding a better<br />
allocation next time.<br />
The actual process of setting up an individual group is usually a three stage process<br />
(Wessner, 2001): (1) initiating the formation manually by the learner or triggered automatically<br />
by the system, (2) identifying peer learners that meet certain requirements, and (3)<br />
negotiating with potential participants.<br />
Collaborative tasks are often executed in a structured way and involve a certain<br />
amount of role-playing which further imposes skill and ability demands on possible actors.<br />
Demands for different roles are usually different so that even actors with sharply<br />
contrasting skill sets may find the collaborative experience of working together rewarding.<br />
For example, in an early collaborative effort, the COSOFT project (Hoppe, 1995) when<br />
the learner encounters a problem he (phase 1) initiates the formation of a so-called learnerhelper<br />
group by pressing the “Ask” button. System displays a list of potential peers (phase<br />
2) based on the learner model. The learner can then select the helper who is subsequently<br />
asked if she wishes to help the learner with the current topic (phase 3). After this learnerhelper<br />
group is successfully negotiated a shared communication channel between them is<br />
established.<br />
In OurWeb system (Miettinen, 2005), group formation is supported by identifying<br />
students with shared interests; authors suggest that a suitable way of supporting group