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|Title: ||Designing optimal peer support for knowledge sharing in Learning Networks|
|Authors: ||Hsiao, Amy|
|Keywords: ||peer support|
|Issue Date: ||24-Oct-2012|
|Abstract: ||Learning Networks (LNs) are a particular kind of online social network designed to support self-directed lifelong learners in a particular domain. Within our notion of a LN, learners have to take responsibilities to organize their own learning activities of knowledge sharing with others to achieve their personalised learning goals of knowledge building. The success of knowledge building depends on how learners self-direct learning activities of finding peers and maintaining the mutual interaction process, namely collaboration. Cognitive load theory (CLT) assumes that learning works best under instructional conditions that are aligned with the human cognitive architecture. In the present context, this means that individual learners only learn effectively if the architecture of their cognitive system, the characteristics of the task and the technical infrastructure are understood, accommodated, and aligned.
Cognitive load is the load that is imposed by a particular task on the learner’s cognitive system when performing that task. To facilitate learning, CLT suggests that an effective educational intervention should optimise cognitive load: to first reduce extraneous load that is imposed by an ineffective design that forces learners to carry out unnecessary cognitive processing and then to direct the freed-up cognitive capacity to learning activities that induce germane load. Without support, the self-organizing process could have a detrimental effect on knowledge sharing when working on complex learning tasks. We propose a software-based peer support system (PSS) to facilitate knowledge building by using an automated matchmaking system which forms ad hoc groups/pairs based on learners’ requests. Following the CLT guidelines, we have conducted the first experiment to examine whether our matchmaking system reduces extraneous load imposed by finding relevant peer supporters for knowledge sharing. Secondly, studies in peer learning (such as cooperative and collaborative learning) have shown that the characteristics of group members have significant influences on group process and learning outcomes. From collaborative learning we know that the first way to increase the probability that some types of interaction occur is to carefully design the situation, which includes setting certain criteria of selecting group members. Therefore, the current research question is to define suitable peer supporters who are likely to reduce extraneous load and to induce extra germane processing for knowledge sharing. Based on the literature review and our previous work, we have identified two tutor competences that predict effective tutor functioning for knowledge sharing: content knowledge and tutoring skills. The current study is to find out which competence has more effects on optimizing tutee cognitive load in a more controlled setting. In the future study, we will use these findings to assign weights of different competences in our PSS system to examine the effects in a natural LN.|
|Description: ||Hsiao, Y. P., Brouns, F., & Sloep, P. B. (2012, 2 April). Designing optimal peer support for knowledge sharing in Learning Networks. Presented at Doctoral Consortium of The 8th International Conference on Networked Learning, Maastricht, The Netherlands.|
|Appears in Collections:||2. LN: Presentations|
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