Peer Support to Facilitate Knowledge Sharing on Complex Tasks

This thesis explores how to design a peer support system to facilitate self-organized knowledge sharing in non-formal learning environments, in particular when learners work on complex tasks. The peer support system aims to replace two teacher-led didactic arrangements: selecting a tutor at the initial stage, and guidance during the interaction process (Dillenbourg, 1999; Topping, 1996). Such a system has previously been developed by Van Rosmalen (2008) and De Bakker (2010) and has been tentatively used to facilitate knowledge sharing on content-related questions. In this thesis, we would like to find out how to further improve the design of this peer support system, especially to facilitate knowledge sharing on complex tasks. Since little pedagogical theory is available to inform the design of our peer support system, this thesis attempts to apply cognitive load theory (Sweller, Van Merriënboer, & Paas, 1998; Van Merriënboer & Sweller, 2005) that informs instructional designs in classroom settings to the design of our peer support system in Learning Networks.

Comparing architectural styles for distributed expert knowledge modules in intelligent tutoring systems

Intelligent Tutoring Systems (ITSs) are computerized systems for learning-by-doing. These systems provide students with immediate and customized feedback on learning tasks. An ITS typically consists of several modules that are connected to each other. This research focuses on the distribution of the ITS module that provides expert knowledge services. For the distribution of such an expert knowledge module we need to use an architectural style because this gives a standard interface, which increases the reusability and operability of the expert knowledge module. To provide expert knowledge modules in a distributed way we need to answer the research question: ‘How can we compare and evaluate REST, Web services and Plug-in architectural styles for the distribution of the expert knowledge module in an intelligent tutoring system?’. We present an assessment method for selecting an architectural style. Using the assessment method on three architectural styles, we selected the REST architectural style as the style that best supports the distribution of expert knowledge modules. With this assessment method we also analyzed the trade-offs that come with selecting REST. We present a prototype and architectural views based on REST to demonstrate that the assessment method correctly scores REST as an appropriate architectural style for the distribution of expert knowledge modules.