The web forum is a key tool in the building of new knowledge among students in Learning Management Systems. Students’ posted messages, in fact, build up a relationship network which supports a collaborative reflection about the forum topic. In this network two interaction levels can be distinguished. The former is the interaction between peers (the students), the latter between students and instructors (teachers and tutors). The role of the second interaction is particularly important as a feedback mechanism in the discussion dynamic but it is subjected to two kinds of limitations. The first one is the huge number of messages that makes difficult, for tutors and teachers, to quickly evaluate the progress of their students and the second one is the subjective bias of the tutors that influence the evaluation. In order to limit these two inefficiencies a multiagent system can be used to monitor such evolution and recognize the state in which the forum is. Such system is based on metrics derived from the textual and social network analysis that, feeding a rule engine, gives the instructor a more objective view of the forum evolution.
The purpose of this study is to support the learning activity in the Internet learning space. In this paper, we examine the knowledge management and the knowledge representation of the learning information for the collaborative learning support. RAPSODY-EX (REX) is a distributed learning support environment organized as a learning infrastructure. REX can effectively carry out the collaborative learning support in asynchronous/synchronous learning mode. Distributed learning is a learning style where individual learning and collaborative learning are carried out on the multimedia communication network. In the distributed learning environment, arrangement and integration of the learning information are attempted to support the decision making of learners and mediators. Various information in the educational context is referred and reused as knowledge which oneself and others can practically utilize. We aim at the construction of an increasingly growing digital portfolio database. In addition, the architecture of the learning environment that includes such a database is researched.
Success in collaboratively learning subject matter means both learning the subject matter (collaborating to learn), and learning how to effectively manage the team interaction (learning to collaborate). Supporting online learning teams means supporting both these activities. We focus on the problem of assimilating the knowledge needed to address interaction problems that may arise during collaborative learning sessions. This involves gathering knowledge about the types of problems that learning groups might encounter, evaluating methods for identifying situations in which those problems exist, and implementing strategies to facilitate groups learning online.
Collaboration between peers is an important aspect of the learning process and can considerably augment learning in studying complex domains. To ensure that peer collaboration occurs within unfamiliar situations such as those provided by Virtual Learning Environments, support for collaborative activities needs to be offered to learners. This support can be provided using intelligent agents that actively support the formation of collaborative relationships and mediate collaboration between learners in Virtual Learning Environments. This paper describes intelligent agents developed to provide support for proctoring, a form of collaborative learning where learners adopt the role of tutor or tutee. This collaborative activity is described within the context of an environment constructed for the learning of Entity Relationship Modelling. The intelligent agents determine effective collaboration partners, based on the monitoring of learner behaviour and initiate the collaborative activity between these partners. Using this approach, learners interact as both tutor and tutee and experience different types of collaboration. Learners have identified positive learning experiences and can be seen to have an increased understanding of Entity Relationship Modelling as a result of these collaborative activities.
The field of collaborative interactive learning (CIL) aims at developing and investigating the technological foundations for a new generation of smart systems that support humans in their everyday life. While the concept of CIL has already been carved out in detail (including the fields of dedicated CIL and opportunistic CIL) and many research objectives have been stated, there is still the need to clarify some terms such as information, knowledge, and experience in the context of CIL and to differentiate CIL from recent and ongoing research in related fields such as active learning, collaborative learning, and others. Both aspects are addressed in this paper.