Semantic Modeling for Group Formation

Group formation has always been a subject of interest in collaborative learning research. As it is concerned with assigning learners to the groups that maximize their benefits, computer-supported group formation can be viewed in this context as an active personalization for the individual as an entity within the group. While applying this personalization to all students in the class can cause conflicts due to the differences of needs and interests between the individuals, negotiating the allocations to groups to reach consensus can be a very challenging task. The automated process of grouping students while preserving the individual’s personalization needs to be supported by an appropriate learner model. In this paper, we propose a semantic learner model based on the Friend of Friend (FOAF) ontology, a vocabulary for mapping social networks. We discuss the model as we analyse the different types of groups and the learners’ features that need to be modeled for each of these types

Towards a semantic modeling of learners for social networks

The Friend of a Friend (FOAF) ontology is a vocabulary for mapping social networks. In this paper we propose an extension to FOAF in order to allow it to model learners and their social networks. We analyse FOAF alongside different learner modeling standards and specifications, and based on this analysis we introduce a taxonomy of the different features found in those models. We then compare the learner models and FOAF against the taxonomy to see how their characteristics have been shaped by their purpose. Based on this we propose extensions to FOAF in order to produce a learner model that is capable of forming the basis of a semantic social network.<br/

The role of social networks in students’ learning experiences

The aim of this research is to investigate the role of social networks in computer science education. The Internet shows great potential for enhancing collaboration between people and the role of social software has become increasingly relevant in recent years. This research focuses on analyzing the role that social networks play in students’ learning experiences. The construction of students’ social networks, the evolution of these networks, and their effects on the students’ learning experience in a university environment are examined

The role of social networks in students' learning experiences

SIGCSE December 2007.The aim of this research is to investigate the role of social networks in computer science education. The Internet shows great potential for enhancing collaboration between people and the role of social software has become increasingly relevant in recent years. This research focuses on analyzing the role that social networks play in students’ learning experiences. The construction of students’ social networks, the evolution of these networks, and their effects on the students’ learning experience in a university environment are examined.Keywords: Social network, computer science education, student experience, higher education, learning proces

Enhancing the automation of forming groups for education with semantics

Many approaches to learning and teaching rely upon students working in groups. Formation of optimal groups can be a time consuming and complex task, particularly when the list of participants is unknown in advance. This research investigates the implementation of semantics to enhance computer-supported group formation in education using two approaches: The first approach uses semantics to express the criteria specified by the person forming the groups. The group formation in this approach is modelled as a constraint satisfaction problem where the criteria is a set of constraints that we aim to minimise their violation while processing the groups. The second approach uses Semantic Web domain ontologies in describing the participants to enrich the data used in calculating the similarity between the participants when the group formation is processed using a heuristic approach such as clustering algorithms.We run a number of experiments that include real datasets from higher education classes, simulated datasets, Web-based datasets, and user studies, to evaluate the research. The results proved that in both approaches, implementing semantics improved the generated groups, in that, using semantics to model group formation’s constraints generates an optimised grouping in terms of constraint satisfaction that exceeds the performance of existing applications, particularly in terms of the number of constraints it can handle; and that using semantics to model the participants’ data enhances their satisfaction with the groups they are allocated to

A framework for semantic group formation

Collaboration has long been considered an effective approach to learning. However, forming optimal groups can be a time consuming and complex task. Different approaches have been developed to assist teachers allocate students to groups based on a set of constraints. However, existing tools often fail to assign some students to groups creating a problem well known as “orphan students”. In this paper we propose a framework for learner group formation, based upon satisfying the constraints of the person forming the groups by reasoning over semantic data about the potential participants. The use of both Semantic Web technologies and Logic programming proved to increase the satisfaction of the constraints and overcome the orphans’ problem