Rory Sie

Social network analysis for technology-enhanced learning: review and future directions

By nature, learning is social. The interactions by which we learn from others inherently form a network of relationships among people, but also between people and resources. This paper gives an overview of the potential social network analysis (SNA) may have for social learning. It starts with an overview of the history of social learning and how SNA may be of value. The core of the paper outlines the state-of-art of SNA for technology-enhanced learning (TEL), by means of four possible types of SNA applications: visualisation, analysis, simulation, and interventions. In an outlook, future directions of SNA research for TEL are provided.

Retrieval of Case Law to Provide Layman with Information about Liability: Preliminary Results of the BEST-Project

This paper describes the experiments carried out in the context of the BEST-project, an interdisciplinary project with researchers from the Law faculty and the AI department of the VU University Amsterdam. The aim of the project is to provide laymen with information about their legal position in a liability case, based on retrieved case law. The process basically comes down to (1) analyzing the input of a layman in terms of a layman ontology, (2) mapping this ontology to a legal ontology, (3) retrieve relevant case law based, and finally (4) present the results in a comprehensible way to the layman. This paper describes the experiments undertaken regarding step 4, and in particular step 3.

A new approach to collaborative creativity support of new product designers

Effective collaborative creativity is crucial to contemporary professionals who have to continuously produce innovative products and services. The technological nature and complexity of the innovations require team work, among specialists from different disciplines. Often these teams work in a distributed fashion, across boundaries of time and place. Therefore, they need electronic |spaces| that support (|afford|) their creative collaboration. Co-creativity support is not only a matter of making appropriate groupware spaces available but also of providing concurrent support in all these dimensions. These considerations inspired the development of the idSpace platform. idSpace is a collaboration platform integrating a variety of creativity tools with pedagogy-based guidance. It aims to optimise both the use of creativity techniques themselves and of the supporting processes of team collaboration and knowledge creation. In this paper, we zoom in on knowledge-sharing strategies for collaborative creativity (KS4CC). We show how collaborative creativity can be enhanced via integration of pattern-based pedagogical flow support, including suggestions of optimal use of creativity techniques. The KS4CC strategies consist of a merger of learning and collaboration flow patterns with support for the application of creative techniques.

The Influence of Coalition Formation on Idea Selection in Dispersed Teams: A Game Theoretic Approach

In an open innovation environment, organizational learning takes place by means of dispersed teams which expand their knowledge through collaborative idea generation. Research is often focused on finding ways to extend the set of ideas, while the main problem in our opinion is not the number of ideas that is generated, but a non-optimal set of ideas accepted during idea selection. When selecting ideas, coalitions form and their composition may influence the resulting set of accepted ideas. We expect that computing coalitional strength during idea selection will help in forming the right teams to have a grand coalition, or having a better allocation of accepted ideas, or neutralising factors that adversely influence the decision making process. Based on a literature survey, this paper proposes the application of the Shapley value and the nucleolus to compute coalitional strength in order to enhance the group decision making process during collaborative idea selection.

A Simulation for Content-based and Utility-based Recommendation of Candidate Coalitions in Virtual Creativity Teams

Psychological literature shows that people do not always make rational choices with respect to whom to collaborate with. Providing the value of candidate connections may help them choosing the right people to connect with in a network. This paper presents a model about coalitions in creativity that will be used to generate content-based and knowledge-based recommendations of candidate coalitions.

COCOON CORE: CO-author REcommendations Based on Betweenness Centrality and Interest Similarity

When researchers are to write a new article, they often seek co-authors who are knowledgeable on the article’s subject. However, they also strive for acceptance of their article. Based on this otherwise intuitive process, the current article presents the COCOON CORE tool that recommends candidate co-authors based on like-mindedness and power. Like-mindedness ensures that co-authors share a common ground, which is necessary for seamless cooperation. Powerful co-authors foster adoption of an article’s research idea by the community. Two experiments were conducted, one focusing on the perceived quality of the recommendations that COCOON CORE generates and one focusing on the usability of COCOON CORE. Results indicate that participants perceive the recommendations moderately positively. Particularly, they value the recommendations that focus fully on finding influential peers and the recommendation in which they themselves can adjust the balance between finding influential peers and like-minded peers. Also, the usability of COCOON CORE is perceived to be moderately good.

Supporting co-creation with software, the idSpace platform

The idSpace platform provides support for collaborating innovators.Support for innovators affects learning, choice of creativity technique and context awareness.Evaluation using a realistic usage scenario revealed platform weaknesses and strengths. Innovation, in general, requires teamwork among specialist of different disciplines. The idSpace project developed ideas on how teams of collaborating innovators could best be supported. These ideas were embodied in a platform that the project developed. This idSpace platform allows its users to choose between various creativity techniques, pedagogical approaches and context-aware uses of stored information on projects, people and techniques. The platform follows a general process metaphor with specialised modules for specific parts, i.e. it starts with defining the problem to be addressed and through a sequence of steps concludes with a proposed solution. The platform was designed and developed by a multi-disciplinary team. It was evaluated through a realistic usage scenario which focused on the integral platform, from both an end-user and expert user perspective embodying a combination of qualitative and quantitative measurements on usability, general functionality and creativity aspects. This combination, as will be explained, proved to be a powerful way to prioritise and steer the further development of the platform.

Factors that influence cooperation in networks for innovation and learning

Networked cooperation fails if the available partnerships remain opaque.A literature review and Delphi study uncovered the elements of a fruitful partnership.They relate to personality, diversity, cooperation, and management. Innovation networks and learning networks share the same cooperative intention, but they too often fail as members of the network do not know which partnerships are valuable. If one plans to build a support service that provides insight into the value of future cooperation, one first needs to know what contributes to effective and efficient cooperation. In addition to carrying out a literature review, we invoked the eDelphi method to answer this question. eDelphi is a method to solicit knowledge from experts anonymously and without geographical constraints. Observations from two eDelphi rounds are reported in this article. The first round focused on factor generation and determined which factors influence cooperation networks; it was conducted with two groups of six representative experts. Experts list open communication, a positive attitude, trust, keeping appointments, and personality as influential factors for cooperation networks. A team of four moderators categorised the factors in a second round, resulting in four core clusters: personal characteristics, diversity, effective cooperation, and managerial aspects. Interestingly the experts failed to list some factors that are mentioned in the literature. This finding is discussed.