Modeling characteristics in the design of e-collaboration systems

Among the many ways to do business, e-collaboration system is gradually widely used by virtue of its advantages. Yet, designing e-collaboration systems still proves to be a great challenge due to the incomplete and inaccurate design specifications. This paper presents a characteristic modeling approach to facilitate e-collaboration system design. This approach transforms e-collaboration requirements descriptions into four types of design models. The coordination, communication, collaboration, and connectivity characteristics of e-collaborative systems are firstly addressed in these design models. In general, these models are designed to provide a more comprehensive and accurate system specification than the original requirement descriptions. The approach intends to provide a systematical approach for modeling e-collaboration processes to support e-collaboration systems design.

An Empirical Investigation of Two Group Idea Generation Techniques

Gallery writing is a widely used variant of brainwriting and the technique is available in electronic and manual forms. This study posits a model based on the input-process-output framework to empirically test the relative efficacy of electronic and manual gallery writing. An experiment using a student sample was conducted and data was collected to test the proposed model. Path analysis shows that while either technique can be used successfully, groups using the electronic version generated more text. Also, free riders were dissatisfied with the meeting process. Some implications of this study are that when a large number of ideas are desired in group meetings, electronic gallery writing might be the preferred technique, while manual gallery writing might be better when meeting participants want to keep the discussion focused on succinct ideas.

Towards Games for Knowledge Acquisition and Modeling

Many model-based methods in AI require formal representation of knowledge as input. For the acquisition of highly structured, domain-specific knowledge, machine learning techniques still fall short, and knowledge elicitation and modelling is then the standard. However, obtaining formal models from informants who have few or no formal skills is a non-trivial aspect of knowledge acquisition, which can be viewed as an instance of the well-known “knowledge acquisition bottleneck”. Based on the authors’ work in conceptual modelling and method engineering, this paper casts methods for knowledge modelling in the framework of games. The resulting games-for-modelling approach is illustrated by a first prototype of such a game. The authors’ long-term goal is to lower the threshold for formal knowledge acquisition and modelling.