Abstract
A Geographic Information Systems (GIS) play a vital role in various applications associated with sustainable development and clean energy. In these applications, the GIS provides a capability to upload on-site geographical information collected by public into online maps. One of the major problems is how to make a decision for those reports. In this paper, we study two types of cognitive modes for decision making: argument and narrative reasoning. We investigate how various discussion representations, argumentation theoretical model, and reasoning modes of geo-graphics problems affect knowledge accumulation and argument quality. We conduct empirical tests on different groups of participants regarding their discussions on a particular offshore wind farm project as a case study. We have demonstrated that graph representation provides better results than threaded representation for collaborative work. We also illustrate that the argument theoretical model leads to reduce participants’ performance. Moreover, we conclude that there is no significant difference between narrative representation and graph representation in the participants’ performance to construct knowledge.
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Al-Shehhi, A., Aung, Z., Woon, W.L. (2015). Argument Visualization and Narrative Approaches for Collaborative Spatial Decision Making and Knowledge Construction: A Case Study for an Offshore Wind Farm Project. In: Woon, W., Aung, Z., Madnick, S. (eds) Data Analytics for Renewable Energy Integration. DARE 2015. Lecture Notes in Computer Science(), vol 9518. Springer, Cham. https://doi.org/10.1007/978-3-319-27430-0_10
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