Cognitive Agents as a Design Metaphor in Environmental-Knowledge Management

DOI: 10.1007/978-3-7643-8900-0_7


Representing and sharing knowledge has been a central problem in artificial intelligence since its inception. Representations
such as semantic networks, frames, concept maps and ontologies, as well as various methodologies for using these systems have
been proposed for dealing with such issues. However, problems exist about issues such as communication among heterogeneous
agents, incomplete or uncertain knowledge, imprecise formal-izations, and so on. Here, a mapping system between knowledge
representations (concept maps and ontologies) is modeled using a methodology for the development of multi agent systems. Ontologies
are formalized from non-formal concept maps and can then be used to represent agents knowledge, and to facilitate the communication
among persons and software agents. A system is presented, in which a set of agents, implementing three functionalities (retrieval,
disambiguation and formalization), collaborates in the process of knowledge management. This multi-agent system is part of
a larger knowledge management system based on concept maps, and facilitates the use of generated and managed knowledge by
not only people but also other software agents, namely those which require knowledge about domains that have been represented
as concept maps, such as the environment domain, object of this book.

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Available from: Luigi Ceccaroni, Oct 08, 2015
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    ABSTRACT: The research presented here is from a three-year study that uses concept mapping to assess change in student conceptual understanding in science at the undergraduate level. The fundamental question being addressed is, "To what extent do pedagogical changes such as adaptation of an environmental problem-solving (EPS) model influence student understanding in undergraduate science?" This study is part of a National Science Foundation (NSF)-initiative to improve the teaching of science at the undergraduate level, and to study changes in teaching practice and student learning that result from this improvement. NSF-funded regional summer workshops (RWP) trained 400 faculty in facilitating local environmental problem-solving experiences, field/laboratory exercises, and cooperative learning environments for students at their home universities. One and two years following workshop attendance, eight faculty members were selected from this pool of attendees for in-depth analysis of student learning in a selected course they taught. The study used qualitative and quantitative analysis of concept mapping data to assess student conceptual understanding across a wide range of institutions and academic disciplines. The sample population consisted of a total of 79 students, 59 science majors and 20 non-majors. Results suggest that the adaptation of the EPS model was effective in increasing student conceptual understanding, as measured by concept maps. The greatest determinant of increased conceptual understanding over the course of a semester was the student's self-report of approaches to learning and studying. Approaches to learning, in turn, were reflective of differences in the quality of student concept maps. Concomitantly, the student concept maps reflected student gains in content and depth over a semester with respect to an expert map. The results also suggest that teaching styles, particularly the level of faculty-student interaction, are associated with student gains in depth of understanding.
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