Dynamic Maps’ Use in Smart-Cities Learning Contexts

Author:

Pedroni Marco1

Affiliation:

1. Facoltà di Lettere e Filosofia, University of Ferrara, Ferrara, Italy

Abstract

This paper examines the potentialities and characteristics of dynamic maps in relationship with constructivist teaching, by considering maps’ support to four functions: the contents’ learning, the contextualization of Learning Objects, the contextualization of online learning interaction and the knowledge construction. Several algorithms for polymorphic and animated maps’ reconstruction, both bi-dimensional and tridimensional, will be examined and described in detail. Among these algorithms, a further differentiation is made between those concerning proximal, or hierarchical development, and those regarding gravitational developments. In the latter one the positioning of nodes derives from quantitative values, that express their relation’s attractive strength. Conclusions derived from this work are the unavoidable need to implement maps’ dynamic reconstruction algorithms, when the complexity of the disciplinary ontology makes the traditional static approaches unable to provide an effectively usable image of the map.

Publisher

IGI Global

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference13 articles.

1. Cañas, A. J., Hill, G., Carff, R., Suri, N., Lott, J., & Eskridge, T. … Carvajal, R. (2004). CmapTools: A knowledge modeling and sharing environment. In Proceedings of the 1th International Conference on Concept Mapping, Pamplona, Spain.

2. Kremer, R. (1994). Concept mapping: Informal to formal. In Tepfenhart. In W., Dick, J. & Sowa, J. (Eds.), Proceedings of the Third International Conference on Conceptual Structures, Knowledge Acquisition Using Conceptual Graphs Theory Workshop (pp. 152-167), University of Maryland, College Park, MD.

3. Concept maps as a learning assessment tool. In Information and Beyond;L.La Vecchia;The Journal of Issues in Informing Science and Information Technology,2007

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