http://hdl.handle.net/1893/16527
Appears in Collections: | Computing Science and Mathematics Journal Articles |
Peer Review Status: | Refereed |
Title: | Toward a Formal, Visual Framework of Emergent Cognitive Development of Scholars |
Author(s): | Hussain, Amir Niazi, Muaz A |
Contact Email: | amir.hussain@stir.ac.uk |
Keywords: | Agent-based modeling Cognitive development Cognitive agent-based computing Complex adaptive system Hirsch index Complex networks |
Issue Date: | Mar-2014 |
Date Deposited: | 26-Aug-2013 |
Citation: | Hussain A & Niazi MA (2014) Toward a Formal, Visual Framework of Emergent Cognitive Development of Scholars. Cognitive Computation, 6 (1), pp. 113-124. https://doi.org/10.1007/s12559-013-9219-y |
Abstract: | Understanding the cognitive evolution of researchers as they progress in academia is an important but complex problem; one that belongs to a class of problems, which often require the development of models to gain further understanding of the intricacies of the domain. The research question that we address in this paper is: how to effectively model this temporal cognitive mental development of prolific researchers? Our proposed solution is based on noting that the academic progression and notability of a researcher are linked with a progressive increase in the citation count for the scholar's refereed publications, quantified using indices such as the Hirsch index. We propose the use of an yearly increment of a scholar's cognition quantifiable by means of a function of the scholar's citation index, thereby considering the index as an indicator of the discrete approximation of the scholar's cognitive development. Using validated agent-based modeling, a paradigm presented as part of our previous work aimed at the development of a cognitive agent-based computing framework, we present both formal as well as visual agent-based complex network representations for this cognitive evolution in the form of a temporal cognitive level network model. As proof of the effectiveness of this approach, we demonstrate the validation of the model using historic data of citations. |
DOI Link: | 10.1007/s12559-013-9219-y |
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Licence URL(s): | http://www.rioxx.net/licenses/under-embargo-all-rights-reserved |
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