Toward a Formal, Visual Framework of Emergent Cognitive Development of Scholars

Hussain, Amir; Niazi, Muaz

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.

• Journal Article Type: Article
• Acceptance Date: May 6, 2013
• Online Publication Date: Jun 4, 2013
• Publication Date: 2014-03
• Deposit Date: Sep 26, 2019
• Journal: Cognitive Computation
• Print ISSN: 1866-9956
• Publisher: BMC
• Peer Reviewed: Peer Reviewed
• Volume: 6
• Issue: 1
• Pages: 113-124
• DOI: https://doi.org/10.1007/s12559-013-9219-y
• Keywords: Agent-based modeling; Cognitive development; Cognitive agent-based computing; Complex adaptive system; Hirsch index; Complex networks
• Public URL: http://researchrepository.napier.ac.uk/Output/1793070