Examining the Scientific Productivity of Authors in Dyslexia Research: A Study Using Lotka’s Law

Authors

Muneer AhmadFollow
Dr. M.Sadik Batcha, Annamalai University

Date of this Version

2020

Document Type

Article

Citation

Ahmad, M., & Batcha, M. S. (2020). Examining the Scientific Productivity of Authors in Dyslexia Research: A Study Using Lotka’s Law. Library Philosophy and Practice (E-Journal)

Comments

Scientometric Analysis of Dyslexia Research and applicability of Lotka's Law.

Abstract

Dyslexia, or a reading disability, occurs when an individual has significant difficulty with speed and accuracy of word decoding. Comprehension of text and spelling are also affected. The diagnosis of dyslexia involves the use of reading tests, but the continuum of reading performance means that any cut off point is arbitrary. The IQ score does not play a role in the diagnosis of dyslexia. The cognitive difficulties of dyslexics include problems with speech perception, recognizing and manipulating the basic sounds in a language, language memory, and learning the sounds of letters. Dyslexia is a neurological condition with a genetic basis. There are abnormalities in the brains of dyslexic individuals. There are also differences in the electrophysiological and structural characteristics of the brains of dyslexics. Physicians play a particularly important role in recognizing children who are at risk for dyslexia and helping their parents obtain the proper assessment. The fundamental aim of this study was, to analyze the application of Lotka’s law to the research publication, in the field of Dyslexia. The data related to Dyslexia were extracted from web of science database, which is a scientific, citation and indexing service, maintained by Clarivate Analytics. A total of 5182 research publications were published by the researchers, in the field of Dyslexia. The study found out that, the Lotka’s inverse square law is not fit for this data. The study also analyzed the authorship pattern, Collaborative Index (CI), Degree of Collaboration (DC), Co-authorship Index (CAI), Collaborative Co-efficient (CC), Modified Collaborative Co-efficient (MCC), Lotka’s Exponent value, Kolmogorov-Smirnov Test (K-S Test), Relative Growth Rate and Doubling Time.