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Modelling diffusion of a personalized learning framework

Publication Type : Journal Article

Thematic Areas : Learning-Technologies

Publisher : Springer

Source : Educational Technology Research and Development, vol. 60, no. 4, pp. 585-600, 2012

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-84865583160&doi=10.1007%2fs11423-012-9249-2&partnerID=40&md5=82b23e0c67fd36c991c6b20cee9799bc

Campus : Amritapuri

School : Department of Computer Science and Engineering, School of Engineering

Center : Technologies & Education (AmritaCREATE), Amrita Center For Research in Analytics

Department : Computer Science

Year : 2012

Abstract : A new modelling approach for diffusion of personalized learning as an educational process innovation in social group comprising adopter-teachers is proposed. An empirical analysis regarding the perception of 261 adopter-teachers from 18 schools in India about a particular personalized learning framework has been made. Based on this analysis, teacher training (TT) has been identified as one of the dominant factor which can significantly influence decision by teachers to adopt the educational innovation. Different situations corresponding to fixed and time dependent dynamic carrying capacity of potential adopter-teachers at any time have been developed. New generalized models capturing the growth dynamics of the innovation diffusion process in conjunction with the evolutionary carrying capacity of potential adopters are investigated. The coupled dynamics allows forecasting the likelihood of success or failure of new educational innovation in a given context. Different scenarios for TT are considered based on—constant growth rate model; proportional growth rate model; stratified growth rate model. The proposed modelling framework would be of great interest to education policy makers as it has the potential to predict the likelihood of success or failure of new educational innovation.

Cite this Research Publication : Prof. Prema Nedungadi, Raghu Raman, and Karmeshu, “Modelling diffusion of a personalized learning framework”, Educational Technology Research and Development, vol. 60, no. 4, pp. 585-600, 2012

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