Multilayered-quality education ecosystem (MQEE): an intelligent education modal for sustainable quality education

Abstract

Sustainable quality education is a big challenge even for the developed countries. In response to this, education 4.0 is gradually expanding as a new era of education. This work intends to unfold some hidden parameters that are affecting the quality education ecosystem (QEE). Academic loafing, unawareness, non-participation, dissatisfaction, and incomprehensibility are the main parameters under this study. A set of hypothesis and surveys are exhibited to study the behavior of these parameters on quality education at the institution level. The bidirectional weighted sum method is deployed for precise and accurate results regarding boundary value analysis of the survey. The association between parameters understudy and quality education is illustrated with correlation and scatter diagrams. Academic loafing, the hidden and unintended rudiment that affects the QEE is also defined, intended and explored in this work. The study exhibits that the average percentage association between quality education and all the parameters under study is 93.32%, whereas awareness has the least association (82.63%) and academic loafing has the highest association (99.35%) with quality education. The paper proposes a cognitive-IoT (internet of things) based multilayered QEE as a remedial solution for sustainable quality education. The emerging demand of real-time data processing for the education 4.0 environment, makes MQEE suitable for education 4.0 environment. The IoT enabled heterogeneous-data preprocessing, integration, and analysis to foster the proposed model with robustness, scalability, and flexibility. The proposed abstraction mechanism, public/private reporting, and IoT-based data preprocessing system are rich enough to handle data management issues under education 4.0 environment.