Design Of An Efficient Model For Enhancing Online Teaching Platform Adoption Among Teachers During Pandemics

Abstract

In the rapidly evolving educational landscape, necessitated by the unprecedented challenges of the pandemic, the imperative need to adopt effective online teaching modules has become paramount. Existing methods in assessing and enhancing the integration of technology in education have revealed significant limitations, particularly in their failure to accurately gauge and address the multifaceted challenges faced by educators. These include a lack of comprehensive analysis of the technical and pedagogical obstacles, insufficient consideration of the social influences impacting teachers' attitudes, and the disregard for the facilitating conditions crucial for the adoption of online learning platforms. To bridge this gap, this study introduces an innovative approach, employing Graph Neural Networks combined with Grey Wolf Coot Optimizer (GWCO), to enhance the efficiency of the classification process. This methodology is uniquely positioned to dissect and understand the intricate web of factors influencing teachers' behavioral intentions and attitudes towards technology adoption during the pandemic scenarios. The proposed model leverages the synergistic effect of technical and pedagogical challenges assessment to estimate teachers' attitudes, which, when combined with social influence, accurately predicts their behavioral intention sets. This intention, further analyzed alongside facilitating conditions, provides a robust understanding of the adoption rates of online learning platforms. The superiority of this approach is evidenced by its performance on multiple real-time datasets. It demonstrated an 8.5% increase in precision, 3.9% higher accuracy, an 8.3% boost in recall, a 4.9% increase in AUC (Area Under the Curve), a 4.5% rise in specificity, and a 1.9% reduction in delay compared to existing methodologies. These advancements not only signify a substantial improvement over current models but also mark a significant stride in understanding and facilitating the adoption of online teaching platforms by educators in the face of pandemic-induced challenges. This work, thus, stands at the forefront of educational technology research, offering invaluable insights and practical solutions for the challenges of online teaching adoption. It paves the way for more nuanced, efficient, and effective integration of technology in education, aligning with the dynamic needs of educators and the education system during times of crisis. The implications of this research are far-reaching, providing a foundational framework for future studies and practical applications in the realm of online education, especially in scenarios demanding rapid adaptation and adoption of digital teaching methodologies.