Hybrid Model of Learning for School Education: AI-Based Opinion Mining of Secondary School

Abstract

The COVID-19 pandemic is acting as a promoter of innovations compelling us to think and act beyond the existing boundary to solve today’s problem. Executing effective remote learning at the school level is extremely difficult, and allowing children to fall behind academically is not affordable for the country. Thus, the hybridization of in-person and remote learning could be a viable solution during the process of reopening the school. The researchers here explored secondary school teachers’ opinions regarding the optimization of various parameters relating to the Hybrid Learning Model. A purposive sample is used for data collection. AI-Based Opinion Mining was adopted to analyze teachers’ feedback. The majority of respondents not only favoured the hybridization as a model of teaching-learning, but their confidence level is high in positive response with a low standard deviation indicating teachers are strongly advocating such formats of physical & digital combinations. Most of the teachers show confidence in terms of the percentage of hybridization of both asynchronous and synchronous virtual presence in combination with the face-to-face format. The findings may be a crucial input in determining the viable form of the Hybridization Model in the Indian context while we are preparing for new normal in the context of reopening the schools.