Educational Emergency Treatment Model: An Adaptive Response To Education And Multivariate HMM Model To Latent Crisis State In Rural Rajasthan During COVID-19

Abstract

In this study, we propose an emergency education model that utilizes adaptive decision-making to navigate different intervention states. The model was implemented in an afterschool program in Harirampura, India, which transitioned from in-person teaching to various forms of remote and distance learning during the COVID-19 pandemic. To assess the effectiveness of this adaptive approach, the study employs a multivariate Hidden Markov Model to compare the latent crisis states caused by COVID-19. This analysis expands on Karalis' original Effective Educational Emergency and Treatment (MEET) model. Additionally, the study evaluates the impact of the adaptive approach by comparing standardized Annual Status of Education Report scores in Harirampura with those in other rural areas of Rajasthan before and after the pandemic. The results of the analysis demonstrate a strong correlation between the intervention states implemented and the observed latent crisis states during the pandemic. This study indicates that the adaptive MEET model effectively mitigated the negative effects of the COVID crisis on education outcomes in Harirampura. Furthermore, these results support the applicability of the model to the address of other educational disruptions stemming from natural or manmade disasters.