Investigating the Association between Algorithmic Thinking and Performance in Environmental Study

Presently, computational thinking (CT) is considered necessary for adapting to the future. Concurrently, COVID-19 pandemic has accentuated demand strengthening Environmental Education as a means improve sustainability and stimulate environmental protection public health. Having in mind that CT does not concern only technocrats but also applies solving everyday problems, we introduce novel idea of synergistic learning Study. Thus, our research aim explore correlation between algorithmic (AT), fundamental competency, educational achievements Study course during early primary school years. Towards this end, implemented quantitative study, employing an innovative assessment framework propose. The adoption cluster sampling eventuated sample 435 students. exploitation ordinal logistic regression analysis machine method validated two fields pointed out AT levels constitute predictive factor performance vice versa. These results support concurrently cultivating consciousness build robust base future studies will focus on providing ecological reflection activities.