A Bayesian Model and Bayesian Classification on the Data Obtained from Children's Educational Activity in the IoT Environment

Document Type : Original Article


Information Technology and Computer Engineering, University of Qom, Qom, Iran


In the last decade, there has been a notable surge in both attention and scientific exploration regarding the integration of technology in educational settings. An impactful outcome of incorporating such technology in child education is the enhancement of children's motivation, self-assurance, and collaborative skills. The significance of early childhood education can be approached from two distinct angles: firstly, the ease with which young minds can be shaped in contemporary times, and secondly, the enduring impact of education in this era. To delve into the effectiveness of technology in education, the study employed Bayesian modeling to analyze data sourced from Internet of Things technology. Specifically, a classifier was devised to anticipate future educational outcomes for children based on their prior performance. The test data unequivocally substantiated the model's commendable accuracy, reinforcing the positive potential of technology in shaping the educational landscape for young learners.


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