Sociodemographics and Knowledge Transfer in the Age of Artificial Intelligence: A Case Study of Pre-Kindergarten Enrollment

An urban school district in Texas aims to improve pre-kindergarten ( pre-K) school enrollment through uncommon knowledge management (KM) practices to reach a growing population of low socioeconomic, minority households. Previous studies prove that learning disparities between low- and middle-income households are greatly reduced through pre-K enrollment. School districts view enrollment in pre-K as a means to reduce future educational disparities and slow or stop the cycle of poverty in their cities. Through the examination of cognitive authority theory, cultural literacy, and sociodemographics, this case study investigates how to improve knowledge sharing in communities with education disparities. Enrollment in pre-K impacts school readiness during early childhood years and can impact long-term success beyond grade school. With the advent of artificial intelligence (AI), this study investigates how AI can be utilized to innovate even the most human of knowledge sharing practices. As AI grows in popularity, there will be new ways to innovate KM practices, even when human connection must remain at the forefront of transferring knowledge to tight-knit communities.