Artificial Intelligence Model for the Improvement of the Quality of Education at the National University of Central Peru, Huancayo 2024

This paper presents a project that addresses the problem of the high rate of non-attendance and disinterest in the tutoring course, and how this affects academic performance. The objective is to determine the influence of implementing an Artificial Intelligence Model using data prediction and intelligent tutoring. The hypothesis is that this model will positively influence the improvement of students' educational quality. A model was developed in SmartPLS using a dataset obtained from an application developed in Flutter and trained in Azure Machine Learning. The results show the reliability of the data through Cronbach's Alpha (0.747 to 0.975), explanatory power of the model through the R-squared (0.001 to 0.188), good prediction accuracy through the path coefficient (0.022 to 0.433), and adequate statistical significance through the p-value=0.000.