How AI Supports Knowledge Sharing and Management in Educational Institutions

Abstract

It investigates how the use of AI-based knowledge management and sharing systems may affect Pakistani students’ academic outcomes and how well they learn. To do the study, researchers took a sample of 215 students who had enrolled through simple random sampling, both at public and private schools. A Likert-scale survey was used to study student views about AI in education. To look at the data, the study used various statistical tests, for instance, regression analysis, multiple regression, ANOVA and correlation analyses, in order to identify how the student learning outcomes are related to AI and knowledge management. When applying regression analysis, it was detected that using AI in knowledge management yields strong positive impacts on the knowledge sharing process (β = 0.727) and is highly statistically significant (p-value < 0.001). Furthermore, the model showed that 44.9% of variance is explained (R² = 0.449) and analysis of variance (ANOVA) confirmed the significance of the overall model with an F-value of 173.410 and a p-value below 0.001. the link between AI and Knowledge Management is very clear, highlighted by Knowledge Sharing (correlation of 0.670) and Learning Outcomes (correlation of 0.497). Sharing knowledge and using AI are strongly related to learning outcomes (at the 0.01 level); their correlation is 0.464. An analysis done after the study showed that AI tools performed differently at different schools and among students of different educations. AI helps students graduate better, study effectively and transfer knowledge, making it clear that AI is making a difference in education today.