MUMBAI, India, June 30 -- Intellectual Property India has published a patent application (202641074401 A) filed by Cvr College Of Engineering on June 16, 2026, for Explainable Ai-Based System For At-Risk Student Detection And Personalized Academic Interventions.
Inventor includes Nayani Sateesh.
The application for the patent was published on June 26, 2026, under issue no. 26/2026.
Abstract: The present invention relates to an Explainable Artificial Intelligence (XAI)-based system and method for the early detection of academically at-risk students and the generation of personalized academic intervention recommendations. The invention utilizes educational data obtained from academic records, attendance systems, learning management systems, assessment results, student learning activities, and behavioral data. Machine learning models such as Random Forest, XGBoost, and Ensemble Models are employed to predict academic performance and identify students at varying levels of academic risk. An explainability engine based on SHAP, LIME, and rule extraction techniques provides interpretable explanations by identifying the key factors that influence prediction outcomes. Based on the evaluated academic risk and the explanatory factors from the prediction results, students are categorized into suitable academic risk groups, following which personalized academic intervention recommendations are generated. These recommendations help educators provide prompt academic assistance to students who may encounter learning difficulties.
Disclaimer: Curated by HT Syndication.
