Intelligent Student Mental Health Assessment Model on Learning Management System

A learning management system (LMS) is a software or web based application, commonly utilized for planning, designing, and assessing particular procedure. Generally, the LMS offers method of creating delivering content to instructor, monitoring students’ involvement, validating their outcomes. Since mental health issues become common among studies in higher education globally, it needed properly determine improve stability. This article develops new seven spot lady bird feature selection with optimal sparse autoencoder (SSLBFS-OSAE) model assess on LMS. The major aim SSLBFS-OSAE proper status students respect depression, anxiety, stress (DAS). involves SSLBFS elect useful set features. In addition, OSAE applied classification conditions performance can be improved by use cuckoo search optimization (CSO) parameter tuning process. design CSO algorithm optimally SAE parameters results enhanced For examining classifier model, comprehensive analysis done obtained values highlighted supremacy over its recent methods interms different measures.