Text- Natural Language Processing (NLP)/Machine Learning (ML) Models to Identify or classify various performances of CPS

Abstract

This work aims to discover examples of learning, communication, and relationships, and to provide a viable appraisal for a mind-boggling framework that could get enormous information from a proposed collaborative learning environment (CLE). The framework will be based on artificial intelligence (AI). While completing situational judgment tasks (SJT), dyads or larger groups of coworkers may engage in community-oriented learning by discussing potential solutions to problems and sharing ideas. Numerous challenges arise while attempting to demonstrate a coordinated framework that incorporates multimodal data. A Machine Learning (ML) based framework is proposed in this study to enhance understanding of the CLE's procedures, bunch constituents, and linkages. A combination of techniques from computational psychometrics (CP) and deep learning models, our approach makes use of CNNs for feature extraction, expertise distinguishing proof, and example recognition. We may also rely on our system to help us identify the social components at a microscopic level and withdisplaying the rituals of a meeting related to education.Algorithm for convolutional neural networks (CNNs), machine learning, collaborative learning.