Real-time interactive AI-based training ecosystem

Abstract

A system for an automated real-time interactive testing based on user-response data including a processor of a testing support server (TSS) node configured to host a machine learning (ML) module and connected to at least one user-entity node and to at least one test-entity node over a network and a memory on which are stored machine-readable instructions that when executed by the processor, cause the processor to: provide test question data including a plurality of key elements to the at least one user-entity node; receive user response data from the at least one user-entity node; parse the user response data to extract a plurality of classifying features based on the plurality of key elements; query a local testing database to retrieve local historical tests-related data based on the plurality of classifying features; generate at least one feature vector based on the plurality of classifying features and the local historical tests-related data; provide the at least one feature vector to the ML module coupled to an Artificial Neural Network (ANN); receive a plurality of question update parameters from a test predictive model generated by the ML module using outputs of the ANN based on the feature vector; and generate an updated question based on the plurality of question update parameters.

CPC Classifications