Assistive Intelligent Communication Models for Peer-Based Online Learning Environments

Abstract

Online learning communities based on peers are based on sound communication to facilitate collaboration, engagement and sharing of knowledge. Nevertheless, peer interactions within those conditions are usually overloaded with information, miscommunication, barriers to access, and cognitive load to negative effect on learning outcomes. The available platforms on the internet in most online learning have been found to utilise non-adaptive or even generic communication tools that cannot adapt to service the dynamic needs of peer interaction. In this paper, an assistive intelligent communication framework is introduced that is designed to fit in an online learning setting characterised by peers. The suggested model will include situational awareness, dynamic decision-making, and mediation of communication in order to deliver real-time supportive assistance in the peer interactions. The communication dynamic between peers is modelled by formulating a system model, and an assistive intelligence mechanism is implemented to change communications interventions based on the exchange of state and context. Extensive experiments are carried out to compare the suggested approach with baseline approaches based on the communication-focused attributes of interaction effectiveness, learner engagement, and system overhead. Findings indicate that the suggested model can invariably improve the quality of peer communication at an acceptable level of computational and communication efficiency thus qualifying it to be used in an intelligent assistive communication system.