Overview of Intelligent Tutoring System in Human Teamwork and Its Impact Generally on Learning

Abstract

Teams can be depicted in many organizations and is becoming increasingly used for effective and efficient productivity. Teams work as the collection of individuals that have different skills to complement each other rather than compete, their driving force is to achieve a common goal by inculcating strategical approaches of which they are held accountable. This, helps in maximizing general output, however the need of its incorporation in learning. This study presents an overview of Intelligent Tutoring System and its impact generally on learning. A review of previous works done on this area was also inculcated in this study highlighting their importance and relevance. Intelligent Tutoring System (ITS), been a machine intelligence learning paradigm. This research explores and unveils what an intelligent tutoring system is all about and its role in learning. The work also covers how intelligent tutoring system has enhanced learner's skill and performance. In conclusion, the massive effects of intelligent tutoring system on the learning process are acknowledged.

Agent Based Intelligent System for Enhanced Teamwork Performance

“…Because there is maximum communication throughout operations, teams allow the various personnel in a company to create a welcoming environment for providing services. Teams within a business foster an atmosphere where individuals are free to speak and act upon their ideas, ultimately leading to high performance [18].…”

A Study on the Factors Influencing the Sustainable Development of Education in the Context of COVID-19: Tencent Conference Online Platform

“…Click data from online learning environments were analyzed by two mathematical methods by An-tonenko et al to determine the learning behavior characteristics of high-achieving students [24]. Some scholars used a potential correspondence model of machine learning to detect whether students misuse intelligent tutoring systems for the sake of creating a classification system for detecting students' honesty rates [25]. Others combined the concept of self-selection and argued that the factors influencing participants' willingness to continue learning online are the basic indicators of TAM and perceived enjoyment [26].…”