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Modelling Group Dynamics with SYMLOG and Snowdrift for Intelligent Classroom Environment

Longford, Edward (2022) Modelling Group Dynamics with SYMLOG and Snowdrift for Intelligent Classroom Environment. PhD thesis, University of Essex.

Thesis__Supporting_Classroom_Teachers_in_Group_Learning_Exercisers__Modelling_and_Responding_to_group_dynamics_in_a_classroom_environment (1).pdf

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The aim of this thesis is to provide assistance to human teachers focusing on supporting group work within a classroom environment. This is achieved by incorporating theories from Psychology and Game Theory in order to provide a better method of modelling and predicting group interactions. This research proposes a framework that extends the pre-existing Intelligent Tutorial System (ITS) beyond the individual and into one that encompasses one or more groups of learners within a learning space. This framework transforms a traditional school classroom into a group interface as part of the communication module of an ITS and enhances the role of a human teacher. This is achieved by automating class management tasks and providing an immersive learning experience. Moreover, the proposed framework monitors emotional well-being and feeds back, to the teacher, emotional profiles of individuals and groups. This new ITS system is named Intelligent Classroom Tutoring System (ICTS). 6 experiments were conducted to support the ICTS. 2 experiments were set up to compare experimental frameworks for SYMLOG allowing the researchers to test a new mod-SYMLOG which was found to be an effective tool for modelling groups interactions. 1 experiment was centred around a longitudinal study of group work, and the final 3 composing of both AI and human studies, examining applying a new mod-Snowdift game to produce a predictive mechanism for group interaction.

Item Type: Thesis (PhD)
Subjects: L Education > L Education (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Edward Longford
Date Deposited: 14 Feb 2022 10:18
Last Modified: 14 Feb 2022 10:18

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