Development and Deployment of a Large-Scale Dialog-based Intelligent Tutoring System
Author(s) -
Shazia Afzal,
Tejas I. Dhamecha,
Nirmal Mukhi,
Renuka Sindhgatta,
Smit Marvaniya,
Matthew Ventura,
Jessica Yarbro
Publication year - 2019
Publication title -
qut eprints (queensland university of technology)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18653/v1/n19-2015
Subject(s) - dialog box , software deployment , scale (ratio) , computer science , volume (thermodynamics) , association (psychology) , artificial intelligence , software engineering , world wide web , cartography , philosophy , geography , epistemology , physics , quantum mechanics
There are significant challenges involved in the design and implementation of a dialog-based tutoring system (DBT) ranging from domain engineering to natural language classification and eventually instantiating an adaptive, personalized dialog strategy. These issues are magnified when implementing such a system at scale and across domains. In this paper, we describe and reflect on the design, methods, decisions and assessments that led to the successful deployment of our AI driven DBT currently being used by several hundreds of college level students for practice and self-regulated study in diverse subjects like Sociology, Communications, and American Government.
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