A Knowledge Scoring Engine (KSE) for real-time knowledge base generation used in intelligent tutoring systems

Abstract

This paper provides a detailed account of a tool developed to facilitate the development of individual computational cognitive models to be used in intelligent tutoring systems (ITS). A generic tool that we will call the Knowledge Scoring Engine (KSE) reads eye tracking and human performance data in real-time, parses the data into discrete events, and uses a knowledge inference generator to build and update student knowledge bases. Student knowledge bases are generated by interpreting actions in real-time based on the context in which the actions take place. The knowledge bases generated by KSE are used by ADAPT, a comprehension-based framework construction-integration model of pilot action planning. This paper provides a detailed description of KSE, the current ADAPT architecture, how the ADAPT model interacts with KSE, and the potential for future developments.