Identifying and Responding to Disengagement in a Constraint-Based Intelligent Tutoring System
Year: 2014
Type: dissertation
Abstract: Numerous studies have shown the effectiveness of Intelligent Tutoring Systems in improving learning. However, there are still students who do not engage with problem solving and therefore miss opportunities for learning. In my project, I am investigating whether it is possible to predict when the student would abandon a problem, thus allowing the system to try to motivate the student to persevere. I will discuss the approach taken to generate a predictor, including identifying the features from log data and the selection of the learning algorithm to produce a predictor. To demonstrate the accuracy of the generated decision tree predictor, we conduct an experiment deploying this predictor in a study with SQL-Tutor.
DOI: 10.26021/3088
Author: Hong, Jin Kwang
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W2944446759