Building a mapping between items and their related knowledge components, while difficult and time consuming, is central to the task of developing affective intelligent tutoring systems. Improving performance on this task by creating a semi-automatic skill encoding system would facilitate the development of such systems. The goal of this project is to explore techniques involved in text classification to the end of improving the time required to correctly tag items with their associated skills.
, Heffernan, Neil T.
(2006). Knowledge Engineering for Intelligent Tutoring Systems: Using machine learning assistance to help humans tag questions to skills based upon the words in the questions.. .
Retrieved from: http://digitalcommons.wpi.edu/computerscience-pubs/49