Automatically assessing oral reading fluency in a computer tutor that listens - Robotics Institute Carnegie Mellon University

Automatically assessing oral reading fluency in a computer tutor that listens

Joseph E. Beck, P. Jia, and Jack Mostow
Journal Article, Technology, Instruction, Cognition and Learning, Vol. 2, No. 1, pp. 61 - 81, April, 2004

Abstract

Much of the power of a computer tutor comes from its ability to assess students. In some domains, including oral reading, assessing the proficiency of a student is a challenging task for a computer. Our approach for assessing student reading proficiency is to use data that a computer tutor collects through its interactions with a student to estimate his performance on a human-administered test of oral reading fluency. A model with data collected from the tutor's speech recognizer output correlated, within-grade, at 0.78 on average with student performance on the fluency test. For assessing students, data from the speech recognizer were more useful than student help-seeking behavior. However, adding help-seeking behavior increased the average within-grade correlation to 0.83. These results show that speech recognition is a powerful source of data about student performance, particularly for reading.

BibTeX

@article{Beck-2004-16942,
author = {Joseph E. Beck and P. Jia and Jack Mostow},
title = {Automatically assessing oral reading fluency in a computer tutor that listens},
journal = {Technology, Instruction, Cognition and Learning},
year = {2004},
month = {April},
volume = {2},
number = {1},
pages = {61 - 81},
}