Speech Technology Enhanced Assessment of Modeling (STEAM)

Sri International, Menlo Park CA

Investigators

Abstract

This project seeks to achieve more efficient and accurate assessment of students' mathematical reasoning by developing improved speech recognition technology, calibrated to recognize children's speech, and integrating it with a computerized mathematics education environment (SimCalc) involving interactive representations and simulations. Specific questions of interest include: Q1. What are the most promising task-relevant mechanisms for constraining students? spoken responses in such a way that enables valid and reliable speech-based assessments despite the imperfect accuracy of automatic spoken language systems? Q2. What are the most efficient modifications to existing spoken language technologies that achieve acceptable performance with middle-school students engaged in spontaneous speech acts about mathematical models, representations, and simulations? Q3. Which aspects of the computer-based dynamic representation system must be integrated with student speech to provide a more complete representation of student knowledge of the mathematics underlying the model? Q4. Which features of the combined output of the computer-based environment and student speech allow the spoken language understanding engine to reliably assign rubric-based scores to student work? Assessments will address five key aspects of fluency with mathematical models: comprehending, predicting, explaining, improving, and reflecting. A particularly unique focus of this work will be on combining inputs from the speech recognition engine with time-stamped information from a mathematics education environment to reliably score student responses according to a rubric. In addition to its application to education, this research on adolescents' spontaneous mathematical speech will drive advances in spoken language technology.