Detecting learning in noisy data: The case of oral reading fluency

Authors

• Beata Beigman Klebanov, Educational Testing Service
• Anastassia Loukina, Educational Testing Service
• John Lockwood, Educational Testing Service
• Van Rynald T. Liceralde, The University of North Carolina at Chapel Hill
• John Sabatini, University of Memphis
• Nitin Madnani, Educational Testing Service
• Binod Gyawali, Educational Testing Service
• Zuowei Wang, Educational Testing Service
• Jennifer Lentini, Educational Testing Service

Abstract

In a school context, learning is usually detected by repeated measurements of the skill of interest through a sequence of specially designed tests; in particular, this is the case with tracking improvement in oral reading fluency in elementary school children in the U.S. Results presented in this paper suggest that it is possible and feasible to detect improvement in oral reading fluency using data collected during children's independent reading of a book using the Relay Reader app. We are thus a step closer to the vision of having a child read for the story, not for a test, yet being able to unobtrusively assess their progress in oral reading fluency.

Publication Title

ACM International Conference Proceeding Series

Recommended Citation

Klebanov, B., Loukina, A., Lockwood, J., Liceralde, V., Sabatini, J., Madnani, N., Gyawali, B., Wang, Z., & Lentini, J. (2020). Detecting learning in noisy data: The case of oral reading fluency. ACM International Conference Proceeding Series, 490-495. https://doi.org/10.1145/3375462.3375490