Tenaha O’Reilly

Also published as: Tenaha O’reilly


2024

pdf bib
From Miscue to Evidence of Difficulty: Analysis of Automatically Detected Miscues in Oral Reading for Feedback Potential
Beata Beigman Klebanov | Michael Suhan | Tenaha O’Reilly | Zuowei Wang
Proceedings of the 19th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2024)

This research is situated in the space between an existing NLP capability and its use(s) in an educational context. We analyze oral reading data collected with a deployed automated speech analysis software and consider how the results of automated speech analysis can be interpreted and used to inform the ideation and design of a new feature – feedback to learners and teachers. Our analysis shows how the details of the system’s performance and the details of the context of use both significantly impact the ideation process.

2023

pdf bib
A dynamic model of lexical experience for tracking of oral reading fluency
Beata Beigman Klebanov | Michael Suhan | Zuowei Wang | Tenaha O’reilly
Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023)

We present research aimed at solving a problem in assessment of oral reading fluency using children’s oral reading data from our online book reading app. It is known that properties of the passage being read aloud impact fluency estimates; therefore, passage-based measures are used to remove passage-related variance when estimating growth in oral reading fluency. However, passage-based measures reported in the literature tend to treat passages as independent events, without explicitly modeling accumulation of lexical experience as one reads through a book. We propose such a model and show that it helps explain additional variance in the measurements of children’s fluency as they read through a book, improving over a strong baseline. These results have implications for measuring growth in oral reading fluency.

2017

pdf bib
Continuous fluency tracking and the challenges of varying text complexity
Beata Beigman Klebanov | Anastassia Loukina | John Sabatini | Tenaha O’Reilly
Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications

This paper is a preliminary report on using text complexity measurement in the service of a new educational application. We describe a reading intervention where a child takes turns reading a book aloud with a virtual reading partner. Our ultimate goal is to provide meaningful feedback to the parent or the teacher by continuously tracking the child’s improvement in reading fluency. We show that this would not be a simple endeavor, due to an intricate relationship between text complexity from the point of view of comprehension and reading rate.

2013

pdf bib
Automated Scoring of a Summary-Writing Task Designed to Measure Reading Comprehension
Nitin Madnani | Jill Burstein | John Sabatini | Tenaha O’Reilly
Proceedings of the Eighth Workshop on Innovative Use of NLP for Building Educational Applications