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Measuring Teaching Practices at Scale: A Novel Application of Text-as-Data Methods

Valid and reliable measurements of teaching quality facilitate school-level decision-making and policies pertaining to teachers. Using nearly 1,000 word-to-word transcriptions of 4th- and 5th-grade English language arts classes, we apply novel text-as-data methods to develop automated measures of teaching to complement classroom observations traditionally done by human raters. This approach is free of rater bias and enables the detection of three instructional factors that are well aligned with commonly used observation protocols: classroom management, interactive instruction, and teacher-centered instruction. The teacher-centered instruction factor is a consistent negative predictor of value-added scores, even after controlling for teachers’ average classroom observation scores. The interactive instruction factor predicts positive value-added scores. Our results suggest that the text-as-data approach has the potential to enhance existing classroom observation systems through collecting far more data on teaching with a lower cost, higher speed, and the detection of multifaceted classroom practices.

Keywords
teaching quality; K-12 education; classroom observation; text as dat
Education level
Topics
Document Object Identifier (DOI)
10.26300/6bqj-vh81
EdWorkingPaper suggested citation:
Liu, Jing, and Julie Cohen. (). Measuring Teaching Practices at Scale: A Novel Application of Text-as-Data Methods. (EdWorkingPaper: -369). Retrieved from Annenberg Institute at Brown University: https://doi.org/10.26300/6bqj-vh81

Machine-readable bibliographic record: RIS, BibTeX

Published Edworkingpaper:
(Forthcoming). Measuring Teaching Practices at Scale: A Novel Application of Text-as-Data Methods