REVIEW 5 cited by
The NCTE Transcripts: A Dataset of Elementary Math Classroom Transcripts
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
The NCTE Transcripts: A Dataset of Elementary Math Classroom Transcripts
read the original abstract
Classroom discourse is a core medium of instruction - analyzing it can provide a window into teaching and learning as well as driving the development of new tools for improving instruction. We introduce the largest dataset of mathematics classroom transcripts available to researchers, and demonstrate how this data can help improve instruction. The dataset consists of 1,660 45-60 minute long 4th and 5th grade elementary mathematics observations collected by the National Center for Teacher Effectiveness (NCTE) between 2010-2013. The anonymized transcripts represent data from 317 teachers across 4 school districts that serve largely historically marginalized students. The transcripts come with rich metadata, including turn-level annotations for dialogic discourse moves, classroom observation scores, demographic information, survey responses and student test scores. We demonstrate that our natural language processing model, trained on our turn-level annotations, can learn to identify dialogic discourse moves and these moves are correlated with better classroom observation scores and learning outcomes. This dataset opens up several possibilities for researchers, educators and policymakers to learn about and improve K-12 instruction. The dataset can be found at https://github.com/ddemszky/classroom-transcript-analysis.
Forward citations
Cited by 5 Pith papers
-
TeachObs: A Human-Validated Benchmark for Multimodal Teaching Observation and Model Evaluation
TeachObs is a new human-validated benchmark dataset and evaluation protocol for multimodal AI on classroom teaching observation, showing no model dominates across tracks and that models over-rate procedurally clear lessons.
-
TeachObs: A Human-Validated Benchmark for Multimodal Teaching Observation and Model Evaluation
TeachObs provides human-validated segment- and lesson-level labels on 30 classroom videos and finds frontier VLMs inconsistent, frame-inflated, and over-generous versus expert raters.
-
Mitigating LLM biases toward spurious social contexts using direct preference optimization
Debiasing-DPO reduces bias to spurious social contexts by 84% and improves predictive accuracy by 52% on average for LLMs evaluating U.S. classroom transcripts.
-
Creating and Evaluating K-12 GenAI Assessment Graders Through Context Engineering
LLM graders achieve substantial human agreement on math and science MCAS items but vary on ELA, performing best as sources of formative narrative feedback rather than summative numerical scores.
-
Enhancing Instructional Quality: Leveraging Computer-Assisted Textual Analysis to Generate In-Depth Insights from Educational Artifacts
AI and NLP applied to educational artifacts within the Instructional Core Framework can identify advantages for teacher coaching, student support, and personalized learning.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.