An NLP Crosswalk Between the Common Core State Standards and NAEP Item Specifications
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Abstract (arXiv)
Natural language processing (NLP) is rapidly developing for applications in educational assessment. In this paper, I describe an NLP-based procedure that can be used to support subject matter experts in establishing a crosswalk between item specifications and content standards. This paper extends recent work by proposing and demonstrating the use of multivariate similarity based on embedding vectors for sentences or texts. In particular, a hybrid regression procedure is demonstrated for establishing the match of each content standard to multiple item specifications. The procedure is used to evaluate the match of the Common Core State Standards (CCSS) for mathematics at grade 4 to the corresponding item specifications for the 2026 National Assessment of Educational Progress (NAEP).
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 0 of its 47 references that are in the map. First posted on arXiv 27 May 2024.
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Citing papers per year: 2025: 2; 2026: 1.
3 papers.
- 2025Text-Based Approaches to Item Alignment to Content Standards in Large-Scale Reading & Writing Testscited by 2
- 2025Automated Alignment of Math Items to Content Standards in Large-Scale Assessments Using Language Modelscited by 0
- 2026SciEval: A Benchmark for Automatic Evaluation of K-12 Science Instructional Materialscited by 0
- 2026SciEval: A Benchmark for Automatic Evaluation of K-12 Science Instructional Materials28 Apr 2026
- 2025Automated Alignment of Math Items to Content Standards in Large-Scale Assessments Using Language Models30 Sep 2025
- 2025Text-Based Approaches to Item Alignment to Content Standards in Large-Scale Reading & Writing Tests30 Sep 2025