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robworks-software/k12-mathematics-standards-expanded

K-12 Mathematics Standards, expanded (generated instruction data) 4,965 instruction/input/output records for mathematics, generated around a K-12 standards taxonomy for instruction-tuning and educational-content experiments. How this was built (read this first) These are programmatically generated training examples, not curriculum written by educators and not the text of any official standard. A generator combined standards metadata - codes, grade levels, domains… See the full description on the dataset page: https://huggingface.co/datasets/robworks-software/k12-mathematics-standards-expanded.

sourceHugging Facecc-by-4.0updated 3mo agoView on Hugging Face
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K-12 Mathematics Standards, expanded (generated instruction data)

4,965 instruction/input/output records for mathematics, generated around a K-12 standards taxonomy for instruction-tuning and educational-content experiments.

How this was built (read this first)

These are programmatically generated training examples, not curriculum written by educators and not the text of any official standard. A generator combined standards metadata - codes, grade levels, domains, Bloom's and DOK levels - into instruction and output text using a fixed set of templates.

Of 3,204 populated training outputs, 1,554 are distinct (48.5%). The placeholder "Students often confuse mathematical concepts with similar concepts" appears 95 times.

Structured metadata fields (standard codes, grade levels, domain names) come from the source taxonomy and are reliable. The generated prose is not.

Loading

python
from datasets import load_dataset

ds = load_dataset("robworks-software/k12-mathematics-standards-expanded")

Splits

SplitRows
train3,475
validation744
test746
total4,965

Appropriate use

  • —Synthetic instruction-tuning data where fluent, on-topic, low-variety text is acceptable.
  • —Format and schema experiments: task routing, metadata-conditioned generation.
  • —Structural analysis over the standards taxonomy itself.

Inappropriate use

  • —Classroom or student-facing material. Nothing here was reviewed by an educator.
  • —A source of official standard text. Go to the issuing body.
  • —Benchmarking model knowledge of standards. Low text variety lets a model score well by learning templates rather than content.
  • —Training a model whose output will reach students without human review.

Limitations

  • —48.5% distinct outputs, with the same contentless misconception placeholder as the base dataset.
  • —Near-duplicate of [`k12-mathematics-standards-aligned`](https://huggingface.co/datasets/robworks-software/k12-mathematics-standards-aligned). 4,965 rows versus 4,397 from the same generator over the same taxonomy - a 13% increase, not a distinct resource. Pick one.
  • —Prior descriptions claimed college and competition-level coverage. The content does not support that; it is K-12 templated material throughout.
  • —No worked mathematics.
  • —No educator or subject-matter review at any stage.
  • —`quality_score`, `difficulty`, `bloom_level` and `dok_level` are generator assignments, not expert annotations. A high quality score reflects a rule firing, not a judgment about instructional value.
  • —Sparse metadata. Many optional metadata columns are nan for most rows.
  • —US-centric and English-only.

Source taxonomy

Common Core State Standards mathematics structure. Standard codes are public; generated text is original output of this project.

License

CC-BY-4.0 for this compilation and its generated text.

Citation

bibtex
@dataset{k12_mathematics_standards_expanded,
  title  = {K-12 Mathematics Standards, expanded (generated instruction data)},
  author = {Robworks Software},
  year   = {2025},
  publisher = {Hugging Face},
  note   = {Programmatically generated instruction-tuning data; not official standard text},
  url    = {https://huggingface.co/datasets/robworks-software/k12-mathematics-standards-expanded}
}