FoundationalASSIST dataset¶
Product or Programme · All products and programmes
Evidence · 2 claims (2 for) · 1 study (1 design),q2· 0 of 1 report an effect size · 2 claims rest on one study
Description¶
FoundationalASSIST is a dataset of ASSISTments mathematics interactions containing complete question text, actual student responses, distractor selections, and Common Core knowledge-component alignments for developing and evaluating educational AI and knowledge-tracing models.
Components¶
Claims¶
- Cognitive modeling of exact student responses is hardest for multi-select problems and rare-error answers, with select-all accuracy of only 12-15% and cognitive accuracy dropping to as low as 3.7% when answers are incorrect [+W]
- LLMs predict common distractors above chance but fall 15 percentage points below chance at predicting which errors students rarely select [+W]
Related Products and Programmes¶
- ALEKS and ALEKS PPL behavioral trace datasets for studying AI-era learning behavior
- Opiq 6th-grade mathematics interaction dataset from Estonia
- KDD Cup 2010 Bridge to Algebra dataset
Key Sources¶
- Eamon Worden, Cristina Heffernan, Neil Heffernan, and Shashank Sonkar. (2026). FoundationalASSIST: An Educational Dataset for Foundational Knowledge Tracing and Pedagogical Grounding of LLMs. https://arxiv.org/abs/2602.00070
Page metadata
| Field | Value |
|---|---|
type |
product |
id |
foundationalassist-dataset |
title |
FoundationalASSIST dataset |
description |
FoundationalASSIST is a dataset of ASSISTments mathematics interactions containing complete question text, actual student responses, distractor selections, and Common Core knowledge-component alignments for developing and evaluating educational AI and knowledge-tracing models. |
status |
review |
product_kind |
dataset |
generated |
by process:settle-candidates on 2026-10-12 |
trust |
unverified — no one has confirmed this page's content |
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