guoyx18/EduData

Dataset Card for EduData

Dataset Summary

EduData is a large-scale Chinese educational question-answering dataset released with our AAAI 2026 paper, "From Diagnosis to Generalization: A Cognitive Approach to Data Selection for Educational LLMs".

The dataset is designed to support the training and evaluation of educational large language models, with a particular focus on data selection, cross-subject transfer, and generalization in exam-style reasoning settings.

According to the accompanying paper, EduData contains 98,000 high-school-level single-choice questions spanning seven subjects:

• —Mathematics
• —Physics
• —Chemistry
• —Biology
• —History
• —Geography
• —Politics

The paper-organized version contains 14,000 questions per subject.

Supported Tasks

EduData is primarily intended for:

• —Supervised fine-tuning of educational LLMs
• —Multiple-choice question answering in Chinese
• —Research on data selection for LLM training
• —Cross-subject generalization and transfer learning
• —Reproduction of the CASS framework experiments

Language

The dataset is in Chinese. Question text is sourced from Chinese mock examinations and college-entrance-exam-style educational materials.

Dataset Structure

Current Release Format

The current release provides a merged JSON file:

• —EduData.json: 98,000 examples

Each example is stored in instruction-tuning format with the following fields:

• —instruction: the full prompt, including the question stem and answer options
• —input: an auxiliary input field; in the current release this is an empty string for all examples
• —output: the target answer in natural language form, typically 答案为 A/B/C/D
• —id: a unique sample identifier

Data Instance

{
  "instruction": "以下题目为单选题，只有一个正确选项，请根据问题文本和选项给出正确答案 题目文本为： 已知等差数列{$a_{n}},$满足$a_{2}+a_{11}=36,a_{8}=24,$则$a_{5}$等于$\\SIFChoice$ 选项为： (A) $6$ (B) $8$ (C) $10$ (D) $12$",
  "input": "",
  "output": "答案为  B",
  "id": "example-id"
}

Data Fields

• —instruction The main textual prompt. In most cases it includes a fixed instruction prefix, the question body, and four answer options.

• —input Reserved for optional auxiliary content. It is empty in the released EduData.json.

• —output The gold answer label. In the current release, the answer is written as short Chinese text rather than as a bare class label.

• —id A unique identifier for the example.

Data Characteristics

From inspection of the released EduData.json:

• —Total examples: 98,000
• —Unique IDs: 98,000
• —All input fields are empty strings
• —Answers cover the four options A/B/C/D
• —The data is formatted as instruction-following examples rather than as a separately structured question / choices / label schema

Subject mapping

id_subject_mapping.json provides the subject ID for each example in EduData.json. The two files can be joined using the id field.

The mapping covers all 98,000 examples and contains seven subject categories: 1, 3, 4, 5, 6, 7, and 9, with 14,000 examples per subject.

Out-of-Scope Use

This dataset is not intended for:

• —Commercial use
• —High-stakes educational decision-making without human oversight

Curation Rationale

EduData was created to support research on educational LLMs in realistic multi-subject settings. Existing educational datasets are often narrow in subject coverage or insufficient for studying whether a model can generalize beyond a single domain. Our goal was to build a challenging, high-quality benchmark that better reflects practical educational use cases and enables research on cognitively informed data selection.

Source Data

The dataset was curated from Chinese mock examinations and college-entrance-exam-style materials. The released data focuses on single-choice questions and was organized for educational QA and instruction-tuning use.

Processing

The current public release is distributed as instruction-tuning JSON records. During preprocessing, the project also maintained split files that were merged into the final EduData.json.

Biases, Risks, and Limitations

• —The dataset is Chinese-only and reflects one educational and cultural context
• —It is centered on exam-style single-choice questions rather than open-ended pedagogy
• —The merged release does not include explicit subject metadata per row
• —Some formatting noise from source documents remains in a small number of examples
• —Performance on this dataset should not be treated as a comprehensive measure of educational competence

Licensing

This dataset is released under CC BY-NC 4.0.

Commercial use is prohibited. Users are responsible for ensuring that their use complies with the dataset license and any applicable source-material restrictions.

Citation

If you use EduData or the CASS framework in your research, please cite:

@inproceedings{guo2026diagnosis,
  title={From Diagnosis to Generalization: A Cognitive Approach to Data Selection for Educational LLMs},
  author={Guo, Yuxiang and Zhuang, Yan and Liu, Qi and Huang, Zhenya and Wang, Xianquan and He, Liyang and Li, Jiatong and Li, Rui and Wang, Shijin},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={40},
  number={26},
  pages={21522--21530},
  year={2026}
}