---
license: cc-by-nc-4.0
language:
- zh
pretty_name: EduData
size_categories:
- 10K<n<100K
task_categories:
- question-answering
- text-generation
task_ids:
- multiple-choice-qa
tags:
- education
- chinese
- exam
- reasoning
- llm
---

# 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

```json
{
  "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

## 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:

```bibtex
@inproceedings{guo2026cass,
  title     = {From Diagnosis to Generalization: A Cognitive Approach to Data Selection for Educational LLMs},
  author    = {Yuxiang Guo and Yan Zhuang and Qi Liu and Zhenya Huang and Xianquan Wang and Liyang He and Jiatong Li and Rui Li and Shijin Wang},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  year      = {2026}
}
```