Datasets:

songdj
/

ScratchMath

	---
	license: cc-by-nc-sa-4.0
	task_categories:
	- visual-question-answering
	- image-classification
	- text-generation
	language:
	- zh
	tags:
	- education
	- math
	- error-analysis
	- handwritten
	- multimodal
	- scratchwork
	pretty_name: ScratchMath
	size_categories:
	- 1K<n<10K
	configs:
	- config_name: primary
	data_files: "primary/data-*.parquet"
	- config_name: middle
	data_files: "middle/data-*.parquet"
	dataset_info:
	- config_name: primary
	features:
	- name: question_id
	dtype: string
	- name: question
	dtype: string
	- name: answer
	dtype: string
	- name: solution
	dtype: string
	- name: student_answer
	dtype: string
	- name: student_scratchwork
	dtype: image
	- name: error_category
	dtype:
	class_label:
	names:
	0: 计算错误
	1: 题目理解错误
	2: 知识点错误
	3: 答题技巧错误
	4: 手写誊抄错误
	5: 逻辑推理错误
	6: 注意力与细节错误
	- name: error_explanation
	dtype: string
	splits:
	- name: train
	num_examples: 1479
	- config_name: middle
	features:
	- name: question_id
	dtype: string
	- name: question
	dtype: string
	- name: answer
	dtype: string
	- name: solution
	dtype: string
	- name: student_answer
	dtype: string
	- name: student_scratchwork
	dtype: image
	- name: error_category
	dtype:
	class_label:
	names:
	0: 计算错误
	1: 题目理解错误
	2: 知识点错误
	3: 答题技巧错误
	4: 手写誊抄错误
	5: 逻辑推理错误
	6: 注意力与细节错误
	- name: error_explanation
	dtype: string
	splits:
	- name: train
	num_examples: 241
	---

	<div align="center">

	# ScratchMath

	### Can MLLMs Read Students' Minds? Unpacking Multimodal Error Analysis in Handwritten Math

	AIED 2026 — 27th International Conference on Artificial Intelligence in Education

	[![Project Page](https://img.shields.io/badge/Project-Page-blue?style=for-the-badge&logo=googlechrome&logoColor=white)](https://bbsngg.github.io/ScratchMath/)
	[![Paper](https://img.shields.io/badge/Paper-PDF-red?style=for-the-badge&logo=adobeacrobatreader&logoColor=white)](https://bbsngg.github.io/ScratchMath/paper/ScratchMath_AIED2026.pdf)
	[![Code](https://img.shields.io/badge/Code-GitHub-black?style=for-the-badge&logo=github&logoColor=white)](https://github.com/ai-for-edu/ScratchMath)
	[![License](https://img.shields.io/badge/License-CC_BY--NC--SA_4.0-green?style=for-the-badge)](https://creativecommons.org/licenses/by-nc-sa/4.0/)

	</div>

	---

	## Overview

	ScratchMath is a multimodal benchmark for evaluating whether MLLMs can analyze handwritten mathematical scratchwork produced by real students. Unlike existing math benchmarks that focus on problem-solving accuracy, ScratchMath targets error diagnosis — identifying what type of mistake a student made and explaining why.

	- 1,720 authentic student scratchwork samples from Chinese primary & middle schools
	- 7 expert-defined error categories with detailed explanations
	- 2 complementary tasks: Error Cause Explanation (ECE) & Error Cause Classification (ECC)
	- 16 leading MLLMs benchmarked; best model reaches 57.2% vs. human experts at 83.9%

	---

	## Dataset Structure

	### Subsets

	\| Subset \| Grade Level \| Samples \|
	\|:------:\|:-----------:\|:-------:\|
	\| `primary` \| Grades 1–6 \| 1,479 \|
	\| `middle` \| Grades 7–9 \| 241 \|

	### Error Categories

	\| Category (zh) \| Category (en) \| Primary \| Middle \|
	\|:-:\|:-:\|:-:\|:-:\|
	\| 计算错误 \| Calculation Error \| 453 \| 113 \|
	\| 题目理解错误 \| Problem Comprehension Error \| 499 \| 20 \|
	\| 知识点错误 \| Conceptual Knowledge Error \| 174 \| 45 \|
	\| 答题技巧错误 \| Procedural Error \| 118 \| 17 \|
	\| 手写誊抄错误 \| Transcription Error \| 95 \| 29 \|
	\| 逻辑推理错误 \| Logical Reasoning Error \| 73 \| 2 \|
	\| 注意力与细节错误 \| Attention & Detail Error \| 67 \| 15 \|

	### Fields

	\| Field \| Type \| Description \|
	\|:------\|:----:\|:------------\|
	\| `question_id` \| string \| Unique identifier \|
	\| `question` \| string \| Math problem text (may contain LaTeX) \|
	\| `answer` \| string \| Correct answer \|
	\| `solution` \| string \| Step-by-step reference solution \|
	\| `student_answer` \| string \| Student's incorrect answer \|
	\| `student_scratchwork` \| image \| Photo of handwritten work \|
	\| `error_category` \| ClassLabel \| One of 7 error types \|
	\| `error_explanation` \| string \| Expert explanation of the error \|

	---

	## Quick Start

	```python
	from datasets import load_dataset

	# Load primary school subset
	ds_primary = load_dataset("songdj/ScratchMath", "primary")

	# Load middle school subset
	ds_middle = load_dataset("songdj/ScratchMath", "middle")

	# Access a sample
	sample = ds_primary["train"][0]
	print(sample["question"])
	print(sample["error_category"])
	sample["student_scratchwork"].show()
	```

	---

	## Citation

	If you use this dataset, please cite:

	```bibtex
	@inproceedings{song2026scratchmath,
	title = {Can MLLMs Read Students' Minds? Unpacking Multimodal Error Analysis in Handwritten Math},
	author = {Song, Dingjie and Xu, Tianlong and Zhang, Yi-Fan and Li, Hang and Yan, Zhiling and Fan, Xing and Li, Haoyang and Sun, Lichao and Wen, Qingsong},
	booktitle = {Proceedings of the 27th International Conference on Artificial Intelligence in Education (AIED)},
	year = {2026}
	}
	```

	---

	## License

	This dataset is released under the [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) license.