README.md

---
license: unknown
task_categories:
- text-generation
language:
- en
tags:
- question generation
pretty_name: LeaningQ-qg
size_categories:
- 100K<n<1M
train-eval-index:
- config: plain_text
  task: question-generation
  task_id: extractive_question_generation
  splits:
    train_split: train
    eval_split: validation
    test_split: test
  col_mapping:
    context: context
    questionsrc: question source
    question: question
  metrics:
  - type: squad
    name: SQuAD
dataset_info:
  features:
  - name: context
    dtype: string
  - name: questionsrc
    dtype: string
  - name: question
    dtype: string
  config_name: plain_text
  splits:
  - name: train
    num_examples: 188660
  - name: validation
    num_examples: 20630
  - name: test
    num_examples: 18227
---

# Dataset Card for LearningQ-qg

## Dataset Description


- **Repository:** [GitHub](https://github.com/AngusGLChen/LearningQ#readme)
- **Paper:** [LearningQ: A Large-scale Dataset for Educational Question Generation](https://ojs.aaai.org/index.php/ICWSM/article/view/14987/14837)
- **Point of Contact:** s.lamri@univ-bouira.dz

### Dataset Summary

LearningQ, a challenging educational question generation dataset containing over 230K document-question pairs by [Guanliang Chen, Jie Yang, Claudia Hauff and Geert-Jan Houben]. It includes 7K instructor-designed questions assessing knowledge concepts being taught and 223K learner-generated questions seeking in-depth understanding of the taught concepts. This new version collected and corrected from over than 50000 error and more than 1500 type of error by [Sidali Lamri](https://dz.linkedin.com/in/sidali-lamri)

### Use the dataset

```python
from datasets import load_dataset
lq_dataset = load_dataset("sidovic/LearningQ-qg")
lq_dataset["train"][1]
len(lq_dataset["train"]),len(lq_dataset["validation"]),len(lq_dataset["test"])
```

### Supported Tasks and Leaderboards

[Question generation]

### Languages

[English]

## Dataset Structure

### Data Instances

An example of example looks as follows.
```
{
    
    "context": "This is a test context.",
    "questionsrc": "test context",
    "question": "Is this a test?"
}
```

### Data Fields

The data fields are the same among all splits.

- `context`: a `string` feature.
- `questionsrc`: a `string` feature.
- `question`: a `string` feature.
### Data Splits

|   name   |train |validation|test |
|----------|-----:|---------:|----:|
|LearningQ |188660|     20630|18227|

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

[More Information Needed]

### Citation Information

```
{
  author = {Sidali Lamri},
  title = {new LearningQ version for Question generation in transformers},
  year = {2023}
}
@paper{ICWSM18LearningQ,
	author = {Guanliang Chen, Jie Yang, Claudia Hauff and Geert-Jan Houben},
	title = {LearningQ: A Large-scale Dataset for Educational Question Generation},
	conference = {International AAAI Conference on Web and Social Media},
	year = {2018}
}
```

### Contributions

[More Information Needed]