README.md

---
license: mit
task_categories:
  - text-classification
language:
  - en
pretty_name: Reading Performance Dataset
size_categories:
  - n<1K
---

## 📘 Reading Performance Dataset

### 📌 Overview

The **Reading Performance Dataset** is a small-scale tabular dataset designed to analyze **reading behavior and performance characteristics across diverse individuals**.
It captures demographic attributes, reading habits, attention levels, and content difficulty to support educational data analysis and machine learning experiments.

This dataset is suitable for **educational analytics**, **behavioral analysis**, and **predictive modeling** related to reading performance.

### 📊 Dataset features

Each row represents a **single reading session**.
The dataset contains the following columns:

| Feature Name                    | Type        | Description                                                                               |
| ------------------------------- | ----------- | ----------------------------------------------------------------------------------------- |
| `AGE_CATEGORY`                  | Categorical | Age group of the reader (e.g., `young_adult`).                                            |
| `GENDER`                        | Categorical | Gender of the participant (`male`, `female`, `other`).                                    |
| `MAJOR`                         | Categorical | Academic major or role of the reader (e.g., `student`).                                   |
| `MINUTES_READING`               | Numeric     | Total duration (in minutes) spent actively reading during the session.                    |
| `MINUTES_BREAK`                 | Numeric     | Total break time (in minutes) taken during reading.                                       |
| `FOCUS_LEVEL`                   | Ordinal     | Level of focus during the reading session. Higher values indicate stronger concentration. |
| `PAGES`                         | Numeric     | Number of pages read during the session.                                                  |
| `CONTENT_LEVEL_ENUM`            | Ordinal     | Difficulty level of the reading material.                                                 |
| `READING_GENRE`                 | Categorical | Genre of the reading material (e.g., academic, language, self-development).               |
| `SOUND_VOLUME`                  | Ordinal     | Environmental sound intensity during reading, ranging from silent to extremely loud.      |
| `DEVICE`                        | Categorical | Device or medium used for reading (e.g., laptop, smartphone, book, tablet).               |
| `LOCATION`                      | Categorical | Physical environment where the reading session took place (e.g., home, library, café).    |
| `WEATHER`                       | Categorical | Weather condition during the reading session (e.g., sunny, rainy, cloudy).                |
| `MOOD`                          | Ordinal     | Emotional state of the reader during the session, from very bad to very good.             |
| `HUNGER`                        | Ordinal     | Hunger or satiety level during reading.                                                   |
| `AROUSAL`                       | Ordinal     | Cognitive arousal level, from very low to very high.                                      |
| `MENTAL_IN_BREAK`               | Ordinal     | Mental state during breaks (e.g., chaotic, neutral, calm).                                |
| `MENTAL_FATIGUE`                | Ordinal     | Level of mental fatigue experienced during the session.                                   |
| `INTERESTING_LEVEL`             | Ordinal     | Degree of interest in the reading material.                                               |
| `COMPREHENSION_DEPTH`           | Ordinal     | Depth of understanding achieved during reading.                                           |
| `LINKING_TO_PREVIOUS_KNOWLEDGE` | Ordinal     | Extent to which new content was connected to prior knowledge.                             |

### 🎯 Tasks

This dataset can be used for:

- Text / behavior classification
- Educational performance analysis
- Student reading habit modeling
- Correlation analysis between focus, time, and output
- Regression or classification experiments

Although categorized under **text classification**, the dataset is also applicable to **tabular machine learning tasks**.

### 🛠 Data Source & Generation

The dataset was **synthetically curated / collected for educational and analytical purposes**.
No personally identifiable information (PII) is included.

### ⚖️ License

This dataset is released under the **MIT License**, allowing free use, modification, and distribution with attribution.

### 🚀 Usage Example (Python)

#### Basic

```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("Bancie/Reading-Dataset")

# View dataset structure
print(dataset)

# Access the default split (usually 'train')
data = dataset['train']
print(f"Number of examples: {len(data)}")
print(f"Features: {data.features}")

# Access a specific example
print(data[0])

# Convert to pandas DataFrame for analysis
df = data.to_pandas()
print(df.head())
```

#### Streaming

For large datasets or when you want to process data without downloading it entirely:

```python
from datasets import load_dataset

# Load dataset in streaming mode
dataset = load_dataset("Bancie/Reading-Dataset", streaming=True)

# Iterate through examples
for example in dataset['train']:
    print(example)
    # Process your data here
    break  # Remove break to process all examples
```

### 📚 Citation

```bibtex
@misc{c.b_nguyen_2026,
	author       = { C.B Nguyen },
	title        = { Reading-Dataset (Revision 19cfbb0) },
	year         = 2026,
	url          = { https://huggingface.co/datasets/Bancie/Reading-Dataset },
	doi          = { 10.57967/hf/7416 },
	publisher    = { Hugging Face }
}
```