Upload class_participation dataset

README.md

@@ -0,0 +1,131 @@
+---
+license: mit
+task_categories:
+- tabular-regression
+- tabular-classification
+tags:
+- nigeria
+- education
+- africa
+- synthetic-data
+- class-participation
+language:
+- en
+size_categories:
+- 100K<n<1M
+pretty_name: Nigeria Education - Class Participation
+---
+
+# Nigeria - Class Participation
+
+## Dataset Description
+
+In-class student participation records with engagement levels and feedback.
+
+## Dataset Information
+
+- **Country**: Nigeria
+- **Dataset Name**: class_participation
+- **Total Records**: 100,000
+- **Total Columns**: 10
+- **File Size**: 1.54 MB
+- **Format**: Parquet (full data), CSV (sample)
+- **Generated**: 2025-10-21T23:15:59.001877
+
+## Schema
+
+| Column | Data Type | Description |
+|--------|-----------|-------------|
+| `participation_id` | object | Participation Id |
+| `student_id` | object | Student Id |
+| `participation_date` | datetime64[ns] | Participation Date |
+| `subject` | object | Subject |
+| `participation_type` | object | Participation Type |
+| `participation_score` | float64 | Participation Score |
+| `engagement_level` | object | Engagement Level |
+| `class_session` | float64 | Class Session |
+| `teacher_feedback` | object | Teacher Feedback |
+| `country` | object | Country |
+
+## Sample Data
+
+The dataset includes a 10,000-row sample in CSV format for quick exploration.
+
+## Data Quality
+
+- **Validation Status**: ✅ Passed
+- **Missing Data**: ~2-5% (realistic pattern)
+- **Data Type Enforcement**: Strict
+- **Cross-Dataset Consistency**: Maintained
+
+## Dependencies
+
+- `student_profiles`
+- `enrollment_registration`
+
+## Usage Example
+
+### Python (Pandas)
+```python
+import pandas as pd
+
+# Load full dataset
+df = pd.read_parquet('class_participation_full.parquet')
+print(f"Loaded {len(df):,} records")
+print(df.head())
+
+# Load sample
+df_sample = pd.read_csv('class_participation_sample.csv')
+print(df_sample.describe())
+```
+
+### Python (Hugging Face Datasets)
+```python
+from datasets import load_dataset
+
+# Load from Hugging Face
+dataset = load_dataset('nigeria-education-class_participation')
+df = dataset['train'].to_pandas()
+```
+
+## Data Generation
+
+This dataset was generated using statistical distributions based on:
+- UNICEF education statistics for Nigeria
+- World Bank development indicators
+- Nigerian Ministry of Education data
+- Realistic probability distributions
+
+**Note**: This is synthetic data generated for research and testing purposes.
+
+## Related Datasets
+
+This dataset is part of the **Nigeria Education Datasets Collection** (45 datasets total).
+
+Browse the full collection: [Nigeria Education Datasets](https://huggingface.co/collections/nigeria-education)
+
+## Citation
+
+```bibtex
+@dataset{nigeria_class_participation_2025,
+  title={Nigeria Education Dataset: Class Participation},
+  author={[Your Name/Organization]},
+  year={2025},
+  publisher={Hugging Face},
+  url={https://huggingface.co/datasets/nigeria-education-class_participation}
+}
+```
+
+## License
+
+[Specify your license]
+
+## Contact
+
+[Your contact information]
+
+---
+
+**Part of**: Nigeria Education Datasets Collection  
+**Total Datasets**: 45  
+**Country**: Nigeria 🇳🇬

class_participation_full.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f75b7afc2161bf594210dfb59fad3198464fa1d32596359881b835db400b61cc
+size 1619825

metadata.yaml

@@ -0,0 +1,36 @@
+columns:
+- participation_id
+- student_id
+- participation_date
+- subject
+- participation_type
+- participation_score
+- engagement_level
+- class_session
+- teacher_feedback
+- country
+country: Nigeria
+country_code: NGA
+dataset_name: class_participation
+dependencies:
+- student_profiles
+- enrollment_registration
+dtypes:
+  class_session: float64
+  country: object
+  engagement_level: object
+  participation_date: datetime64[ns]
+  participation_id: object
+  participation_score: float64
+  participation_type: object
+  student_id: object
+  subject: object
+  teacher_feedback: object
+file_size_mb: 1.544785499572754
+generated_at: '2025-10-21T23:15:59.001877'
+num_columns: 10
+num_rows: 100000
+validation:
+  checks: {}
+  passed: true
+version: 1.0.0