kasi-ranaweera/Sri_Lankan_UGC_Cutoff_Mark_Dataset

Sri Lankan University Z-Score Recommendations

This dataset supports the Z-Score University Finder project, providing recommendations for Sri Lankan Advanced Level (A/L) students based on their Z-Score, academic stream, and district. It is designed for educational research and building recommendation systems for university admissions.

Provenance

Sources

The dataset is derived from aggregated historical university admission data from the University Grants Commission (UGC) of Sri Lanka and public university records (e.g., University of Moratuwa, University of Colombo). The course_demand column reflects minimum Z-Score cutoffs for courses, compiled from UGC annual reports or estimated from historical trends. [If hypothetical, replace with]:

This dataset is a hypothetical representation created for demonstration purposes, mimicking real-world admission patterns for Sri Lankan universities. It is not sourced from official records.

Collection Methodology

Data was collected by:

• Compiling admission statistics from UGC annual reports (e.g., Minimum Z-Scores for Selection to Courses of Study for the Academic Year 2023/2024) and university prospectuses.
• [If applicable] Web scraping course and Z-Score data from public educational portals, ensuring compliance with terms of service.
• [If applicable] Synthetically generating data based on statistical distributions of Z-Scores and admission cutoffs. Transformations:
• Cleaning: Removed missing values and duplicates using pandas:

  import pandas as pd
  df = pd.read_csv('dataset.csv')
  df = df.dropna().drop_duplicates()
  

• Standardization: Ensured consistent naming for District (e.g., "Colombo" instead of "Colombo District"), Stream (e.g., "Physical Science" instead of "Physics"), and University.
• Feature Engineering: Added course_demand column based on historical cutoffs or estimated thresholds (e.g., Engineering at Moratuwa: 2.8).
• Format Conversion: Converted raw data to CSV with columns: District, Stream, Course, University, Z_Score, course_demand.
• Validation: Verified data integrity (e.g., Z_Score and course_demand as floats) using:

  assert df['Z_Score'].dtype == float
  df.to_csv('dataset.csv', index=False)
  

Citations

• University Grants Commission, Sri Lanka. (2024). Minimum Z-Scores for Selection to Courses of Study for the Academic Year 2023/2024. [Link, if available]. [If hypothetical]:

  No external citations, as the dataset is synthetic.

Usage

Load the dataset using the datasets library:

from datasets import load_dataset
dataset = load_dataset("kasi-ranaweera/Sri_Lankan_UGC_Cutoff_Mark_Dataset")
print(dataset)

Ethical Considerations

• Bias: The dataset may reflect historical admission biases (e.g., regional or stream-based disparities). Users should validate recommendations for fairness.
• Privacy: No personal data is included, as the dataset aggregates public admission statistics or is hypothetical.
• Usage: Intended for educational and research purposes. Avoid using for commercial purposes without verifying the license.

Limitations

• Coverage: May not include all Sri Lankan universities or courses.
• Accuracy: Z-Score cutoffs (course_demand) are based on historical data or estimates and may not reflect current admission criteria.
• [If hypothetical]: As a synthetic dataset, it may not fully represent real-world admission patterns.