References

Research foundations and resources

Frameworks & Standards

Primary frameworks guiding our research methodology:

Global Scale of English (GSE)
Pearson Education Ltd. (2024). The Global Scale of English.
Framework adopted for granular language proficiency measurement, providing numerical alignment with CEFR levels.
Common European Framework of Reference (CEFR)
Council of Europe. (2001). Common European Framework of Reference for Languages: Learning, teaching, assessment.
Foundational framework for language proficiency classification.

Corpora & Datasets

Our research utilizes the following linguistic datasets:

British Council Learn English Corpus
British Council. (2024). Learn English Reading Resources.
learnenglish.britishcouncil.org/skills/reading
Primary source for calibrated ESL reading materials.

Technical Implementation

Core technologies and methodologies:

Natural Language Processing
- Python Scientific Stack (NumPy, Pandas)
- Spacy NLP Framework
- Custom ML Models for Text Analysis
Web Framework & Infrastructure
- Flask Framework (Python)
- RESTful API Architecture
- Containerized Deployment

Acknowledgments

CEFR.AI acknowledges the foundational work of numerous researchers and institutions in the field of language assessment. While we build upon established frameworks, all analysis tools and methodologies are independently developed.

Special thanks to the open-source community and academic partners who have contributed to this research.