Framework Components
Library Partnership Network
The Fay Library is built through strategic partnerships with world-renowned academic institutions and digital repositories. These partnerships provide direct access to high-quality educational resources including textbooks, research papers, reference materials, and multimedia content that form the foundation of our comprehensive library collection.
MIT OpenCourseWare
Comprehensive textbooks, lecture notes, research papers, and reference materials from MIT's renowned engineering and science departments, providing our library with cutting-edge academic content.
Stanford Online
Research publications, academic papers, and educational materials from Stanford's leading faculty across computer science, business, medicine, and humanities departments.
OpenStax
Peer-reviewed textbooks and educational materials covering core academic subjects, professionally designed and available for library collection and student access.
Khan Academy
Educational videos, practice exercises, and instructional materials covering mathematics, science, and humanities for library reference and learning support.
Project Gutenberg
Classic literature and historical texts in the public domain, digitized and available for library collection to support literary and historical research.
Creative Commons
Curated collection of openly licensed educational materials across all subjects, providing clear licensing and attribution for library collection and access.
Library Curation Standards
Every resource in our OER framework undergoes rigorous evaluation to ensure academic excellence, content quality, and suitability for library collection and student access.
Our Curation Criteria
- Academic Accuracy: All materials are reviewed by subject matter experts and verified for accuracy
- Peer Review: Resources undergo peer review processes similar to academic publishing standards
- International Standards: Compliance with UNESCO OER guidelines and library standards
- Regular Updates: Continuous review and updating to maintain currency and relevance
- Legal Compliance: Proper licensing and attribution to ensure legal library use
- Collection Value: Clear assessment of resource value for library collection and student research
Library Curation Process
Content Review
Systematic evaluation of materials for accuracy, completeness, and library collection value
Expert Validation
Review by academic experts and librarians in relevant subject areas
Format Testing
Ensuring resources work across devices and platforms for optimal library access
User Feedback
Incorporation of student and faculty feedback to improve resource accessibility and value
Library Access & Inclusion
Our commitment to accessibility ensures that library resources are available to all users, regardless of their abilities, technological access, or geographical location.
Access Features
WCAG Compliance
All digital resources meet Web Content Accessibility Guidelines (WCAG) 2.1 AA standards
Multilingual Support
Library materials available in multiple languages with ongoing translation efforts
Mobile Optimization
Responsive design ensuring library access on smartphones, tablets, and low-bandwidth connections
Alternative Formats
Audio descriptions, captions, and text alternatives for multimedia library content
Offline Access
Downloadable formats for library materials in areas with limited internet connectivity
Zero Cost
All library resources are completely free, removing financial barriers to access
AI-Enhanced Learning Experience
Our framework integrates artificial intelligence to enhance the discovery, curation, and personalization of educational resources while maintaining cost efficiency and academic quality.
AI Capabilities
- Smart Curation: AI-powered analysis to identify the most relevant and high-quality resources
- Intelligent Search: Natural language processing for intuitive resource discovery
- Personalization: Adaptive recommendations based on learning preferences and progress
- Content Synthesis: AI-assisted compilation of resources into coherent learning materials
- Cost Optimization: Efficient AI usage prioritizing OER APIs to minimize costs
- Quality Metrics: Automated assessment of resource quality and educational value
Technical Implementation
Claude Haiku
Fast, efficient AI model for content analysis and user interaction processing
SDXL Integration
Advanced image generation for creating educational diagrams and visual aids
OER-First Architecture
Direct API integration with partner institutions for real-time resource access
Privacy Protection
Secure processing with user privacy and data protection as primary concerns