Educational resource understanding is vital to online learning platforms,
which have demonstrated growing applications recently. However, researchers and
developers always struggle with using existing general natural language
toolkits or domain-specific models. The issue raises a need to develop an
effective and easy-to-use one that benefits AI education-related research and
applications. To bridge this gap, we present a unified, modularized, and
extensive library, \textit{EduNLP}, focusing on educational resource
understanding. In the library, we decouple the whole workflow to four key
modules with consistent interfaces including data configuration, processing,
model implementation, and model evaluation. We also provide a configurable
pipeline to unify the data usage and model usage in standard ways, where users
can customize their own needs. For the current version, we primarily provide 10
typical models from four categories, and 5 common downstream-evaluation tasks
in the education domain on 8 subjects for users' usage. The project is released
at: this https URL

教育资源理解对于在线学习平台至关重要，该研究旨在开发出一种统一、模块化、广泛应用的库（EduNLP），以实现有效且易于使用的自然语言处理工具，以促进人工智能教育相关研究和应用。