用NLP自动生成主观题并评分，助力教育评估与自学
Subjective Question Generation and Answer Evaluation using NLP
- 基于文本输入生成开放性问题，结合语义理解匹配答案
- 提升教师批改效率，支持学生自主评估学习效果
- 填补自动化主观题生成与评价的空白，适合教育AI研究者
自然语言处理（NLP）是当今最具革命性的技术之一，利用人工智能理解人类文本和口语，广泛应用于文本摘要、语法检查、情感分析及智能对话系统。它在教育领域也展现出巨大潜力。尽管客观题生成已有较多研究，但自动主观题生成与答案评估仍处于发展阶段。本文旨在改进现有NLP模型或提出新模型，实现从文本输入中自动生成主观问题并评估答案。该系统可帮助教师高效批改作业，同时使学生在阅读文章或章节后进行自我评估，从而增强学习体验。
原文摘要 · Abstract (English)
Natural Language Processing (NLP) is one of the most revolutionary technologies today. It uses artificial intelligence to understand human text and spoken words. It is used for text summarization, grammar checking, sentiment analysis, and advanced chatbots and has many more potential use cases. Furthermore, it has also made its mark on the education sector. Much research and advancements have already been conducted on objective question generation; however, automated subjective question generation and answer evaluation are still in progress. An automated system to generate subjective questions and evaluate the answers can help teachers assess student work and enhance the student's learning experience by allowing them to self-assess their understanding after reading an article or a chapter of a book. This research aims to improve current NLP models or make a novel one for automated subjective question generation and answer evaluation from text input.
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