Automated Essay Score (AES) is proven to be one of the cutting-edge technologies. Scoring techniques are used for various purposes. Reliable scores are calculated based on influential variables. Such variables can be computed by different methods based on the domain. The research is concentrated on the user's understanding of a given topic. The analysis is based on a scoring index by using Large Language Models. The user can then compare and contrast the understanding of a topic that they recently learned. The results are then contributed towards learning analytics and progression is made for enhancing the learning ability. In this research, the focus is on summarizing a PDF document and gauging a user's understanding of its content. The process involves utilizing a Langchain tool to summarize the PDF and extract the essential information. By employing this technique, the research aims to determine how well the user comprehends the summarized content.

翻译：自动作文评分（AES）已被证明是一项前沿技术。评分技术被用于多种目的，基于影响变量计算出可靠的分数。这些变量可根据不同领域的方法进行计算。本研究聚焦于用户对给定主题的理解程度，分析基于采用大语言模型的评分指标。用户可借此对比自身对近期所学主题的理解差异。研究结果将用于学习分析，并通过优化学习能力促进学习进程。本研究重点关注PDF文档摘要生成及用户对文档内容理解程度的评估。该过程利用LangChain工具对PDF进行摘要提取，从而获取核心信息。通过这一技术路线，本研究旨在判定用户对摘要内容的理解深度。