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BioWorldParser: A suite of parsers for leveraging educational data mining techniques

机译：BioWorldParser：用于利用教育数据挖掘技术的一套解析器

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摘要

There has been a dramatic expansion in both the amount of available large-scale educational databases and educational mining techniques. Educational data mining has been a fertile subject of research in recent times; further, the use of educational data mining has become popular among both researchers and practitioners. Log files generated by computer-based learning environments like Intelligent Tutoring Systems contain a wealth of information about learner behaviors that characterize academic success. There is growing interest in mining these data sources for knowledge-based discovery to reveal relevant, meaningful, and useful educational information to illuminate our understanding of learners' behaviors and outcomes. All too often however, extracting the pertinent information from the data to leverage the data mining techniques can be a major roadblock; for example, the asynchronous nature of the data logged in computer-based learning environments and data mining tools pose several challenges for mining data. We sought to mitigate this by developing a parser for the BioWorld System. In this paper, we explore the viability of a hand-coded parser by presenting BioWorldParser (a suite of scripts), which was developed to parse and retrieve data from raw log files generated by the BioWorld system, to help leverage educational data mining techniques in the context of an Intelligent Tutoring System for the medical domain.
机译：可用的大型教育数据库和教育挖掘技术的数量都有一个急剧扩张。教育数据挖掘是最近研究的肥沃主题;此外，教育数据挖掘的使用已经在研究人员和从业者中流行。由智能辅导系统等计算机的学习环境生成的日志文件包含有关学习表征学习成功的学习行为的大量信息。对挖掘这些数据来源的兴趣越来越感兴趣，以揭示相关，有意义和有用的教育信息，以照亮我们对学习者行为和结果的理解。然而，常常常见，从数据中提取相关信息以利用数据挖掘技术可以是一个主要的障碍;例如，基于计算机的学习环境和数据挖掘工具中记录的数据的异步性质对挖掘数据构成了几个挑战。我们试图通过为BioWorld系统开发解析器来缓解这一点。在本文中，我们通过呈现BioWorldParser（一套脚本）来探讨手编码解析器的可行性，这是开发的，用于从BioWorld系统生成的原始日志文件中解析和检索数据，以帮助利用教育数据挖掘技术医疗领域智能辅导系统的背景。

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