基于遗传算法和自然语言处理的书面活动词汇句法评价:ENEM实验

Jário Santos, R. Paiva, I. Bittencourt
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引用次数: 0

摘要

信息和通信技术的使用在教育中日益突出。目前,有几种技术为远程学习提供支持。在此场景之前,数以百万计的用户拥有海量的教育数据,这些评估给教师带来了负担,消耗了他们的时间,学生只能等待对他们表现的评估。随着计算机自动校正技术的使用,活动的流动性更大,教师的工作量相应减少,他们可以自由地评价别人的活动。本文介绍了一种使用遗传算法和自然语言处理- NLP的词汇句法分析器,用于自动评估葡萄牙语的书面活动。该系统通过实验对大约20个书面活动进行了评估,它发现并评估了以前由人工纠错器识别的错误。结果表明,对于检测到的错误,适当的建议率很高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lexical-Syntactic Evaluation of written activities based on Genetic Algorithm and Natural Language Processing: An experiment on ENEM
The use of information and communication technologies is increasingly standing out in Education. Currently, there are several technologies that provide support for distance learning. Before this scenario, there are millions of users with an huge amount of educational data, which evaluation burdens teachers and consume their time, leaving the students waiting for the evaluation of their performance. With the use of automatic correction technics performed by computers, there is a bigger fluidity of activities and a relevant decrease of work for the teachers, leaving them free to evaluate others activities. This paper presents a lexical-Syntactic Analyzer for automatic evaluation of written Activities in Portuguese using Genetic Algorithms and Natural Language Processing – NLP. The proposed system was evaluated by experiment, about 20 written activities and it found and evaluated the mistakes previously identified by human correctors. The results demonstrated a high rate of appropriate suggestions for the errors detected.
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