首页> 外文期刊>Intelligent automation and soft computing >An E-Assessment Methodology Based on Artificial Intelligence Techniques to Determine Students' Language Quality and Programming Assignments' Plagiarism
【24h】

An E-Assessment Methodology Based on Artificial Intelligence Techniques to Determine Students' Language Quality and Programming Assignments' Plagiarism

机译:基于人工智能技术的电子评估方法,用于确定学生的语言质量和编程作业的抄袭

获取原文
获取原文并翻译 | 示例
           

摘要

This research aims to an electronic assessment (e-assessment) of students' replies in response to the standard answer of teacher's question to automate the assessment by WordNet semantic similarity. For this purpose, a new methodology for Semantic Similarity through WordNet Semantic Similarity Techniques (SS-WSST) has been proposed to calculate semantic similarity among teacher' query and student's reply. In the pilot study-1 42 words' pairs extracted from 8 students' replies, which marked by semantic similarity measures and compared with manually assigned teacher's marks. The teacher is provided with 4 bins of the mark while our designed methodology provided an exact mcamre of marks. Secondly, the source codes plagiarism in students' assignments provide smart e-assessment. The WordNet semantic similarity techniques are used to investigate source code plagiarism in binary search and stack data structures programmed in C++, Java, C# respectively.
机译:这项研究旨在对学生的回答进行电子评估(电子评估),以响应教师提问的标准答案,从而通过WordNet语义相似性自动进行评估。为此,提出了一种通过WordNet语义相似度技术(SS-WSST)进行语义相似度计算的新方法,以计算教师查询和学生答复之间的语义相似度。在试点研究1中,从8个学生的答复中提取了42个单词对,这些单词对通过语义相似性度量进行标记,并与手动分配的教师评分进行比较。向老师提供了4个标记盒,而我们的设计方法则提供了确切的标记集。其次,学生作业中的源代码窃可提供智能的电子评估。 WordNet语义相似性技术用于调查二进制搜索中的源代码抄袭和分别以C ++,Java和C#编程的堆栈数据结构。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号