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A strategy for detection of inconsistency in evaluation of essay type answers

机译:评估论文类型答案中不一致之处的策略

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The quality of evaluation of essay type answer books involving multiple evaluators for courses with large number of enrollments is likely to be affected due to heterogeneity in experience, expertise and maturity of evaluators. In this paper, we present a strategy to detect anomalies in evaluation of essay type answers by multiple evaluators based on the relationship between marks/grades awarded and symbolic markers, opinionated words recorded in answer books during evaluation. Our strategy is based on the results of our survey with evaluators, analysis of large number of essay type evaluated answer books and our own experiences regarding grievances of students regarding marks/grades. Results of both survey and analysis of evaluated answer books identified underline, tick and cross as frequently used markers compared to circle and question mark. Further, both opinionated words and symbolic markers identified through the survey are used by evaluators to express either positive or negative sentiments. They have differential usage pattern of these symbols as single evaluator and as one amongst multiple evaluators. Tick and cross have well define purposes and have strong correlation with marks awarded. However, the underline marker is being used for dual purpose of expressing both correctness and incorrectness of answers. Our strategy of inconsistency detection first identifies outliers based on the relationship between marks/grades awarded and number of symbols and/or opinionated words used in evaluation. Subsequently, marks and number of symbolic markers of outliers are compared with peer non-outlier answer books having same marks but different number of markers used. Such outlier answer books are termed as anomalous. We discovered 36 anomalies out of total 425 evaluated answer books. We have developed a prototype tool to facilitate online evaluation of answer book and to proactively alert evaluators of possible anomalies.
机译:由于评估者经验,专业知识和成熟度的异质性,涉及多个评估者的论文类型答案书的评估质量可能会受到影响。在本文中,我们提出了一种策略,可根据授予的分数/等级与符号标记之间的关系,以及在评估过程中记录在答题簿中的有条理的单词,来检测由多个评估者评估论文类型答案的异常情况。我们的策略基于对评估人员的调查结果,对大量论文类型的答卷的分析以及我们对学生对成绩/等级的不满的经验。评估答卷的调查和分析结果均将下划线,刻度线和十字线标识为与圆圈和问号相比常用的标记。此外,评估人员使用通过调查确定的带有观点的单词和符号标记来表达正面或负面情绪。它们具有作为单个评估者和多个评估者之一的这些符号的不同用法模式。刻度线和十字线具有明确的目的,并且与授予的标记密切相关。但是,下划线标记用于表达答案的正确性和错误性的双重目的。我们的不一致检测策略首先根据所授予的分数/等级与评估中使用的符号和/或带有注释的单词数量之间的关系来识别异常值。随后,将异常值的标记和符号标记的数量与具有相同标记但使用的标记数量不同的同级非异常答案书进行比较。这样的异常答案书被称为异常。我们在425份经评估的答卷中发现了36​​个异常。我们开发了一个原型工具,以方便在线评估答题簿并主动提醒评估者可能出现的异常情况。

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