AP日语计算机模拟会话测试中考生回答的内容分析——一种有效性论证的混合方法

IF 1.4 2区 文学 0 LANGUAGE & LINGUISTICS
Nana Suzumura
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引用次数: 0

摘要

摘要本研究是一个更大的混合方法项目的一部分,该项目调查了日本语言文化高级入学考试的口语部分。它通过对考生反应的内容分析,调查了评估推断的假设。内容分析的结果与相同语音数据的多方面Rasch分析的结果相结合。本研究发现,大多数信息寻求提示都会引发具有相关内容的可评分语音样本,并且评分标准似乎符合互动的性质。因此,信息寻求提示通常为考生的能力提供了适当的证据。相比之下,非信息寻求提示,如请求和表达性提示,往往在引出具有相关内容的大小适中的可评分语音样本方面存在问题,并且他们在评分标准中实现的反应预期与互动的性质不符。因此,在当前的测试设计中,非信息寻求提示显示出更大的成为测量误差源的潜力。本文讨论了提高评价推理有效性的可能解决方案。本研究的结果将有助于未来基于计算机的二语测试的发展,该测试旨在评估人际沟通技能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Content Analysis of Test Taker Responses on an AP Japanese Computer-Simulated Conversation Test: A Mixed Methods Approach for A Validity Argument
ABSTRACT The present study is part of a larger mixed methods project that investigated the speaking section of the Advanced Placement (AP) Japanese Language and Culture Exam. It investigated assumptions for the evaluation inference through a content analysis of test taker responses. Results of the content analysis were integrated with those of a many-facet Rasch analysis of the same speech data. This study found that most information-seeking prompts elicited a good sized ratable speech sample with relevant content, and the rating criteria seemed to fit with the nature of the interaction. Therefore, information-seeking prompts generally provided appropriate evidence of test takers’ ability. In contrast, non-information-seeking prompts such as requests and expressive prompts tended to have issues with eliciting a good sized ratable speech sample with relevant content, and their response expectations realized in the rating criteria did not fit with the nature of the interaction. Thus, non-information-seeking prompts showed greater potential of becoming sources of measurement error with the current test design. This article discusses possible solutions to increase the validity of the evaluation inference. Findings from the present study would be useful for future test development of computer-based L2 tests that aim to assess interpersonal communication skills.
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来源期刊
CiteScore
6.40
自引率
3.40%
发文量
22
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