2023年12月15日下午，应上海对外经贸大学语言教育与测评中心 (CLEAR)邀请，上海外国语大学国际教育学院陈慧麟教授为我院师生带来了一场主题为 “语言测试中认知诊断的应用” 的线下研修坊。本次讲座由蔡雨阳教授主持，15名师生在博萃楼104参加了此次研修坊。
On the afternoon of December 15th, 2023, Professor Chen Huilin from the School of Education of Shanghai International Studies University (SISU) gave a workshop entitled “The application of cognitive diagnostic assessment in language testing” at the invitation of the Center for Language Education and Assessment Research (CLEAR) of Shanghai University of International Business and Economics (SUIBE). Professor Cai Yuyang chaired the workshop, and 15 students attended this event in BC104.
研修坊初始，蔡雨阳教授热烈欢迎陈慧麟教授的莅临。陈教授首先梳理了“经典测试—项目反应理论—认知诊断”这一测评理论发展脉络。接着引出认知诊断模型，结合图形对其定义、分类以及流程进行深入阐述。此外，陈教授还从理论概述、诊断试题、认知属性、模型比较、诊断反馈、理论启示等多个方面对认知诊断模型进行了全面综述，提供了丰富的文献资料，以为大家后续学习奠定基础。
At the beginning of the workshop, Professor Cai Yuyang extended a warm welcome to Professor Chen Huilin. Professor Chen first briefed us on the evolution of language testing theories, from classic test theory through item response theory to cognitive diagnostic assessment. Then, he elaborated via graphics on the cognitive diagnosis model, particularly its definition, classification, and processes. Afterward, he comprehensively reviewed the cognitive diagnostic models from aspects such as theoretical overview, diagnostic tests, cognitive attributes, model comparison, diagnostic feedback, theoretical enlightenment, etc. To facilitate the attendees’ further learning, the speaker also provided abundant relevant literature.
研修坊第二部分，陈教授结合认知诊断在选择题型的阅读测试中的实证研究，带领大家进行了具体演练。 陈教授及其博士研究生葛倩文同学首先指导大家安装R和R-studio软件，接着以PISA2009数据为例，演示了认知诊断模型中的GDINA模型的具体操作流程。从软件安装，数据导入，到实际的软件操作，陈教授详细指导了同学们的实际操作。在之后的环节中，陈教授就模型拟合、模型检验、模型修正以及可视化等方面进行了深入解释，且讲解了具体的参数（例如attribute level accuracy和absolute test fit）的合理取值范围，让听众对认知诊断模型和具体操作有了更深入的了解。
In the second part of the workshop, Professor Chen guided the audience to conduct a specific exercise based on empirical research on cognitive diagnosis in multiple-choice reading tests. Professor Chen and his doctoral student, Ge Qianwen, assisted us in installing R and R-studio software. Then he took PISA2009 data as an example to demonstrate the specific operation process of the GDINA model in the cognitive diagnosis model, specifically, software installation, data import, and software operation. Next, Professor Chen explained model fit, model testing, model modification, and visualization and explained the value ranges of specific parameters (such as attribute level accuracy and absolute test fit). This elaboration enabled attendees to better understand the CDM and its software operations.
研修坊第三部分，结合实际案例，陈教授讲授了如何创新性地将认知诊断模型应用于综合型写作任务（Reading-to-write)。首先，对认知属性进行定义，根据读后概述、思辨论证、文本组构等五个技能对测试描述语进行编码（coding），生成Q矩阵。其次，评分者根据描述语对写作任务进行评估和编码。研究过程发现RRUM模型拟合写作翻译类考试效果更好，写作技能的认知结构可分为概述技能群和论述技能群。陈教授对该研究的讲解引发了在座师生的积极讨论。
In the third part, Professor Chen introduced how to creatively apply the cognitive diagnostic model to integrated writing tasks (Reading-to-write) using an authentic writing task. First, the cognitive attributes were defined, and the test descriptors were coded based on the five skills of post-reading summary, speculative argumentation, textual organization, language, and grammar to generate a Q matrix. Secondly, raters assessed and coded the writing tasks based on the descriptors. During the research process, he and his colleagues found that the RRUM model fit better for writing and translation tasks. Besides, the cognitive structure of writing skills can be divided into summary skill groups and argumentation skill groups. Professor Chen’s explanation triggered active discussions among the attendees.
最后，蔡雨阳教授代表国际商务外语学院和CLEAR再次向陈慧麟教授致以诚挚的谢意。陈教授详尽的认知诊断模型讲解让在座的全体师生受益匪浅。这次研修坊为本院学生提供了学习认知诊断模型的宝贵机遇。。
In the end, on behalf of CLEAR, Professor Cai Yuyang once again expressed sincere gratitude to Professor Chen Huilin. Professor Chen’s detailed explanation of the CDM greatly inspired teacher and student attendees. This workshop provided a valuable opportunity for students at SUIBE to learn the CDM.
撰稿人：陈艳、徐修玥、王攀、左巧玲
Contributed by CHEN Yan, XU Xiuyue, WANG Pan, ZUO Qiaoling