国际教育成就评价协会（IEA）：2016年EPIRLS中文本响应的操作自动评分：性能和语言差异报告（英文版）

In this project report, we report on the feasibility of automatic scoring systems for text responses from the 2016 ePIRLS. We show that the multilingual automatic scoring approach used in this study can be applied to different languages and countries, despite their linguistic variance. To measure linguistic variance, we used a variant of the conventional type-token-ratio, which we refer to as STTR. We utilized two systems for automatic scoring: fuzzy lexical matching (FLM) and supervised classif