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Special Issue on Big Data Sources in Educational Measurement

Introduction

As large-scale assessments, digital learning environments, and institutional systems generate increasingly complex data, they offer new opportunities for advancing research on student learning, assessment quality, and educational equity. This special issue presents three descriptive papers that introduce publicly shareable big data resources relevant to educational measurement, assessment, and evaluation. The three articles introduce a large-scale item response data repository, a longitudinal international assessment database for studying student growth, and a digital learning infrastructure supporting large-scale educational data. Together, this special issue aims to serve as both a practical reference for researchers seeking data and a catalyst for broader cultural change in the field of educational measurement, assessment, and evaluation toward greater openness, transparency, and equity in the use of large-scale educational data. -- Okan Bulut and Yi Zheng, co-editors of the special issue.

Articles

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The Item Response Warehouse: What It Is, How to Use It, and Targets for Potential Improvements
Savira D. Nadela, Hansol Lee, Nishka Jain, Ayaan Gupta, Xingyi Zhang, and Benjamin W. Domingue

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项目反应数据库:是什么、如何使用以及未来提升目标
Savira D. Nadela, Hansol Lee, Nishka Jain, Ayaan Gupta, Xingyi Zhang, and Benjamin W. Domingue

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Learning at Scale as Infrastructure: LMS Platforms, Data Pipelines, and Language-Based Evidence for Educational Measurement
Danielle S. McNamara, Michelle Banawan, Renu Balyan, Rod D. Roscoe, and Tracy Arner