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Debeer, Dries; Janssen, Rianne; De Boeck, Paul – Journal of Educational Measurement, 2017
When dealing with missing responses, two types of omissions can be discerned: items can be skipped or not reached by the test taker. When the occurrence of these omissions is related to the proficiency process the missingness is nonignorable. The purpose of this article is to present a tree-based IRT framework for modeling responses and omissions…
Descriptors: Item Response Theory, Test Items, Responses, Testing Problems
Gibson, David C.; Webb, Mary; Ifenthaler, Dirk – International Association for Development of the Information Society, 2015
This paper briefly discusses four measurement challenges of data science or "big data" in educational assessments that are enabled by technology: 1. Dealing with change over time via time-based data. 2. How a digital performance space's relationships interact with learner actions, communications and products. 3. How layers of…
Descriptors: Measurement, Data Analysis, Psychometrics, Correlation
Ranguelov, Stanislav; Horvath, Anna; Dalferth, Simon; Noorani, Sogol – Education, Audiovisual and Culture Executive Agency, European Commission, 2011
This report on Key Data on Learning and Innovation through ICT at School in Europe 2011 builds on the previous Eurydice publications on information and communication technology in schools in Europe. It also aims to extend the theoretical framework by looking not only at the teaching and learning of ICT but also at the use of ICT to promote…
Descriptors: Educational Technology, Information Technology, Educational Innovation, Teaching Methods
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection

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