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Direct linkYang, Zhitong – ProQuest LLC, 2019
Computer-based assessments allow practitioners to collect rich process data by logging students' interactions with assessment tasks. In addition to providing final responses to test questions, computer-based assessments promise to furnish more evidence to support claims about what a student knows and can do through logging process data in log…
Descriptors: Problem Solving, Computer Assisted Testing, Data Analysis, Foreign Countries
Peer reviewedTeig, Nani; Scherer, Ronny; Kjaernsli, Marit – Journal of Research in Science Teaching, 2020
Previous research has demonstrated the potential of examining log-file data from computer-based assessments to understand student interactions with complex inquiry tasks. Rather than solely providing information about what has been achieved or the accuracy of student responses ("product data"), students' log files offer additional…
Descriptors: Science Process Skills, Thinking Skills, Inquiry, Simulation
Download full textGibson, 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
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
