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Gould, Robert; Bargagliotti, Anna; Johnson, Terri – Statistics Education Research Journal, 2017
Participatory sensing is a data collection method in which communities of people collect and share data to investigate large-scale processes. These data have many features often associated with the big data paradigm: they are rich and multivariate, include non-numeric data, and are collected as determined by an algorithm rather than by traditional…
Descriptors: Secondary School Teachers, Logical Thinking, Data Collection, Data
Toure, Ibrahim – ProQuest LLC, 2017
Terrorism is a complex and evolving phenomenon. In the past few decades, we have witnessed an increase in the number of terrorist incidents in the world. The security and stability of many countries is threatened by terrorist groups. Perpetrators now use sophisticated weapons and the attacks are more and more lethal. Currently, terrorist incidents…
Descriptors: Data Analysis, Prediction, Terrorism, Risk
Rijmen, Frank – Educational Testing Service, 2010
As is the case for any statistical model, a multidimensional latent growth model comes with certain requirements with respect to the data collection design. In order to measure growth, repeated measurements of the same set of individuals are required. Furthermore, the data collection design should be specified such that no individual is given the…
Descriptors: Tests, Statistical Analysis, Models, Measurement
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Stamper, John; Barnes, Tiffany; Croy, Marvin – International Journal of Artificial Intelligence in Education, 2011
The Hint Factory is an implementation of our novel method to automatically generate hints using past student data for a logic tutor. One disadvantage of the Hint Factory is the time needed to gather enough data on new problems in order to provide hints. In this paper we describe the use of expert sample solutions to "seed" the hint generation…
Descriptors: Cues, Prompting, Learning Strategies, Teaching Methods
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Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis