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Selent, Douglas; Patikorn, Thanaporn; Heffernan, Neil – Grantee Submission, 2016
In this paper, we present a dataset consisting of data generated from 22 previously and currently running randomized controlled experiments inside the ASSISTments online learning platform. This dataset provides data mining opportunities for researchers to analyze ASSISTments data in a convenient format across multiple experiments at the same time.…
Descriptors: Intelligent Tutoring Systems, Data, Randomized Controlled Trials, Electronic Learning
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Sao Pedro, Michael A.; Gobert, Janice D.; Betts, Cameron G. – Grantee Submission, 2014
There are well-acknowledged challenges to scaling computerized performance-based assessments. One such challenge is reliably and validly identifying ill-defined skills. We describe an approach that leverages a data mining framework to build and validate a detector that evaluates an ill-defined inquiry process skill, designing controlled…
Descriptors: Performance Based Assessment, Computer Assisted Testing, Inquiry, Science Process Skills
Hedges, Larry V.; Hedberg, Eric C. – Grantee Submission, 2013
Background: Cluster randomized experiments that assign intact groups such as schools or school districts to treatment conditions are increasingly common in educational research. Such experiments are inherently multilevel designs whose sensitivity (statistical power and precision of estimates) depends on the variance decomposition across levels.…
Descriptors: Correlation, Multivariate Analysis, Educational Experiments, Academic Achievement
Gobert, Janice D.; Kim, Yoon Jeon; Sao Pedro, Michael; Kennedy, Michael; Betts, Cameron – Grantee Submission, 2015
Many national policy documents underscore the importance of 21st century skills, including critical thinking. In parallel, recent American frameworks for K-12 Science education call for the development of critical thinking skills in science, also referred to as science inquiry skills/practices. Assessment of these skills is necessary, as indicated…
Descriptors: Learning Analytics, Science Education, Teaching Methods, 21st Century Skills
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Sao Pedro, Michael A.; Baker, Ryan S. J. d.; Gobert, Janice D. – Grantee Submission, 2013
When validating assessment models built with data mining, generalization is typically tested at the student-level, where models are tested on new students. This approach, though, may fail to find cases where model performance suffers if other aspects of those cases relevant to prediction are not well represented. We explore this here by testing if…
Descriptors: Educational Research, Data Collection, Data Analysis, Generalizability Theory
Gobert, Janice Darlene; Sao Pedro, Michael A.; Baker, Ryan S. – Grantee Submission, 2012
In this paper we explored whether engaging in two inquiry skills associated with data collection, designing controlled experiments and testing stated hypotheses, within microworlds for one physical science domain (density) impacted the acquisition of inquiry skills in another domain (phase change). To do so, we leveraged educational data mining…
Descriptors: Data Collection, Learning Analytics, Inquiry, Science Process Skills
Hershkovitz, Arnon; Baker, Ryan S. J. d.; Gobert, Janice; Wixon, Michael; Sao Pedro, Michael – Grantee Submission, 2013
In recent years, an increasing number of analyses in Learning Analytics and Educational Data Mining (EDM) have adopted a "Discovery with Models" approach, where an existing model is used as a key component in a new EDM/analytics analysis. This article presents a theoretical discussion on the emergence of discovery with models, its…
Descriptors: Learning Analytics, Models, Learning Processes, Case Studies