Publication | Closed Access
A Theoretical Framework for Data-Driven Decision Making
117
Citations
24
References
2006
Year
Unknown Venue
EducationProgram EvaluationData ScienceManagementData-driven Decision MakingLuz RuvasDecision TheoryLinking DataHuman LearningCognitive ScienceLearning SciencesPredictive AnalyticsTheoretical FrameworkKnowledge DiscoveryEducational Data MiningLearning AnalyticsEducational MeasurementData-driven PlanningEvaluation MeasureLearning TheoryData-driven Decision-makingIntelligent Decision MakingEducational AssessmentData-driven LearningDecision ScienceEvaluation TechniqueWingspread ConferenceData Modeling
The research on which this paper is based has been funded by the National Science Foundation under Grant No. REC 03356653. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. The authors would like to acknowledge the contributions of the staff of the NSF evaluation framework project and other colleagues – Cornelia Brunner, Juliette Heinze, Hannah Nudell, and Luz Ruvas. This paper is based on a presentation made at the Wingspread Conference on Linking Data and Learning, October, 2005.
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