Digital Library

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Title:      DATA CHALLENGES OF LEVERAGING A SIMULATION TO ASSESS LEARNING
Author(s):      David Gibson, Peter Jakl
ISBN:      978-989-8533-18-0
Editors:      Demetrios G Sampson, J. Michael Spector, Dirk Ifenthaler and Pedro Isaías
Year:      2013
Edition:      Single
Keywords:      Learning analytics, simulation, digital game-based learning, adaptive learning
Type:      Full Paper
First Page:      141
Last Page:      149
Language:      English
Cover:      cover          
Full Contents:      click to dowload Download
Paper Abstract:      Among the unique affordances of digital simulations are changes in the possibilities for targets as well as the methods of assessment, most significantly, toward integration of thinking with action, embedding of tasks-as-performance of knowledge-in-action, and unobtrusive observational methods. This paper raises and briefly defines key data challenges of assessing learning in a complex domain of performance within a digital simulation, which at the atomistic level include time and event segmentation, cyclic dynamics, multicausality, intersectionality, and nonlinearity. At the summary level, the key challenge is model building. An example of a simulation designed to develop teachers - simSchool – is integrated with an adaptive content delivery and analytics database – Leverage – which grounds the discussion.
   

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