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Harnessing the Currents of the Digital Ocean

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Learning Analytics

Abstract

The digital revolution concerns the shift in human history that allows the transformation of experiential inputs and work products into digital form that can be immediately collected, modified, moved, stored, and computed upon. This shift has already had remarkable social consequences and raises fundamental questions regarding the nature of science and knowledge. In the context of educational research, it raises key questions about the nature of our relationship with data in scientific endeavor and the role of computing systems and computational skills of researchers.

This paper extends the discussion begun by DiCerbo & Behrens (Computers and their impact on state assessment: Recent history and predictions for the future, Information Age, Charlotte, NC, pp. 273–306) which outlined how the societal shift related to the digital revolution can be understood in terms of a shift from a pre-digital “digital desert” to a post-digital “digital ocean.” Using the framework of Evidence Centered Design (Language testing, 19(4), 477–496, 2002) they suggest that the core processes of educational assessment and data collection can be re-thought in terms of new capabilities from computing devices and large amounts of data and suggest further that many of our original categories of educational activity represent views limited by their origination in the digital desert. After reviewing the core ideas of the digital desert to digital ocean shift, implications for understanding educational research are addressed in terms of methodological implications of this shift, including the role of data in hypothesis generation, the role of data in theory testing, the impact of continuous data generation and analysis, and the changing role of statistical and computational tools. Implications for training are addressed throughout.

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Correspondence to John T. Behrens .

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Behrens, J.T., DiCerbo, K.E. (2014). Harnessing the Currents of the Digital Ocean. In: Larusson, J., White, B. (eds) Learning Analytics. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3305-7_3

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