Data Accessibility

Supporting students' work with authentic data requires a carefully developed and rigorously-tested curriculum to help them understand what the data represent, and to guide them in how to use data analysis tools and visualizations to identify meaningful patterns and develop evidence-based hypotheses.

About 20 years ago, psychologist Lynn Liben presented an model of the relationships among a learner, an external (i.e. not mental) representation, and those aspects of the real world represented by the representation (the “referent”). Liben notes that the learner can learn either through direct interactions with the real world or through interactions with a representation.

Presentation at American Geophysical Union Conference in San Francisco, December 2013

Keynote Address, IBM's Big Data and Analytics EdCon 2013, November 2, Las Vegas

The world is awash with data. This growth of data shows no signs of slowing, and indeed seems to be accelerating. Analyzing data, spotting patterns, and extracting useful information have become gateway skills to full participation in the workforce and civic engagement of the 21^st century. Yet pre-college classrooms are falling short of preparing students for this world. And they’re missing the opportunity to harness the power of big data to transform student learning.

(October 2012)

The "Fourth Paradigm" of Science, which seeks insight by mining vast archives of existing data rather than by doing experiments to gather new data, is being touted as a new method of doing science.  But Walter Pitman mined data archives in 1966, as did Tanya Atwater in 1970, so is “The Fourth Paradigm” really new?...

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