New Methods for New Methods
Version 2 2018-01-21, 02:12
Version 1 2016-09-21, 12:08
Posted on 2018-01-21 - 02:12 authored by Gavin T. L. Brown
This collection provides work on the challenge of preparing doctoral students in education to develop competence in the advanced statistical methods they need to properly analyse the complex data that education generates.
For example: Knowing whether a new curriculum program has
impact over the status quo requires matching students in the innovation schools
with similar students in a counterfactual situation (propensity matching),
while taking into account that students are taught in groups which influence
the nature of an innovation (nested hierarchical analysis) and that some students
will be absent at data collection points (missing data analysis), and
determining the effect of change (longitudinal value added analysis) may have
to use non-equivalent measures of effectiveness (equating required) and take
into account multiple confounding factors.
Thus, this collection provides source documents and working documents around the idea that new ways of teaching and designing curriculum are probably needed to assist future post-doctoral researchers to cope with the complexity of educational data.CITE THIS COLLECTION
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Brown, Gavin T. L. (2016). New Methods for New Methods. The University of Auckland. Collection. https://doi.org/10.17608/k6.auckland.c.3469797.v2
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