Research in Engineering Education Symposium 2011 - rees2009

Universidad Politécnica de Madrid (UPM) Página 389 de 957
Table 1: Loading from the exploratory factor analysis
Note: Light grey shading denotes the components that have a loading above 0.32 in more than one factor.
Multidimensional scaling
Multidimensional scaling was used to visualize the network of components that influence
student retention (using the same 34 components that were used for exploratory factor
analysis). Network theory data analysis tools and complexity thinking were used to
interpret the results.
Network Creation
Multidimensional scaling analysis was used on the data to determine the distances
between components arising from this data. We used the multidimensional proximities
between the components to identify components with relative closeness. Analysis
continued as long as the network continued to resemble a decentralized network
(Freeman, 1978).
At a cut-off proximity of 0.1 less than half the components remain connected to one
another. Thus two components were considered to be within each others’ “zone of
influence” when their proximity was below 0.25. To retain the connectedness of the
system Retention needed to have a higher cut-off of 0.5. Four other components dropped
out of the network at the 0.25 level. Three particularly influential components (nodes)
were identified. Figure 1 gives a visualization of the network showing connections
between components, not their proximities.
Proceedings of Research in Engineering Education Symposium 2011
Madrid, 4 th - 7 th October 2011