Research in Engineering Education Symposium 2011 - rees2009

Universidad Politécnica de Madrid (UPM) Página 385 de 957
careers in science and technology in many countries, particularly in the developed world
(CSEPP, 2007, OECD, 2009).
Moreover, in many countries the percentage of students who manage to successfully
complete their degrees in engineering programmes in minimum time, or at all, is
decreasing (CSEPP, 2007, OECD, 2009). It is our aim in this study to develop a model of
student retention that will be able to inform such institutions of the most critical features
affecting student retention, together with how they are related to one another, to enable
them to make better decisions with regard to improving retention.
Research Questions
The aim just outlined leads to the following research questions:
Can the use of complexity thinking provide helpful insights into the relationships
between the variables affecting student retention in programmes such as
engineering, which are not provided by current models of student retention?
Can these insights help us to improve the retention in engineering programmes?
We have undertaken a pilot study that will help us to address these questions.
Theoretical Framework: Complexity thinking
In this section, we will present the concepts that we draw upon from complexity thinking
to produce a more powerful and holistic modelling system of student retention.
Complexity thinking aims to describe and understand complex systems and their capacity
to show order, patterns, and structure. Especially important is how these orders, patterns
and structures seem to emerge spontaneously from interactions between components of
systems, as well as between them and the external world.
Complexity thinking is often pitted against “classical science”, which is, in turn, portrayed
in terms of efforts to condense phenomena into their simplest components. However, to
obtain a reasonable portrayal of a complex phenomenon, an understanding of the
properties of the components alone is not sufficient. What is central in describing or
understanding a complex system is identifying the components, their interactions, and
what emerges from the complex system: its behaviours, properties and structures, or the
“structuring structures” of the complex system (Bourdieu, 1984).
The structure of complex systems
Three types of network structures may be identified:
1. Centralized networks have a single central node with every other node connected
only to that central node. Centralized networks spread information effectively, but
they are vulnerable to break down due to the dependency on the central node.
Proceedings of Research in Engineering Education Symposium 2011
Madrid, 4 th - 7 th October 2011