Research in Engineering Education Symposium 2011 - rees2009

Universidad Politécnica de Madrid (UPM) Página 746 de 957
The Center for Research in Creativity and Higher Education-CICES has been involved in
studies aimed at enhancing institutional knowledge about learning, as a way of improving
retention rates,. A novel approach has been chosen as complementary to others already in
course. This approach relates at developing and applying some measures of learning
processes that can be associated to what the authors call ―Learning dynamics‖. Here
―dynamics‖ is meant to encompass concepts such as speed, time-rates, energy and power
(energy per unit time), mainly. We have worked around a pivotal hypothesis: in some
academic programs student success is dependent, among other factors, on learning speed
and other related variables. This is assumed to be applicable to engineering where novice
students have to learn a large number of new and complex concepts in short time. At this
stage of and ongoing research the main goal is to verify whether or not it is possible to
detect significant individual differences as to learning dynamic variables. Such differences,
according to the main hypothesis, should be related, at least in some cases, to learning
success in engineering. In this paper are presented some results concerning the
identification of individual differences.
A set of tests has been developed for measuring learning speed, mind power and mind
resistance. These variables are supposed here to be related as in other physical systems.
The research outcomes have demonstrated, in all groups tested, that significant individual
differences appear referring to test performance.
Background
Researches referring to individual cognitive differences have historically been made
regarding three points of view: psychometric structure of individual differences (Vernon,
1950); predictive validity of evidence gathering instruments (Deary, Whalley, Lemmon,
Crawford, & Starr, 2000); and supposed causes of individual differences in terms of
psychometric and cognitive components, and biological rates (Deary, 2001). This last
approach is the most relevant for this research.
Many studies have shown some degree of relation between peripheral nerve conduction
velocity and intelligence, or other cognitive sub-abilities, obtaining interesting correlations
(Rijsdijk, 1997), some have referred to it as efficient use of cerebral resources, ie. mental
power (Reed, Vernon & Johnson, 2004). Other researchers have proposed that personal
differences on mental capacities for executing specific tasks depend on factors like glucose
consume, and brain signal’s speed, among others. This would explain differences on
intelligence (Vernon et al., 2000).
All these studies intend to evaluate the mental capacity required to perform in specific
tasks. In the engineering education domain, this gains relevance; since study programs are
configured around learning outcomes, such as competences (Letelier et al., 2009).
Thus the challenge arisen for this study, as it has been anticipated, is to assess people
capacity to use brain energy, specifically regarding three concepts: mind resistance, mind
power and learning speed. We suggest that correctly using brain energy has a main role in
ability development, task accomplishment, and learning; three aspects that impact in first
year students’ academic performance.
Proceedings of Research in Engineering Education Symposium 2011
Madrid, 4 th - 7 th October 2011