Biomedical subjects

Dimitrios Stamovlasis

Publications and source records attributed to Dimitrios Stamovlasis.

3 recordsLinked to original sources

PubMed2006

The nonlinear dynamical hypothesis in science education problem solving: a catastrophe theory approach.

The current study tests the nonlinear dynamical hypothesis in science education problem solving by applying catastrophe theory. Within the neo-Piagetian framework a cusp catastrophe model is proposed, which accounts for discontinuities in students' performance as a function of two controls: the functional M-capacity as asymmetry and the degree of field dependence/independence as bifurcation. The two controls have functional relation with two opponent processes, the processing of relevant information and the inhibitory process of dis-embedding irrelevant information respectively. Data from achievement scores of freshmen at a technological college were measured at two points in time, and were analyzed using dynamic difference equations and statistical regression techniques. The cusp catastrophe model proved superior (R(2)=0.77) comparing to the pre-post linear counterpart (R(2)=0.46). Besides the empirical evidence, theoretical analyses are provided, which attempt to build bridges between NDS-theory concepts and science education problem solving and to neo-Piagetian theories as well. This study sets a framework for the application of catastrophe theory in education.

Humans↗

PubMed2003

A complexity theory model in science education problem solving: random walks for working memory and mental capacity.

The present study examines the role of limited human channel capacity from a science education perspective. A model of science problem solving has been previously validated by applying concepts and tools of complexity theory (the working memory, random walk method). The method correlated the subjects' rank-order achievement scores in organic-synthesis chemistry problems with the subjects' working memory capacity. In this work, we apply the same nonlinear approach to a different data set, taken from chemical-equilibrium problem solving. In contrast to the organic-synthesis problems, these problems are algorithmic, require numerical calculations, and have a complex logical structure. As a result, these problems cause deviations from the model, and affect the pattern observed with the nonlinear method. In addition to Baddeley's working memory capacity, the Pascual-Leone's mental (M-) capacity is examined by the same random-walk method. As the complexity of the problem increases, the fractal dimension of the working memory random walk demonstrates a sudden drop, while the fractal dimension of the M-capacity random walk decreases in a linear fashion. A review of the basic features of the two capacities and their relation is included. The method and findings have consequences for problem solving not only in chemistry and science education, but also in other disciplines.

Adolescent↗

PubMed2002

Achievement in chemistry problem-solving as a function of the mobility-fixity dimension.

The present studies explored the relation between students' achievement in chemistry problem-solving and the Mobility-Fixity dimension. Fixity characterizes consistency of function of field-independent subjects in a field-independent fashion, while Mobility provides for variation according to circumstances. The effect of this cognitive variable was examined as a function of the type and the complexity of the problem. Two kinds of problems were used, chemical equilibrium problems with varying mental demand and logical structure, and organic synthesis problems with varying mental demand. The subjects had to carry out different mental tasks, such as manipulation of logical schemata, applying algorithmic procedures, solving nonalgorithmic problems. In all cases, Mobile subjects demonstrated higher achievement than Fixed subjects. The results of this study support the hypothesis that the Mobility-Fixity dimension can serve as a predictor variable of students' performance on chemistry problem-solving.

Adolescent↗