Marilyne Stains - Classification of Chemical Substances Using Particulate Representations of Matter: An Analysis of Student Thinking

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      Publication Details (including relevant citation   information):

        Stains, M. & Talanquer, V. (2007). Classification of Chemical   Substances Using Particulate Representations of Matter: An   Analysis of   Student Thinking. International Journal of Science   Education, 29(5), 643-661; Erratum 29(7),   935 (2007).DOI:  10.1080/09500690600931129

      Abstract:

        We applied a mixed‐method research design to investigate the   patterns of reasoning used by novice undergraduate chemistry   students to classify chemical substances as elements, compounds,   or mixtures based on their particulate representations. We were   interested in the identification of the representational features   that students use to build a classification system, and in the   characterization of the thinking processes that they follow to   group substances in different classes. Students in our study used   structural and chemical composition features to classify chemical   substances into elements, compounds, and mixtures. Many of the   students’ classification errors resulted from strong mental   associations between concepts (e.g., atom–element,   molecule–compound) or from lack of conceptual differentiation   (e.g., compound–mixture). Strong concept associations led novice   students to reduce the number of relevant features used to   differentiate between substances, while the inability to   discriminate between two concepts (conceptual undifferentiation)   led them to pay too much attention to irrelevant features during   the classification tasks. Comparisons of the responses to   classification tasks of students with different levels of   expertise in chemistry indicate that some of these naïve patterns   of reasoning may be strengthened by, rather than weakened by,   training in the discipline.

      Address (URL): http://www.tandfonline.com/doi/abs/10.1080/09500690600931129