The Chemical Educator
ISSN: 1430-4171 (electronic version)
Abstract Volume 9
Issue 6 (2004) pp 398-405
Conceptual Understanding versus Algorithmic Problem Solving: A Principal Component Analysis of a National Examination
Dimitrios Stamovlasis, Georgios Tsaparlis,* Charalambos Kamilatos, Dimitrios Papaoikonomou, and Erifyli Zarotiadou
University of Ioannina, Department of Chemistry, GR-451 10 Ioannina, Greece, firstname.lastname@example.org
Received February 5, 2004. Accepted August 1, 2004.
Published online: 24 November 2004
Abstract. The present work analyzes the results of a national examination from the perspective of conceptual learning versus algorithmic problem solving. It is demonstrated that principal component analysis (PCA) can serve as a tool for scrutinizing examination papers in chemistry education. Further, national, large-scale examinations provide reliable data that are appropriate for such an analysis. Detailed achievement data were studied for the Greek national examination for a sample of 647 eleventh-grade students (age about 17) who were oriented toward science, engineering, or medicine. PCA led to the extraction of three factors: one factor concentrated on the (easiest) recall and simple application of knowledge questions; a second factor separated out the conceptual questions; finally, the third factor included all computational, well-practiced (algorithmic) questions. Some more demanding computational questions (requiring analysis and synthesis) had some bearing on the second factor as well. The above conclusions are supported by multivariate analysis of variance (MANOVA). Achievement was at about the same level for the conceptual and the more demanding algorithmic questions. A scheme suggested by Nakhleh (J. Chem. Educ. 1993, 70, 52–55) was also used to categorize the students in the various categories of algorithmic versus conceptual thinking. Finally, the implications of the findings are discussed.
Key Words: Research in Teaching and Learning; chemistry education research; conceptual understanding; algorithmic problem solving; quantitative methods; principal components analysis (PCA); national examinations; general chemistry
(*) Corresponding author. (E-mail: email@example.com)
The national examination questions in chemistry with the categorizing of those questions is included as supporting material (109 KB Zip file).
Issue date: December