PROGRESSIVE TRANSITIONS FROM ALGORITHMIC TO CONCEPTUAL UNDERSTANDING IN STUDENT ABILITY TO SOLVE CHEMISTRY PROBLEMS - A LAKATOSIAN INTERPRETATION

The main objective of this study is to construct models based on strat egies students use to solve chemistry problems and to show that these models form sequences of progressive transitions similar to what the h istory of science refers to as progressive ''problemshifts'' that incr ease the explanatory/heuristic power of the models. Results obtained s how the considerable difference in student performance on chemistry pr oblems (mol, gases, solutions, and photoelectric effect) that require algorithmic or conceptual understanding. The difference between studen t performance on algorithmic and conceptual problems can be interprete d as a process of progressive transitions (models) that facilitate dif ferent degrees of explanatory power to student conceptual understandin g. A parallel is drawn between the methodology of idealization (simpli fying assumptions) used by scientists and the construction of strategi es (models) used by students to facilitate conceptual understanding. A major educational implication of this study is that the relationship between algorithmic and conceptual problems is not dichotomous, but ra ther characterized by a continuum that consists of sequences of models that facilitate greater conceptual understanding. This reconstruction of student strategies to solve problems (progressive transitions) can provide the teacher a framework to anticipate as to how student under standing could develop from being entirely algorithmic to conceptual. (C) 1995 John Wiley & Sons, Inc.