This paper describes a method aimed at pointing out the quality of the mental models undergraduate engineering students deploy when asked to create explanations for phenomena or processes and/or use a given model in the same context. Student responses to a specially designed written questionnaire are quantitatively analyzed using researcher-generated categories of reasoning, based on the physics education research literature on student understanding of the relevant physics content. The use of statistical implicative analysis tools allows us to successfully identify clusters of students with respect to thesimilarity to the reasoning categories, defined as ‘‘practical or everyday,’’ ‘‘descriptive,’’ or ‘‘explicative.’’Through the use of similarity and implication indexes our method also enables us to study the consistencyin students’ deployment of mental models. A qualitative analysis of interviews conducted with studentsafter they had completed the questionnaire is used to clarify some aspects which emerged from thequantitative analysis and validate the results obtained. Some implications of this joint use of quantitativeand qualitative analysis for the design of a learning environment focused on the understanding of some aspects of the world at the level of causation and mechanisms of functioning are discussed.
|Numero di pagine||21|
|Rivista||PHYSICAL REVIEW SPECIAL TOPICS. PHYSICS EDUCATION RESEARCH|
|Stato di pubblicazione||Published - 2013|
All Science Journal Classification (ASJC) codes
- Physics and Astronomy(all)