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 the similarity 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 consistency in students’ deployment of mental models. A qualitative analysis of interviews conducted with students after they had completed the questionnaire is used to clarify some aspects which emerged from the quantitative analysis and validate the results obtained. Some implications of this joint use of quantitative and 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.

Student understanding of the laws that describe the flow of a fluid is often hampered by a defective knowledge of basic classical mechanics (kinematics, statics, dynamics, and conservation laws) and by wrong common-sense ideas about quantities related to fluids, such as velocity and pressure. A pedagogical discussion about the Venturi effect, based on experiments inspired by historical instruments, may be an effective way to introduce students to these laws. In this paper, we discuss an approach to the understanding of the Venturi effect based on the study of historical instruments and on simple experiments. In particular, after a presentation of the Venturi effect, also from a historical point of view, we illustrate some interesting applications, the Venturi meter, the Bunsen burner, the Venturi vacuum pump, and propose some simple experiments.

Many research papers have studied the problem of taking a set of data and separating it into subgroups through the methods of Cluster Analysis. However, the variables and parameters involved in Cluster Analysis have not always been outlined and criticized, especially in the field of Science...

Background: Research in Science Education has shown that often students need to learn how to identify differences and similarities between descriptive and explicative models. The development and use of explicative skills in the field of thermal science has always been a difficult objective to...