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\ud similarity to the reasoning categories, defined as ‘‘practical or everyday,’’ ‘‘descriptive,’’ or ‘‘explicative.’’\ud Through the use of similarity and implication indexes our method also enables us to study the consistency\ud in students’ deployment of mental models. A qualitative analysis of interviews conducted with students\ud after they had completed the questionnaire is used to clarify some aspects which emerged from the\ud quantitative analysis and validate the results obtained. Some implications of this joint use of quantitative\ud 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

The Boltzmann factor is the basis of a huge amount of thermodynamic and statistical physics, both classical and quantum. It governs the behaviour of all systems in nature that are exchanging energy with their environment. To understand why the expression has this specific form involves a deep mathematical analysis, whose flow of logic is hard to see and is not at the level of high school or college students' preparation. We here present some experiments and simulations aimed at directly deriving its mathematical expression and illustrating the fundamental concepts on which it is grounded. Experiments use easily available apparatuses, and simulations are developed in the Net-Logo environment that, besides having a user-friendly interface, allows an easy interaction with the algorithm. The approach supplies pedagogical support for the introduction of the Boltzmann factor at the undergraduate level to students without a background in statistical mechanics.

This paper describes an undergraduate experiment that yields the velocity distribution of thermionic electrons by analyzing the I-V characteristics of diodes and triodes. The experiment allows students to focus on the distribution function more than on difficulties arising from the complexity of thermionic emission. By using a simple model, the velocity distribution of thermionic electrons emitted by the vacuum tube cathode can be described by Maxwell’s distribution.

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.

The problem of taking a set of data and separating it into subgroups where the elements of each subgroup are more similar to each other than they are to elements not in the subgroup has been extensively studied through the statistical method of cluster analysis. In this paper we want to discuss the application of this method to the field of education: particularly, we want to present the use of cluster analysis to separate students into groups that can be recognized and characterized by common traits in their answers to a questionnaire, without any prior knowledge of what form those groups would take (unsupervised classification). We start from a detailed study of the data processing needed by cluster analysis. Then two methods commonly used in cluster analysis are before described only from a theoretical point a view and after in the Section 4 through an example of application to data coming from an open-ended questionnaire administered to a sample of university students. In particular we describe and criticize the variables and parameters used to show the results of the cluster analysis methods.

1 People's reasoning is often described as the "running" of the procedures present in their mental models [1-4]. Gilbert and Boulter [5] define expressed models as the external representations expressed by an individual through actions, speech, or writing. We understand "path, or line of reasoning" as the external representation of the mental models used by an individual when they try to describe, predict, or explain the physical world.

A small insect can stand or walk on water surface, drops of mercury do not spread on a solid surface, and a meniscus is formed at the free surface of a liquid contained in a thin vessel. These phenomena can be seen as macroscopic manifestations of molecular interactions and can be explained macroscopically in terms of surface tension. In this study, we deal with an approach to surface tension from a mechanical point of view, presenting a simple mesoscopic mechanical model of surface tension and the results of its implementation in numerical fluid dynamics simulations. Particularly, phenomena like droplet formation without gravity and with gravity when it can drop from a narrow hole like a trickling tap, the formation of a meniscus at the free surface of a liquid contained in a vessel, the behavior of a small piece of solid on a liquid surface, and a sessile droplet are studied. Student and teachers can study the behavior of a liquid due to the surface tension by using the numeric simulations as a “tool” for analyzing several different situations.

An open inquiry (OI)-based teaching/learning experience, regarding a scientific investigation of the process of energy exchange by thermal radiation, is presented. A sample of upper secondary school physics teachers carried out this experience at the University of Palermo, Italy, in the framework of ESTABLISH, a FP7 European Project aimed at promoting and developing inquiry-based science education. The teachers had the opportunity to personally experience an OI-based learning activity, with the aim of exploring the pedagogical potentialities of this teaching approach to promote both the understanding of difficult concepts and a deeper view of scientific practices. The teachers were firstly engaged in discussions concerning real-life problematic situations, and then stimulated to design and carry out their own laboratory activities, aimed at investigating the process of energy exchange by thermal radiation. A scientific study on the energy exchange between a powered resistor and its surrounding environment, during the heating and cooling processes, was designed and performed. Here we report the phases of this experiment by following the teachers' perspective. A structured interview conducted both before and after the OI experience allowed us to analyze and point out the teachers' feedback from a pedagogical point of view. The advantages and limits of an OI-based approach to promote the development of more student-centred inquiry-oriented teaching strategies are finally discussed.