Examining Thematic Variation in a Phenomenographical Study on Computational Physics

Abstract

Projects and Practices in Physics (P 3 ) is a transformed, first-year introductory mechanics course offered at Michigan State University. The focus of the course is concept-based group learning implemented through solving analytic problems and computational modeling problems using the VPython programming environment. Interviews with students from P 3 were conducted to explore the variation of students' perceptions of the utility of solving computational physics problems in the classroom setting. A phenomenographic method is being used to develop categories of student experience with computational physics problems based on themes emerging across the different students' interviews. This paper will focus on exploring the variation within the theme of Computation Helps to Learn Physics that arose from our preliminary analysis of the data from a larger phenomenographic study. When examined on an individual basis, this theme provides important insights into students' perception of the use of computation, such as the way that students can engage with computation as a learning tool in a Physics classroom.

The benefit of computational modelling in physics teaching: a historical overview

“…They found that their students drastically improved in carrying out these projects during the semester and rated the course highly [68]. Similarly, in an interview study carried out by Hawkins et al most of the participating students held the opinion that their use of 'VPython' to model three different problems helped them to learn physics [69]. Furthermore, they structured students' statements regarding the theme 'Computation helps to Learn Physics' into categories.…”

Student Representations of Computation in the Physics Community

“…We conducted this study after the students completed their fall 2020 coursework involving computation because we wanted to examine the persistence of their experience with computation. This study therefore complements Hawkins et al [90], who interviewed students about their perceptions of using computation shortly after completing the first three weeks of a computationally integrated physics course. With this context established, we expanded our overarching question ("How is computation represented in students' mental models of the physics community of practice after they complete a course involving computation?")…”

“…However, this rich pedagogical approach still requires investigation and improvement. Student resistance has been identified as a common and significant obstacle in integrating computation [51], and not all students come to see computation as a helpful learning experience [90]. Because computation is a novel activity for many students, and many students find programming intimidating [50], student motivation [58] plays a key role in integrating computation into the physics curriculum.…”

Mathematische Modellbildung und Videoanalyse zum Lernen der Newtonschen Dynamik im Vergleich

“…Die Nutzung von "Mathematica" und "Python" in einer anderen Studie wurden von Studierenden ebenfalls gelobt und führte zu einer drastischen Verbesserung der damit durchgeführten Projekte (Araujo et al, 2008). Die Nutzung von "VPython" half Studierenden außerdem nach eigener Einschätzung dabei, drei verschiedene Probleme zu modellieren und die Physik dahinter besser zu verstehen (Hawkins et al, 2017). Benacka (2015b) untersuchte in verschiedenen Studien die motivierenden Eigenschaften der mathematischen Modellbildung mit Tabellenkalkulationsprogrammen in Oberstufenschulen (Benacka, 2015a(Benacka, , 2015b und kam zu dem Ergebnis, dass 97 % der Schüler*innen die Einheit, in der ein neuartiges Problem mit dem Euler-Verfahren modelliert wurde, sehr interessant fanden (Benacka, 2016).…”