Stealing from physics: modeling with mathematical functions in data-rich contexts

Erickson, Tim

doi:10.1093/teamat/hri025

Cited by 19 publications

(12 citation statements)

References 4 publications

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“…Translating physics into mathematics is not an easy task for students, as some previous studies on modeling in physics and student understanding of physics equation have already shown (e.g., Refs. [34,35]).…”

Section: The Preferred Strategy On Physics Questions Seems To Be the mentioning

confidence: 99%

Student reasoning about graphs in different contexts

Ivanjek

Sušac

Planinić

et al. 2016

Phys. Rev. Phys. Educ. Res.

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This study investigates university students' graph interpretation strategies and difficulties in mathematics, physics (kinematics), and contexts other than physics. Eight sets of parallel (isomorphic) mathematics, physics, and other context questions about graphs, which were developed by us, were administered to 385 first-year students at the Faculty of Science, University of Zagreb. Students were asked to provide explanations and/or mathematical procedures with their answers. Students' main strategies and difficulties identified through the analysis of those explanations and procedures are described. Student strategies of graph interpretation were found to be largely context dependent and domain specific. A small fraction of students have used the same strategy in all three domains (mathematics, physics, and other contexts) on most sets of parallel questions. Some students have shown indications of transfer of knowledge in the sense that they used techniques and strategies developed in physics for solving (or attempting to solve) other context problems. In physics, the preferred strategy was the use of formulas, which sometimes seemed to block the use of other, more productive strategies which students displayed in other domains. Students' answers indicated the presence of slope-height confusion and interval-point confusion in all three domains. Students generally better interpreted graph slope than the area under a graph, although the concept of slope still seemed to be quite vague for many. The interpretation of the concept of area under a graph needs more attention in both physics and mathematics teaching.

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Section: The Preferred Strategy On Physics Questions Seems To Be the mentioning

confidence: 99%

Student reasoning about graphs in different contexts

Ivanjek

Sušac

Planinić

et al. 2016

Phys. Rev. Phys. Educ. Res.

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show abstract

“…This figure displays a model of physics competence required in physics-related tasks in secondary school and clarifies the relationship between the cognitive domain of physics and the cognitive domain of of mathematics. The cognitive domain, in this sense, directly refers to the context in which tasks are solved and hence a type of cognitive mode (Erickson, 2006;Bing & Redish, 2009). For example, if a student is working on a task in physics, (s)he is enacting schematic language and conceptual knowledge in order to successfully complete this task that is embedded in a physics context (e.g., experiments, classroom, books, etc.).…”

Section: A Model Of Physics Competencementioning

confidence: 99%

“…For example, the competency Handling Symbols is accessed in order to successfully manipulate and solve an equation. When performing mathematical operations, the student thinks and acts in the mode of mathematics (Erickson, 2006). Subsequently, re-entering the mode of physics is necessary in order to interpret the answer and then to communicate and evaluate the answer in a physics context.…”

Section: A Model Of Physics Competencementioning

confidence: 99%

Mathematical competencies and the role of mathematics in physics education: A trend analysis of TIMSS Advanced 1995 and 2008

Nilsen¹,

Angell²,

Grønmo³

2013

ADNO

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As students advance in their learning of physics over the course of their education, the requirement of mathematical applications in physics-related tasks increases, especially so in upper secondary school and in higher education. Yet there is little empirical work (particularly large-scale or longitudinal) on the application of mathematics in physics education compared with the research related to the conceptual knowledge of physics. In order to clarify the nature of mathematics in physics education, we developed a theoretical framework for mathematical competencies pertinent to various physics tasks based on theoretical frameworks from mathematics and physics education. We used this synthesis of frameworks as a basis to create a model for physics competence. The framework also served as a tool for analyzing and categorizing trend items from the international large-scale survey, TIMSS Advanced 1995 and 2008. TIMSS Advanced assessed students in upper secondary school with special preparation in advanced physics and mathematics. We then investigated the changes in achievements on these categorized items across time for nations who participated in both surveys. The results from our analysis indicate that students whose overall physics achievement declined struggled the most with items requiring mathematics, especially items requiring them to handle symbols, such as manipulating equations. This finding suggests the importance of collaboration between mathematics and physics education as well as the importance of traditional algebra for physics education.

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“…Depending on the exercise at hand, the students' work tended towards either conceptual knowledge of physics and everyday experience ("physics mode"), mathematical relations and arithmetic calculations ("math mode") or programming techniques and the programming language's syntax ("programming mode"). The physics mode and the math mode have been documented by others (see for example Angell, et al, 2008;Erickson, 2006;Taber, 2006). The "programming mode", however, comes in addition as a result of the new computational perspectives introduced in the mechanics course.…”

Section: Working In Modesmentioning

confidence: 96%

Undergraduate students’ challenges with computational modelling in physics

Sørby

Angell

2012

NorDiNa

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In later years, computational perspectives have become essential parts in several of the University of Oslo’s natural science studies. In this paper we discuss some main findings from a qualitative study of the computational perspectives’ impact on the students’ work with their first course in physics– mechanics – and their learning and meaning making of its contents. Discussions of the students’ learning of physics are based on sociocultural theory, which originates in Vygotsky and Bakhtin, and subsequent physics education research. Results imply that the greatest challenge for students when working with computational assignments is to combine knowledge from previously known, but separate contexts. Integrating knowledge of informatics, numerical and analytical mathematics and conceptual understanding of physics appears as a clear challenge for the students. We also observe alack of awareness concerning the limitations of physical modelling. The students need help with identifying the appropriate knowledge system or “tool set”, for the different tasks at hand; they need helpto create a plan for their modelling and to become aware of its limits. In light of this, we propose thatan instructive and dialogic text as basis for the exercises, in which the emphasis is on specification, clarification and elaboration, would be of potential great aid for students who are new to computational modelling.

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Stealing from physics: modeling with mathematical functions in data-rich contexts

Cited by 19 publications

References 4 publications

Student reasoning about graphs in different contexts

Student reasoning about graphs in different contexts

Mathematical competencies and the role of mathematics in physics education: A trend analysis of TIMSS Advanced 1995 and 2008

Undergraduate students’ challenges with computational modelling in physics

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