No Arabic abstract
Mathematical reasoning skills are a desired outcome of many introductory physics courses, particularly calculus-based physics courses. Positive and negative quantities are ubiquitous in physics, and the sign carries important and varied meanings. Novices can struggle to understand the many roles signed numbers play in physics contexts, and recent evidence shows that unresolved struggle can carry over to subsequent physics courses. The mathematics education research literature documents the cognitive challenge of conceptualizing negative numbers as mathematical objects--both for experts, historically, and for novices as they learn. We contribute to the small but growing body of research in physics contexts that examines student reasoning about signed quantities and reasoning about the use and interpretation of signs in mathematical models. In this paper we present a framework for categorizing various meanings and interpretations of the negative sign in physics contexts, inspired by established work in algebra contexts from the mathematics education research community. Such a framework can support innovation that can catalyze deeper mathematical conceptualizations of signed quantities in the introductory courses and beyond.
One desired outcome of introductory physics instruction is that students will develop facility with reasoning quantitatively about physical phenomena. Little research has been done regarding how students develop the algebraic concepts and skills involved in reasoning productively about physics quantities, which is different from either understanding of physics concepts or problem-solving abilities. We introduce the Physics Inventory of Quantitative Literacy (PIQL) as a tool for measuring quantitative literacy, a foundation of mathematical reasoning, in the context of introductory physics. We present the development of the PIQL and evidence of its validity for use in calculus-based introductory physics courses. Unlike concept inventories, the PIQL is a reasoning inventory, and can be used to assess reasoning over the span of students instruction in introductory physics. Although mathematical reasoning associated with the PIQL is taught in prior mathematics courses, pre/post test scores reveal that this reasoning isnt readily used by most students in physics, nor does it develop as part of physics instruction--even in courses that use high-quality, research-based curricular materials. As has been the case with many inventories in physics education, we expect use of the PIQL to support the development of instructional strategies and materials--in this case, designed to meet the course objective that all students become quantitatively literate in introductory physics.
Computational Thinking (CT) is still a relatively new term in the lexicon of learning objectives and science standards. There is not yet widespread agreement on the precise definition or implementation of CT, and efforts to assess CT are still maturing, even as more states adopt K-12 computer science standards. In this article we will try to summarize what CT means for a typical introductory (i.e. high school or early college) physics class. This will include a discussion of the ways that instructors may already be incorporating elements of CT in their classes without knowing it. Our intention in writing this article is to provide a helpful, concise and readable introduction to this topic for physics instructors. We also put forward some ideas for what the future of CT in introductory physics may look like.
A goal of Introductory Physics for Life Sciences (IPLS) curricula is to prepare students to effectively use physical models and quantitative reasoning in biological and medical settings. To assess whether this goal is being met, we conducted a longitudinal study of the impact of IPLS on student work in later biology and chemistry courses. We report here on one part of that study, a comparison of written responses by students with different physics backgrounds on a diffusion task administered in a senior biology capstone course. We observed differences in student reasoning that were associated with prior or concurrent enrollment in IPLS. In particular, we found that IPLS students were more likely than non-IPLS students to reason quantitatively and mechanistically about diffusive phenomena, and to successfully coordinate between multiple representations of diffusive processes, even up to two years after taking the IPLS course. Finally, we describe methodological challenges encountered in both this task and other tasks used in our longitudinal study.
Energy is a complex idea that cuts across scientific disciplines. For life science students, an approach to energy that incorporates chemical bonds and chemical reactions is better equipped to meet the needs of life sciences students than a traditional introductory physics approach that focuses primarily on mechanical energy. We present a curricular sequence, or thread, designed to build up students understanding of chemical energy in an introductory physics course for the life sciences. This thread is designed to connect ideas about energy from physics, biology, and chemistry. We describe the kinds of connections among energetic concepts that we intended to develop to build interdisciplinary coherence, and present some examples of curriculum materials and student data that illustrate our approach.
Incorporating computer programming exercises in introductory physics is a delicate task that involves a number of choices that may have a strong affect on student learning. We present an approach that speaks to a number of common concerns that arise when using programming exercises in introductory physics classes where most students are absolute beginner programmers. These students need an approach that is (1) simple, involving 75 or fewer lines of well-commented code, (2) easy to use, with browser-based coding tools, (3) interactive, with a high frame rate to give a video-game like feel, (4) step-by-step with the ability to interact with intermediate stages of the correct program and (5) thoughtfully integrated into the physics curriculum, for example, by illustrating velocity and acceleration vectors throughout. We present a set of hour-long activities for classical mechanics that resemble well-known games such as asteroids, lunar lander and angry birds. Survey results from the first activity from four semesters of introductory physics classes at OSU in which a high percentage of the students are weak or absolute beginner programmers seems to confirm that the level of difficulty is appropriate for this level and that the students enjoy the activity. These exercises are available for general use at http://compadre.org/PICUP In the future we plan to assess conceptual knowledge using an animated version of the Force Concept Inventory originally developed by M. Dancy.