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Register a new userUsing psychometric tools as a window into students quantitative reasoning in introductory physics
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The Physics Inventory of Quantitative Literacy (PIQL), a reasoning inventory under development, aims to assess students physics quantitative literacy at the introductory level. The PIQLs design presents the challenge of isolating types of mathematical reasoning that are independent of each other in physics questions. In its current form, the PIQL spans three principle reasoning subdomains previously identified in mathematics and physics education research: ratios and proportions, covariation, and signed (negative) quantities. An important psychometric objective is to test the orthogonality of these three reasoning subdomains. We present results from exploratory factor analysis, confirmatory factor analysis, and module analysis that inform interpretations of the underlying structure of the PIQL from a student viewpoint, emphasizing ways in which these results agree and disagree with expert categorization. In addition to informing the development of existing and new PIQL assessment items, these results are also providing exciting insights into students quantitative reasoning at the introductory level.
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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.
The lack of diversity and the under-performance of underrepresented students in STEM courses have been the focus of researchers in the last decade. In particular, many hypotheses have been put forth for the reasons for the under-representation and under-performance of women in physics. Here, we present a framework for helping all students learn in science courses that takes into account four factors: 1) characteristics of instruction and learning tools, 2) implementation of instruction and learning tools, 3) student characteristics, and 4) students environments. While there has been much research on factor 1 (characteristics of instruction and learning tools), there has been less focus on factor 2 (students characteristics, and in particular, motivational factors). Here, we focus on the baseline motivational characteristics of introductory physics students obtained from survey data to inform factor 2 of the framework. A longitudinal analysis of students motivational characteristics in two-semester introductory physics courses was performed by administering pre- and post-surveys that evaluated students self-efficacy, grit, fascination with physics, value associated with physics, intelligence mindset, and physics epistemology. Female students reported lower self-efficacy, fascination and value, and had a more fixed view of intelligence in the context of physics compared to male students. Grit was the only factor on which female students reported averages that were equal to or higher than male students throughout introductory physics courses. These gender differences can at least partly be attributed to the societal stereotypes and biases about who belongs in physics and can excel in it. The findings inform the framework and have implications for the development and implementation of effective pedagogies and learning tools to help all students learn.
As part of a larger research project into massively open online courses (MOOCs), we have investigated student background, as well as student participation in a physics MOOC with a laboratory component. Students completed a demographic survey and the Force and Motion Conceptual Evaluation at the beginning of the course. While the course is still actively running, we have tracked student participation over the first five weeks of the eleven-week course.
Covariational reasoning -- reasoning about how changes in one quantity relate to changes in another quantity -- has been examined extensively in mathematics education research. Little research has been done, however, on covariational reasoning in introductory physics contexts. We explore one aspect of covariational reasoning: ``goes like reasoning. ``Goes like reasoning refers to ways physicists relate two quantities through a simplified function. For example, physicists often say that ``the electric field goes like one over r squared. While this reasoning mode is used regularly by physicists and physics instructors, how students make sense of and use it remains unclear. We present evidence from reasoning inventory items which indicate that many students are sense making with tools from prior math instruction, that could be developed into expert ``goes like thinking with direct instruction. Recommendations for further work in characterizing student sense making as a foundation for future development of instruction are made.
In an Introductory Physics for Life Science (IPLS) course that leverages authentic biological examples, student ideas about entropy as disorder or chaos come into contact with their ideas about the spontaneous formation of organized biological structure. It is possible to reconcile the natural tendency to disorder with the organized clustering of macromolecules, but doing so in a way that will be meaningful to students requires that we take seriously the ideas about entropy and spontaneity that students bring to IPLS courses from their prior experiences in biology and chemistry. We draw on case study interviews to argue that an approach that emphasizes the interplay of energy and entropy in determining spontaneity (one that involves a central role for free energy) is one that draws on students resources from biology and chemistry in particularly effective ways. We see the positioning of entropic arguments alongside energetic arguments in the determination of spontaneity as an important step toward making our life science students biology, chemistry, and physics experiences more coherent.
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