Prior research suggests that introductory physics students have difficulty with graphing and interpreting graphs. Here, we discuss an investigation of student difficulties in translating between mathematical and graphical representations for a problem in electrostatics and the effect of increasing levels of scaffolding on students’ representational consistency. Students in calculus-based introductory physics were given a typical problem that can be solved using Gauss’s law involving a spherically symmetric charge distribution in which they were asked to write a mathematical expression for the electric field in various regions and then plot the electric field. In study 1, we found that students had great difficulty in plotting the electric field as a function of the distance from the center of the sphere consistent with the mathematical expressions in various regions, and interviews with students suggested possible reasons which may account for this difficulty. Therefore, in study 2, we designed two scaffolding interventions with levels of support which built on each other (i.e., the second scaffolding level built on the first) in order to help students plot their expressions consistently and compared the performance of students provided with scaffolding with a comparison group which was not given any scaffolding support. Analysis of student performance with different levels of scaffolding reveals that scaffolding from an expert perspective beyond a certain level may sometimes hinder student performance and students may not even discern the relevance of the additional support. We provide possible interpretations for these findings based on in-depth, think-aloud student interviews.

Promoting positive attitudes about science among teachers has important implications for teachers’ classroom practice and for their relationship to science as a discipline. In this paper, we report positive shifts in teachers’ attitudes about science, as measured by the Colorado Learning Attitudes about Science (CLASS) survey, over the course of their participation in a professional development course that emphasized the flexible use of energy representations to understand real world scenarios. Our work contributes to the larger effort to make the case that professional development matters for teacher learning and attitudes.

Problem-solving strategies learned by physics undergraduates should prepare them for real-world contexts as they transition from students to professionals. Yet, graduate students in physics-intensive research face problems that go beyond problem sets they experienced as undergraduates and are solved by different strategies than are typically learned in undergraduate coursework. This paper expands the notion of problem solving by characterizing the breadth of problems and problem-solving processes carried out by graduate students in physics-intensive research. We conducted semi-structured interviews with ten graduate students to determine the routine, difficult, and important problems they engage in and problem-solving strategies they found useful in their research. A qualitative typological analysis resulted in the creation of a three-dimensional framework: context, activity, and feature (that made the problem challenging). Problem contexts extended beyond theory and mathematics to include interactions with lab equipment, data, software, and people. Important and difficult contexts blended social and technical skills. Routine problem activities were typically well defined (e.g., troubleshooting), while difficult and important ones were more open ended and had multiple solution paths (e.g., evaluating options). In addition to broadening our understanding of problems faced by graduate students, our findings explore problem-solving strategies (e.g., breaking down problems, evaluating options, using test cases or approximations) and characteristics of successful problem solvers (e.g., initiative, persistence, and motivation). Our research provides evidence of the influence that problems students are exposed to have on the strategies they use and learn. Using this evidence, we have developed a preliminary framework for exploring problems from the solver’s perspective. This framework will be examined and refined in future work. Understanding problems graduate students face and the strategies they use has implications for improving how we approach problem solving in undergraduate physics and physics education research.

A body of research on physics problem solving has focused on single-concept problems. In this study we use “synthesis problems” that involve multiple concepts typically taught in different chapters. We use two types of synthesis problems, sequential and simultaneous synthesis tasks. Sequential problems require a consecutive application of fundamental principles, and simultaneous problems require a concurrent application of pertinent concepts. We explore students’ conceptual performance when they solve quantitative synthesis problems with varying mathematical complexity. Conceptual performance refers to the identification, follow-up, and correct application of the pertinent concepts. Mathematical complexity is determined by the type and the number of equations to be manipulated concurrently due to the number of unknowns in each equation. Data were collected from written tasks and individual interviews administered to physics major students ($N=179$) enrolled in a second year mechanics course. The results indicate that mathematical complexity does not impact students’ conceptual performance on the sequential tasks. In contrast, for the simultaneous problems, mathematical complexity negatively influences the students’ conceptual performance. This difference may be explained by the students’ familiarity with and confidence in particular concepts coupled with cognitive load associated with manipulating complex quantitative equations. Another explanation pertains to the type of synthesis problems, either sequential or simultaneous task. The students split the situation presented in the sequential synthesis tasks into segments but treated the situation in the simultaneous synthesis tasks as a single event.

A two-tier instrument for representational competence in the field of kinematics (KiRC) is presented, designed for a standard (1st year) calculus-based introductory mechanics course. It comprises 11 multiple choice (MC) and 7 multiple true-false (MTF) questions involving multiple representational formats, such as graphs, pictures, and formal (mathematical) expressions (1st tier). Furthermore, students express their answer confidence for selected items, providing additional information (2nd tier). Measurement characteristics of KiRC were assessed in a validation sample (pre- and post-test, $N=83$ and $N=46$, respectively), including usefulness for measuring learning gain. Validity is checked by interviews and by benchmarking KiRC against related measures. Values for item difficulty, discrimination, and consistency are in the desired ranges; in particular, a good reliability was obtained ($\mathrm{KR}20=0.86$). Confidence intervals were computed and a replication study yielded values within the latter. For practical and research purposes, KiRC as a diagnostic tool goes beyond related extant instruments both for the representational formats (e.g., mathematical expressions) and for the scope of content covered (e.g., choice of coordinate systems). Together with the satisfactory psychometric properties it appears a versatile and reliable tool for assessing students’ representational competency in kinematics (and of its potential change). Confidence judgments add further information to the diagnostic potential of the test, in particular for representational misconceptions. Moreover, we present an analytic result for the question—arising from guessing correction or educational considerations—of how the total effect size (Cohen’s $d$) varies upon combination of two test components with known individual effect sizes, and then discuss the results in the case of KiRC (MC and MTF combination). The introduced method of test combination analysis can be applied to any test comprising two components for the purpose of finding effect size ranges.

In physics education research it has been common to interpret student errors on conceptual questions in topic-specific ways, rather than in terms of general perceptual or reasoning difficulties. This paper examines two alternative accounts for responses to questions related to the concept of center of mass. In one account, difficulties are said to be perceptual in nature; in the other, difficulties are said to be tightly linked to the concepts in question. Hypotheses derived from the former perspective are tested in studies conducted among university students in introductory physics courses. The results do not provide strong support for the perceptual hypothesis; in fact, there is evidence that performance on perception tasks may be influenced by subjects’ ideas about the physical scenario. While the results do not provide general support for one perspective versus the other, the paper serves as an illustration of the type of investigation needed to develop the kind of rich representation of student thinking that will allow instructional resources to be most effectively targeted.

Language ambiguities in concept meanings can exacerbate student learning difficulties and conceptual understanding of physics concepts. This is especially true for the concept of “weight,” which has multiple meanings in both scientific and everyday usage. The term weight has been defined in several different ways, with nuances, but in textbooks and teaching the term is almost always defined in one of two ways: operationally either as the contact force between an object and a measuring scale or as the gravitational force on an object due to some other body such as Earth. The use of the same name for different concepts leads to much confusion, especially in accelerating situations, and to conflicting notions of “weightlessness” in free fall situations. In the present paper, we share an innovative approach that initially avoids the term weight entirely while teaching the physics of each situation, and then teaches the language ambiguities explicitly. We developed an instructional module with this approach and implemented it over two terms in three sections of an introductory physics course for preservice elementary teachers. Learning gains for content understanding were assessed using pretests and post-tests. Participants achieved remarkably high gains for both static and accelerating situations. Surveys pre- and postinstruction showed substantially improved appreciation of language issues and ambiguities associated with weight, weightlessness, and free fall. Interviews with instructors teaching the module provided additional insight into the advantages and teaching demands of the new approach.

Instructional labs are widely seen as a unique, albeit expensive, way to teach scientific content. We measured the effectiveness of introductory lab courses at achieving this educational goal across nine different lab courses at three very different institutions. These institutions and courses encompassed a broad range of student populations and instructional styles. The nine courses studied had two key things in common: the labs aimed to reinforce the content presented in lectures, and the labs were optional. By comparing the performance of students who did and did not take the labs (with careful normalization for selection effects), we found universally and precisely no added value to learning course content from taking the labs as measured by course exam performance. This work should motivate institutions and departments to reexamine the goals and conduct of their lab courses, given their resource-intensive nature. We show why these results make sense when looking at the comparative mental processes of students involved in research and instructional labs, and offer alternative goals and instructional approaches that would make lab courses more educationally valuable.

This study examines the causal reasoning that university students use to explain how dc circuits work. We analyze how students use the concepts of electric field and potential difference in their explanatory models of dc circuits, and what kinds of reasoning they use at the macroscopic and microscopic levels in their explanations. This knowledge is essential to help instructors design and implement new teaching approaches that encourage students to articulate the macroscopic and microscopic levels of description. A questionnaire with an emphasis on explanations was used to analyze students’ reasoning. In this analysis of students’ reasoning in the microscopic and macroscopic modeling processes in a dc circuit, we refer to epistemological studies of scientific explanations. We conclude that the student explanations fall into three main categories of reasoning. The vast majority of students employ an explanatory model based on simple or linear causality and on relational reasoning. Moreover, around a third of students use a relational reasoning that relates two magnitudes current and resistance or conductivity of the material, which is included in a macroscopic explanatory model based on Ohm’s law and the conservation of the current. In addition, few students situate the explanations at the microscopic level (charges or electrons) with unidirectional cause-effect reasoning. This study looks at a number of aspects that have been little mentioned in previous research at the university level, about the reasoning types students use when establishing macro-micro relationships and some possible difficulties with complex reasoning.

As research-based, self-paced electronic learning tools become increasingly available, a critical issue educators encounter is implementing strategies to ensure that all students engage with them as intended. Here, we first discuss the effectiveness of electronic learning tutorials as self-paced learning tools in large enrollment brick and mortar introductory physics courses and then propose a framework for helping students engage effectively with the learning tools. The tutorials were developed via research in physics education and were found to be effective for a diverse group of introductory physics students in one-on-one implementation. Instructors encouraged the use of these tools in a self-paced learning environment by telling students that they would be helpful for solving the assigned homework problems and that the underlying physics principles in the tutorial problems would be similar to those in the in-class quizzes (which we call paired problems). We find that many students in the courses in which these interactive electronic learning tutorials were assigned as a self-study tool performed poorly on the paired problems. In contrast, a majority of student volunteers in one-on-one implementation greatly benefited from the tutorials and performed well on the paired problems. The significantly lower overall performance on paired problems administered as an in-class quiz compared to the performance of student volunteers who used the research-based tutorials in one-on-one implementation suggests that many students enrolled in introductory physics courses did not effectively engage with the tutorials outside of class and may have only used them superficially. The findings suggest that many students in need of out-of-class remediation via self-paced learning tools may have difficulty motivating themselves and may lack the self-regulation and time-management skills to engage effectively with tools specially designed to help them learn at their own pace. We conclude by proposing a theoretical framework to help students with diverse prior preparations engage effectively with self-paced learning tools.

The Force Concept Inventory is one of the most popular and most analyzed multiple-choice concept tests used to investigate students’ understanding of Newtonian mechanics. The correct answers poll a set of underlying Newtonian concepts and the coherence of these underlying concepts has been found in the data. However, this inventory was constructed after several years of research into the common preconceptions held by students and using these preconceptions as distractors in the questions. Their sole purpose is to deflect non-Newtonian candidates away from the correct answer. Alternatively, one can argue that the responses could also be treated as polling these preconceptions. In this paper we shift the emphasis of the analysis away from the correlation structure of the correct answers and look at the latent traits underlying the incorrect responses. Our analysis models the data employing exploratory factor analysis, which uses regularities in the data to suggest the existence of underlying structures in the cognitive processing of the students. This analysis allows us to determine whether the data support the claim that there are alternate non-Newtonian worldviews on which students’ incorrect responses are based. The existence of such worldviews, and their coherence, could explain the resilience of non-Newtonian preconceptions and would have significant implications to the design of instruction methods. We find that there are indeed coherent alternate conceptions of the world which can be categorized using the results of the research that led to the construction of the Force Concept Inventory.

The resources framework provides a useful and generative model of student thinking and learning. In particular, it suggests various strategies for instruction such as priming resources and refining intuition that allow students to build on knowledge they already have. In this paper, we describe the affordances of the resources framework in guiding the design, assessment, and refinement of interventions on pressure in fluids. This perspective kept us alert for cognitive resources on which students could build a deeper understanding and encouraged us to model student thinking as complex and context dependent, even on this narrow topic. This framework also facilitated a focus on evidence of productivity in student work as an alternative assessment to conceptual pre- and post testing.

Research on student epistemologies in introductory courses has highlighted the importance of understanding physics as “a refinement of everyday thinking” [A. Einstein, J. Franklin Inst. 221, 349 (1936)]. That view is difficult to sustain in quantum mechanics, for students as for physicists. How might students manage the transition? In this article, we present a case study of a graduate student’s approaches and reflections on learning over two semesters of quantum mechanics, based on a series of nine interviews. We recount his explicit grappling with the shift in epistemology from classical to quantum, and we argue that his success in learning largely involved his framing mathematics as expressing physical meaning. At the same time, we show he was not entirely stable in these framings, shifting away from them in particular during his study of scattering. The case speaks to literature on students’ epistemologies, with respect to the roles of everyday thinking and mathematics. We discuss what this case suggests for further research, with possible implications for instruction.

Learning quantum mechanics is challenging, even for upper-level undergraduate and graduate students. Research-validated interactive tutorials that build on students’ prior knowledge can be useful tools to enhance student learning. We have been investigating student difficulties with quantum mechanics pertaining to the double-slit experiment in various situations that appear to be counterintuitive and contradict classical notions of particles and waves. For example, if we send single electrons through the slits, they may behave as a “wave” in part of the experiment and as a “particle” in another part of the same experiment. Here we discuss the development and evaluation of a research-validated Quantum Interactive Learning Tutorial (QuILT) which makes use of an interactive simulation to improve student understanding of the double-slit experiment and strives to help students develop a good grasp of foundational issues in quantum mechanics. We discuss common student difficulties identified during the development and evaluation of the QuILT and analyze the data from the pretest and post test administered to the upper-level undergraduate and first-year physics graduate students before and after they worked on the QuILT to assess its effectiveness. These data suggest that on average, the QuILT was effective in helping students develop a more robust understanding of foundational concepts in quantum mechanics that defy classical intuition using the context of the double-slit experiment. Moreover, upper-level undergraduates outperformed physics graduate students on the post test. One possible reason for this difference in performance may be the level of student engagement with the QuILT due to the grade incentive. In the undergraduate course, the post test was graded for correctness while in the graduate course, it was only graded for completeness.

We propose a framework for improving accuracy, fluency, and retention of basic skills essential for solving problems relevant to STEM introductory courses, and implement the framework for the case of basic vector math skills over several semesters in an introductory physics course. Using an iterative development process, the framework begins with a careful identification of target skills and the study of specific student difficulties with these skills. It then employs computer-based instruction, immediate feedback, mastery grading, and well-researched principles from cognitive psychology such as interleaved training sequences and distributed practice. We implemented this with more than 1500 students over 2 semesters. Students completed the mastery practice for an average of about $13\min /\mathrm{week}$, for a total of about 2–3 h for the whole semester. Results reveal large ($>1\mathrm{SD}$) pretest to post-test gains in accuracy in vector skills, even compared to a control group, and these gains were retained at least 2 months after practice. We also find evidence of improved fluency, student satisfaction, and that awarding regular course credit results in higher participation and higher learning gains than awarding extra credit. In all, we find that simple computer-based mastery practice is an effective and efficient way to improve a set of basic and essential skills for introductory physics.

There is considerable long-term interest in understanding the dynamics of collaboration networks, and how these networks form and evolve over time. Most of the work done on the dynamics of social networks focuses on well-established communities. Work examining emerging social networks is rarer, simply because data are difficult to obtain in real time. In this paper, we use thirty years of data from an emerging scientific community to look at that crucial early stage in the development of a social network. We show that when the field was very young, islands of individual researchers labored in relative isolation, and the coauthorship network was disconnected. Thirty years later, rather than a cluster of individuals, we find a true collaborative community, bound together by a robust collaboration network. However, this change did not take place gradually—the network remained a loose assortment of isolated individuals until the mid 2000s, when those smaller parts suddenly knit themselves together into a single whole. In the rest of this paper, we consider the role of three factors in these observed structural changes: growth, changes in social norms, and the introduction of institutions such as field-specific conferences and journals. We have data from the very earliest years of the field, a period which includes the introduction of two different institutions: the first field-specific conference, and the first field-specific journals. We also identify two relevant behavioral shifts: a discrete increase in coauthorship coincident with the first conference, and a shift among established authors away from collaborating with outsiders, towards collaborating with each other. The interaction of these factors gives us insight into the formation of collaboration networks more broadly.

At large research universities, physics graduate teaching assistants (TAs) are often responsible for grading in courses at all levels. However, few studies have focused on TAs’ grading practices in introductory and advanced physics courses. This study was designed to investigate whether physics graduate TAs grade students in introductory physics and quantum mechanics using different criteria and if so, why they may be inclined to do so. To investigate possible discrepancies in TAs’ grading approaches in courses at different levels, we implemented a sequence of instructional activities in a TA professional development course that asked TAs to grade student solutions of introductory physics and upper-level quantum mechanics problems and explain why, if at all, their grading approaches were different or similar in the two contexts. We analyzed the differences in TAs’ grading approaches in the two contexts and discuss the reasons they provided for the differences in their grading approaches in introductory physics and quantum mechanics in individual interviews, class discussions, and written responses. We find that a majority of the TAs graded solutions to quantum mechanics problems differently than solutions to introductory physics problems. In quantum mechanics, the TAs focused more on physics concepts and reasoning and penalized students for not showing evidence of understanding. The findings of the study have implications for TA professional development programs, e.g., the importance of helping TAs think about the difficulty of a problem from an introductory students’ perspective and reflecting on the benefits of formative assessment.

In this study, we explore the strategic self-regulatory and motivational characteristics of students in studio-mode physics courses at three universities with varying student populations and varying levels of success in their studio-mode courses. We survey students using questions compiled from several existing questionnaires designed to measure students’ study strategies, attitudes toward and motivations for learning physics, organization of scientific knowledge, experiences outside the classroom, and demographics. Using a person-centered approach, we utilize cluster analysis methods to group students into learning profiles based on their individual responses to better understand the strategies and motives of algebra-based studio physics students. Previous studies have identified five distinct learning profiles across several student populations using similar methods. We present results from first-semester and second-semester studio-mode introductory physics courses across three universities. We identify these five distinct learning profiles found in previous studies to be present within our population of introductory physics students. In addition, we investigate interactions between these learning profiles and student demographics. We find significant interactions between a student’s learning profile and their experience with high school physics, major, gender, grade expectation, and institution. Ultimately, we aim to use this method of analysis to take the characteristics of students into account in the investigation of successful strategies for using studio methods of physics instruction within and across institutions.