Investigating the Perceived Difficulty of Introductory Physics Problems

The Test of Understanding Graphs in Kinematics (TUG-K) is a multiple-choice test developed by Beichner in 1994 to assess students' understanding of kinematics graphs. Many of the items on the TUG-K have strong distractor choices which correspond to students' common difficulties with kinematics graphs. Instruction is unlikely to be effective if instructors do not know the common difficulties of introductory physics students and explicitly take them into account in their instructional design. We evaluate one aspect of the pedagogical content knowledge of first-year physics graduate students enrolled in a teaching assistant training course related to topics covered in the TUG-K. In particular, for each item on the TUG-K, the graduate students were asked to identify which incorrect answer choice they thought would be most commonly selected by introductory physics students if they did not know the correct answer after instruction in relevant concepts. We used the graduate student data and the data from Beichner's original paper for introductory physics students (which was collected from over 500 college and high school students) to assess this aspect of the pedagogical content knowledge of the graduate students, i.e., knowledge of student difficulties related to kinematics graphs as they are revealed by the TUG-K. We find that, although the graduate students, on average, performed better than random guessing at identifying introductory student difficulties on the TUG-K, they did not identify many common difficulties that introductory students have with graphs in kinematics. In addition, we find that the ability of graduate students to identify the difficulties of introductory students is context dependent and that discussions among the graduate students improved their understanding of student difficulties related to kinematics graphs. Moreover, we find that the ability of American graduate students in identifying common student difficulties is comparable with that of foreign graduate students.

In response to substantial evidence that many U.S. students are inadequately prepared in science and mathematics, we have developed an effective and adaptable model that improves the education of all students in introductory physics and increases the numbers of talented physics majors becoming certified to teach physics. We report on the Colorado Learning Assistant model and discuss its effectiveness at a large research university. Since its inception in 2003, we have increased the pool of well-qualified K–12 physics teachers by a factor of approximately three, engaged scientists significantly in the recruiting and preparation of future teachers, and improved the introductory physics sequence so that students’ learning gains are typically double the traditional average.

Research has found circular and rotational motion to be a challenging topic for undergraduate physics students. This article reports on Introductory Physics students’ learning of concepts and quantitative principles in circular and rotational motion. It involves a teaching strategy that uses hands-on practical work, PhET simulations and a focus on feedback in line with the Active Learning Theory developed by Chi and colleagues. Data in this study were collected via in-depth interviews, end-of-lesson tasks and questionnaires. After the intervention, most students were able to show understanding of the relationship between velocity (linear and angular) and radius, predict the motion of a car at a curve given the velocity and show understanding of the relationships between mass distribution and moment of inertia. They considered that hands-on practical work facilitated the derivation of equations and establishing of relationships whereas the accompanying group discussions provided opportunities for justifying developing conceptual understanding. The strengths of the use of PhET simulations were seen as the visualisation of vector directions, the opportunities to confirm predictions and the perceived high reliability of the measurements. The study also showed that feedback was perceived to contribute positively towards the ability to derive equations and relate concepts and even promote self-regulation practices. All in all, this study revealed that a complementary combination of hands-on practical work, free internet-based resources such as PhET simulations and a focus on feedback helps Introductory Physics students learn concepts and quantitative principles in the physics topic of circular and rotational motion.

Identifying the relevant physics principles is a central component of problem solving. A major goal of most introductory physics courses is to help students discern the deep similarities between problems based upon the physics principles so that they can transfer what they learned by solving one problem to solve another problem which involves the same principle. We conducted an investigation in which 251 calculus‐ and algebra‐based introductory physics students were asked explicitly in the recitation quiz to learn from a solved problem and then solve another problem that has different surface features but the same underlying physics principles. We find that many students were able to discern the deep similarities between the problems. When the solved problem was provided, students were likely to invoke the correct principles; however, more scaffolding is needed to help students apply these principles correctly.

Widespread physics education research has shown that most introductory physics students have difficulty learning essential optics concepts - even in the best of traditional courses, and that well-designed active learning approaches can remedy this problem. This mini-workshop and the associated poster session will provide direct experience with methods for promoting students' active involvement in the learning process in lecture and laboratory. Participants will have hands-on experience with activities from <i>RealTime Physics </i>labs and <i>Interactive Lecture Demonstrations</i> - a learning strategy for large (and small) lectures, including specially designed <i>Optics Magic Tricks</i>. The poster will provide more details on these highly effective curricula.

Female students in introductory physics have significantly lower self-efficacy than similarly performing male students; this self-efficacy gap increases after instruction.

Traditional tests are not effective tools for diagnosing the content and structure of students’ knowledge of physics. As a possible alternative, a set of term-association tasks (the ConMap tasks) was developed to probe the interconnections within students’ store of conceptual knowledge. The tasks have students respond spontaneously to a term or problem or topic area with a sequence of associated terms; the response terms and time-of-entry data are captured. The tasks were tried on introductory physics students, and preliminary investigations show that the tasks are capable of eliciting information about the stucture of their knowledge. Specifically, data gathered through the tasks is similar to that produced by a hand-drawn concept map task, has measures that correlate with in-class exam performance, and is sensitive to learning produced by topic coverage in class. Although the results are preliminary and only suggestive, the tasks warrant further study as student-knowledge assessment instruments and sources of experimental data for cognitive modeling efforts.

This conceptual understanding article is part of a series where we explore the recognition and conversion between representations of the electric field concept; in this article, we present the vector field plot’s case. We conducted a study with higher education introductory and upper-division Physics students in a large private Mexican university, intending to learn how students recognize the electric field’s main characteristics in the vector field plot independently and as a source or target representation in conversion processes. We used the theory of registers of semiotic representations and a phenomenographic approach as a framework to analyze data. We explored students’ recognition and conversion abilities through interpretation and construction tasks. We found that the main difficulties of interpreting and constructing the vector field plot are related to the representation’s surface features, often delimited by physical considerations. In the interpretation tasks, this was observed as the interpretation of the physical symmetry, while in construction tasks, it was evident by the confinement of vectors and other associated difficulties. In conversion processes, we observed that there might be an interaction between the source and the target representation, which may result in difficulties in interpreting the vector field plot. We recommend that higher education introductory and upper-division electricity and magnetism instructors and physics education researchers be aware of the difficulties that some interpretation and construction tasks may present to students learning the electric field concept.

The latest advances in science and technology have resulted in great advances in artificial intelligence (AI), including the creation of chatbots. Chatbots simulate human conversation and allow humans to ask questions and receive answers based on a large volume of electronically stored information. Faculties of universities around the world are trying to come to grips with the availability of AI tools, such as chatbots, and are debating the ethical and moral questions surrounding the use of AI in education. This paper presents the results of a study which intended to answer three research questions. RQ1: how familiar are students with AI and tools that utilize it? RQ2: are students aware of the ethical issues involving AI and are they familiar with the university’s policies regarding the use of AI? RQ3: can ChatGPT be used as an efficient tool to teach science majors to code in Python? In this project, a chatbot was used to instruct students on the use of the Python programming language. Introductory college physics students were tasked with using an AI chatbot, ChatGPT (chat generative pre-trained transformer), to learn how to effectively code in the coding program, Python. Before using ChatGPT to code, the students were given a pre-test survey to determine their skill level in Python coding and their familiarity of AI and issues pertaining the use of AI. After completing exercises in Python coding using ChatGPT, a post-test survey was conducted to determine how well the students have learned to code in Python as well as how effective ChatGPT was in assisting their study.

The Physics Resource Center (PRC) is a tutorial center offering supplemental instruction to all introductory level physics students. Physics students were surveyed to investigate and evaluate the center’s effectiveness in meeting their needs. Survey results and suggestions offered by the students are reported. Findings include the dependence of PRC attendance on factors including gender, course performance, and social engagement.

We describe how graduate students categorize introductory mechanics problems based on the similarity of their solutions. Graduate students were asked at the end of a teaching assistant training class to categorize problems from their own perspective and from the perspective of typical introductory physics students whom they were teaching. We compare their categorizations with the categorizations by introductory physics students and physics faculty who categorized the same problems. The utility of categorization as a tool for teaching assistant training and faculty development workshops is discussed.

Drawing appropriate diagrams is a useful problem solving heuristic that can\ntransform a problem into a representation that is easier to exploit for solving\nit. One major focus while helping introductory physics students learn effective\nproblem solving is to help them understand that drawing diagrams can facilitate\nproblem solution. We conducted an investigation in which two different\ninterventions were implemented during recitation quizzes in a large enrollment\nalgebra-based introductory physics course. Students were either (i) asked to\nsolve problems in which the diagrams were drawn for them or (ii) explicitly\ntold to draw a diagram. A comparison group was not given any instruction\nregarding diagrams. We developed rubrics to score the problem solving\nperformance of students in different intervention groups and investigated ten\nproblems. We found that students who were provided diagrams never performed\nbetter and actually performed worse than the other students on three problems,\none involving standing sound waves in a tube (discussed elsewhere) and two\nproblems in electricity which we focus on here. These two problems were the\nonly problems in electricity that involved considerations of initial and final\nconditions, which may partly account for why students provided with diagrams\nperformed significantly worse than students who were not provided with\ndiagrams. In order to explore potential reasons for this finding, we conducted\ninterviews with students and found that some students provided with diagrams\nmay have spent less time on the conceptual analysis and planning stage of the\nproblem solving process. In particular, those provided with the diagram were\nmore likely to jump into the implementation stage of problem solving early\nwithout fully analyzing and understanding the problem, which can increase the\nlikelihood of mistakes in solutions.\n

This study explores student performance on a simple hands-on activity commonly referred to as “batteries and bulbs.” A large population of introductory calculus-based physics students formed the subject group. Special consideration was given to gender differences in success rates.

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) the characteristics of instruction and learning tools, (2) student characteristics, (3) implementation of instruction and learning tools, and (4) the 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 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. We found that female students reported lower levels of self-efficacy, fascination, and value associated with physics, and held a more “fixed” view of intelligence in the context of physics compared to male students. Female students’ fascination and value associated with physics decreased significantly more than males’ after an introductory physics course sequence. In addition, females’ view of physics intelligence became more “fixed” compared to males’ by the end of an introductory physics course sequence. Grit was the only factor on which females reported averages that were equal to or higher than males throughout introductory physics courses. The findings inform the framework and have implications for the development and implementation of effective pedagogies and learning tools to help all students learn.

Introductory physics for life sciences courses frequently include lab activities relevant to life science disciplines are more likely to successfully engage student majoring in life science disciplines than those that do not.