Physics Education
Report of results of physics instruction, curriculum development.
Report of results of physics instruction, curriculum development.
We present a systematic framework of indices designed to characterize Large Language Model (LLM) responses when challenged with rebuttals during a chat. Assessing how LLMs respond to user dissent is crucial for understanding their reliability and behavior patterns, yet the complexity of human-LLM interactions makes systematic evaluation challenging. Our approach employs a fictitious-response rebuttal method that quantifies LLM behavior when presented with multiple-choice questions followed by deliberate challenges to their fictitious previous response. The indices are specifically designed to detect and measure what could be characterized as sycophantic behavior (excessive agreement with user challenges) or stubborn responses (rigid adherence to the fictitious response in the chat history) from LLMs. These metrics allow investigation of the relationships between sycophancy, stubbornness, and the model's actual mastery of the subject matter. We demonstrate the utility of these indices using two physics problems as test scenarios with various OpenAI models. The framework is intentionally generalizable to any multiple-choice format question, including on topics without universally accepted correct answers. Our results reveal measurable differences across OpenAI model generations, with trends indicating that newer models and those employing greater "Reasoning Effort" exhibit reduced sycophantic behavior. The FR pairing method combined with our proposed indices provides a practical, adaptable toolkit for systematically comparing LLM dialogue behaviors across different models and contexts.
2512.20836A Quantum Computing Concept Inventory is needed for the acceleration of uptake of best practice in quantum computing education required to support the quantum computing workforce for the next two decades. Eight experts in quantum computing, quantum ommunication or quantum sensing were interviewed to determine if there is substantial non-mathematical content to warrant such an inventory and determine a preliminary list of key concepts that should be included in such an inventory. Developing such an inventory is a challenging task requiring significant international 'buy-in' and creativity to produce jargon-free valid questions which are accessible to students who are yet to study quantum mechanics.
We conducted a literature review and expert interviews to determine the most common methods being used to teach quantum physics and quantum computing concepts to primary and secondary students. Based on the findings of this review, we provide a framework of seven categories of teaching approaches for teaching mathematically accessible quantum concepts; they are Defamiliarization, Quantum Picturalism, Spin-First Approach, Einstein-First Approach, Many Paths Approach, Historical Development Approach and Game-based Quantum Learning. We summarise each of these teaching methods and overview their advantages and disadvantages of each method. Our framework makes it easy for physics educators to embrace the diverse methods of teaching quantum physics and quantum computing at the primary and secondary level.
2512.16257The accelerating global development of quantum technologies strengthens the case for introducing quantum computing concepts before university. Yet in Latin America, there is no consolidated, region wide integration of quantum computing into secondary education, and the feasibility conditions for doing so remain largely unexamined. This paper proposes a qualitative, comparative framework to assess academic readiness for quantum education across six countries - Peru, Bolivia, Chile, Argentina, Brazil, and Colombia - grounded in the relationship between curriculum compatibility and enabling conditions spanning institutional capacity, teacher preparation, infrastructure, and equity. Using official curricula, policy documents, national statistics, and educational reports, we apply structured qualitative coding and a 1-5 ordinal scoring system to generate a cross country diagnosis. The findings reveal substantial regional asymmetries: among the six countries studied, Chile emerges as the most institutionally prepared for progressive quantum education integration, while the remaining countries exhibit varying combinations of curricular gaps and fragmented but promising enabling conditions. Building on this diagnosis, we propose a country sensitive, regionally coordinated roadmap for staged implementation, beginning with teacher development and pilot centers, leveraging open source platforms and local language resources, and scaling toward gradual curricular integration. This work establishes a baseline for future quantitative and mixed method studies evaluating learning outcomes, motivation, and scalable models for quantum education in Latin America.
Generative AI offers new opportunities for individualized and adaptive learning, particularly through large language model (LLM)-based feedback systems. While LLMs can produce effective feedback for relatively straightforward conceptual tasks, delivering high-quality feedback for tasks that require advanced domain expertise, such as physics problem solving, remains a substantial challenge. This study presents the design of an LLM-based feedback system for physics problem solving grounded in evidence-centered design (ECD) and evaluates its performance within the German Physics Olympiad. Participants assessed the usefulness and accuracy of the generated feedback, which was generally perceived as useful and highly accurate. However, an in-depth analysis revealed that the feedback contained factual errors in 20% of cases; errors that often went unnoticed by the students. We discuss the risks associated with uncritical reliance on LLM-based feedback systems and outline potential directions for generating more adaptive and reliable LLM-based feedback in the future.
This work presents a hands-on molecular communication (MC) testbed developed for the undergraduate Communication Engineering lab course at the Institute for Communications Technology (IfN), TU~Braunschweig. The goal of the experiment is to provide students with an intuitive and reproducible introduction to MC concepts using a low-cost and accessible fluidic setup. The system employs a background water flow into which three dye colors are injected and symbols are detected by a multi-wavelength photosensor. A zero-forcing--based estimator is used to separate the spectral components and reliably identify the transmitted colors. The experiment is designed to be completed independently by students within a single laboratory session and requires only basic prior knowledge from introductory communication engineering courses. A detailed script accompanies the experiment, guiding students through channel characterization, color detection, pseudoinverse computation, and simple data transmission using on-off keying. In pilot trials, students successfully reproduced the entire communication chain and achieved stable data rates of up to 0.5~bit/s over a 15~cm channel. The proposed testbed demonstrates that fundamental principles of MC can be taught effectively using a compact and inexpensive experimental setup. The experiment will be integrated into an undergraduate lab course.
We are at the dawn of the second quantum revolution, where our ability to create and control individual quantum systems is poised to drive transformative advancements in basic science, computation, and everyday life. However, quantum theory has long been conceived as notoriously hard to learn, creating a significant barrier to workforce development, informed decision-making by stakeholders and policymakers, and broader public understanding. This paper is concerned with Quantum Picturalism, a novel visual mathematical language for quantum physics. Originally developed over two decades ago to explore the foundational structure of quantum theory, this rigorous diagrammatic framework has since been adopted in both academia and industry as a powerful tool for quantum computing research and software development. Here, we demonstrate its potential as a transformative educational methodology. We report the findings from a pilot study involving 54 UK high school students, randomly selected from a pool of 734 volunteers across the UK. Despite the absence of advanced mathematical prerequisites, these students demonstrated a strong conceptual grasp of key quantum principles and operations. On an assessment comprising university graduate-level exam questions, participants achieved an 82% pass rate, with 48% obtaining a distinction-level grade. These results pave the way for making quantum more inclusive, lowering traditional cognitive and demographic barriers to quantum learning. This approach has the potential to broaden participation in the field and provide a promising new entry point for stakeholders, future experts, and the general public.
Introductory college Earth and space science courses offer rich opportunities for citizen science projects. One especially compelling context is Earth's geomagnetic field: a self-excited dynamo in the liquid outer core generates a global field that couples Earth's interior to solar forcing, providing a natural laboratory for space weather education. We tested the viability of smartphone magnetometers for quantitative monitoring during the 4 November 2025 X1.8 solar flare, linking planetary magnetism, space weather, and authentic undergraduate research. Co-located observations were obtained with a Geometrics G-857 proton-precession magnetometer and tri-axial smartphone sensors logging via Physics Toolbox in a course-based undergraduate research experience (CURE) emphasizing the Nature of Science (NOS). Fourteen one-minute paired averages spanning 17:27-17:40 UT revealed a systematic smartphone bias of about 630 nT (95% confidence interval 550-710 nT) relative to the G-857 and a weak negative correlation (r ~ -0.4). Smartphone magnetometers thus lack the precision and calibration stability needed for nanotesla-scale flare signatures but remain valuable as pedagogical and engagement tools. We frame smartphones within a tiered instrumentation ladder linking research-grade observatories, intermediate-cost community magnetometers (for example, HamSCI Personal Space Weather Stations), and smartphones as high-engagement entry points to geomagnetic and space weather studies. This hierarchy aligns citizen science with open data protocols and NOS pedagogy, transforming low-cost sensing into epistemically grounded inquiry suitable for introductory college laboratories.
Quantum physics education at the upper-secondary level traditionally follows a historical approach, rarely extending beyond early 20th-century ideas, leaving students unprepared for comprehending modern quantum technologies central to everyday life and many facets of modern industry. To address this gap, we investigated how upper-secondary students and pre-service teachers understand quantum teleportation when taught with a simplified diagrammatic formalism based on the ZX-calculus, which represents quantum processes as diagrams of wires and boxes. Through phenomenographic analysis of video-recorded group work sessions, written responses to exercises, and a group interview, with a total of n=21 participants, we identified an outcome space consisting of four qualitatively different, hierarchically ordered categories of description encapsulating the different ways of experiencing quantum teleportation. The categories revealed that a conceptual progression depends on how one understands the temporality in quantum processes, the role of entanglement in quantum teleportation, the active nature of quantum measurements, and interpretations of mathematical operations in the diagrams. Our findings demonstrate that while a simplified diagrammatic formalism for teaching quantum physics provides an accessible entry point at the upper-secondary level, it does not automatically resolve fundamental conceptual challenges, and requires careful consideration in terms of developing teaching and learning sequences. Finally, these results provide educators with a deeper understanding of conceptual affordances and challenges for designing and improving instruction, whilst also highlighting the need for further exploring how students and teachers alike understand quantum phenomena.
We present Particle Builder, an online board game which teaches students about concepts from the Standard Model of Particle Physics at a high school level. This short activity resulted in a gain of 0.16, indicating that students learned a significant amount of particle physics knowledge. Students found the activity was more engaging and less difficult than a normal classroom lesson.
In this paper we show how students can measure optical features of smartphone displays through three experiments. Observing diffraction patterns from smartphone displays allows students to determine the Pixels Per Inch (PPI). Observing reflections within a smartphone display provides information about touch glass thickness and pixel layer properties. Finally, water drops are used as miniature lenses to see the magnified image of the pixels beneath. An enhanced theoretical model that covers both small and large droplets is provided.
2511.17218We present a practical course targeting graduate students with prior knowledge of the basics of quantum computing. The practical aims to deepen students' understanding of fundamental concepts in quantum computing by implementing quantum circuit simulators. Through hands-on experience, students learn about different methods to simulate quantum computing, including state vectors, density matrices, the stabilizer formalism, and matrix product states. By implementing the simulation methods themselves, students develop a more in-depth understanding of fundamental concepts in quantum computing, including superposition, entanglement, and the effects of noise on quantum systems. This hands-on experience prepares students to do research in the field of quantum computing and equips them with the knowledge and skills necessary to tackle complex research projects in the field. In this work, we describe our teaching approach and the structure of our practical, and we discuss evaluations and lessons learned.
Blind and Visually Impaired (BVI) Individuals face significant challenges in science due to the discipline's reliance on visual elements such as graphs, diagrams, and laboratory work. Traditional learning materials, such as Braille and large-print textbooks, are often scarce or delayed, while practical experiments are rarely adapted for accessibility. Additionally, mainstream educators lack the training to effectively support BVI students, and Teachers for the Visually Impaired (TVIs) often lack scientific expertise. As a result, BVI individuals remain underrepresented in scientific jobs, reinforcing a cycle of exclusion. However, technological advancements and inclusive initiatives are opening new opportunities. Outreach programs aim to make science engaging and accessible for BVI individuals through multi-sensory learning experiences. Hands-on involvement in these activities fosters confidence and interest in scientific careers. Beyond sparking interest, equipping BVI students with the right tools and skills is crucial for their academic success. Early exposure to assistive technologies enables BVI students to navigate scientific studies independently. Artificial Intelligence (AI) tools further enhance accessibility by converting visual data into descriptive text and providing interactive assistance. Several learning sessions demonstrated the effectiveness of these interventions, with participants successfully integrating into university-level science programs. Educating BVI and their teachers on these tools and good pratices is the aim of our project AccesSciencesDV. Research careers offer promising opportunities for BVI, especially in computational fields. By leveraging coding, data analysis, and AI-driven tools, BVI researchers can conduct high-level scientific work without relying on direct visual observations. The presence of BVI scientists enriches research environments.
2511.14318This report summarizes the outcomes of a two-day international scoping workshop on the role of artificial intelligence (AI) in science education research. As AI rapidly reshapes scientific practice, classroom learning, and research methods, the field faces both new opportunities and significant challenges. The report clarifies key AI concepts to reduce ambiguity and reviews evidence of how AI influences scientific work, teaching practices, and disciplinary learning. It identifies how AI intersects with major areas of science education research, including curriculum development, assessment, epistemic cognition, inclusion, and teacher professional development, highlighting cases where AI can support human reasoning and cases where it may introduce risks to equity or validity. The report also examines how AI is transforming methodological approaches across quantitative, qualitative, ethnographic, and design-based traditions, giving rise to hybrid forms of analysis that combine human and computational strengths. To guide responsible integration, a systems-thinking heuristic is introduced that helps researchers consider stakeholder needs, potential risks, and ethical constraints. The report concludes with actionable recommendations for training, infrastructure, and standards, along with guidance for funders, policymakers, professional organizations, and academic departments. The goal is to support principled and methodologically sound use of AI in science education research.
Generative AI is rapidly reshaping how physicists teach, learn, and conduct research, yet little is known about how physics faculty are responding to these changes. We interviewed 12 physics professors at a major Scandinavian research university to explore their uses and perceptions of Generative AI (GenAI) in both teaching and research. Using the theoretical framework of epistemic framing, we conducted a thematic analysis that identified 19 overlapping practices, ranging from coding and literature review to assessment and feedback. From these practices, we derived six overlapping epistemic frames through which professors make sense of GenAI: as a threat to genuine learning and assessment, a source of knowledge, a discussion partner, a text-processing tool, a coding tool, and a labor-saving device. While the latter five position GenAI as a useful tool in the physicists' toolbox, the threat frame represented an overarching concern that colored all other frames. These findings reveal how GenAI is beginning to transform what it means to be a physicist, highlighting both opportunities for innovation and challenges for academic integrity and learning.
Creating software dedicated to simulation is essential for teaching and research in Science, Technology, Engineering, and Mathematics (STEM). Physics lecturing can be more effective when digital twins are used to accompany theory classes. Research in physics has greatly benefited from the advent of modern, high-level programming languages, which facilitate the implementation of user-friendly code. Here, we report our own Python-based software, the gr-orbit-toolkit, to simulate orbits in classical and general relativistic scenarios. First, we present the ordinary differential equations (ODEs) for classical and relativistic orbital accelerations. For the latter, we follow a post-Newtonian approach. Second, we describe our algorithm, which numerically integrates these ODEs to simulate the orbits of small-sized objects orbiting around massive bodies by using Euler and Runge-Kutta methods. Then, we study a set of sample two-body models with either the Sun or a black hole in the center. Our simulations confirm that the orbital motions predicted by classical and relativistic ODEs drastically differ for bodies near the Schwarzschild radius of the central massive body. Classical mechanics explains the orbital motion of objects far away from a central massive body, but general relativity is required to study objects moving at close proximity to a massive body, where the gravitational field is strong. Our study on objects with different eccentricities confirms that our code captures relativistic orbital precession. Our convergence analysis shows the toolkit is numerically robust. Our gr-orbit-toolkit aims at facilitating teaching and research in general relativity, so a comprehensive user and developer guide is provided in the public code repository.
Quaternions provide a unified algebraic and geometric framework for representing three-dimensional rotations without the singularities that afflict Euler-angle parametrisations. This article develops a pedagogical and conceptual analysis of the \emph{Gimbal lock} phenomenon and demonstrates, step by step, how quaternion algebra resolves it. Beginning with the limitations of Euler representations, the work introduces the quaternionic rotation operator $v' = q\,v\,q^{*}$, derives the Rodrigues formula, and establishes the continuous, singularity-free mapping between unit quaternions and the rotation group $SO(3)$. The approach combines historical motivation, formal derivation, and illustrative examples designed for advanced undergraduate and graduate students. As an extension, Appendix~A presents the geometric and topological interpretations of quaternions, including their relation to the groups $\mathbb{Q}_8$ and $SU(2)$, and the Dirac belt trick, offering a visual analogy that reinforces the connection between algebra and spatial rotation. Overall, this work highlights the educational value of quaternions as a coherent and elegant framework for understanding rotational dynamics in physics.
Comparing abstract concepts (such as electric circuits) with familiar ideas (plumbing systems) through analogies is central to practice and communication of physics. Contemporary research highlights self-generated analogies to better facilitate students' learning than the taught ones. "Spontaneous" and "self-generated" analogies represent the two ways through which students construct personalized analogies. However, facilitating them, particularly in large enrollment courses remains a challenge, and recent developments in generative artificial intelligence (AI) promise potential to address this issue. In this qualitative study, we analyze around 800 student responses in exploring the extent to which students spontaneously leverage analogies while explaining Morse potential curve in a language suitable for second graders and self-generate analogies in their preferred everyday contexts. We also compare the student-generated spontaneous analogies with AI-generated ones prompted by students. Lastly, we explore the themes associated with students' perceived ease and difficulty in generating analogies across both cases. Results highlight that unlike AI responses, student-generated spontaneous explanations seldom employ analogies. However, when explicitly asked to explain the behavior of the curve in terms of their everyday contexts, students employ diverse analogical contexts. A combination of disciplinary knowledge, agency to generate customized explanations, and personal attributes tend to influence students' perceived ease in generating explanations across the two cases. Implications of these results on the potential of AI to facilitate students' personalized analogical reasoning, and the role of analogies in making students notice gaps in their understanding are discussed.
Quantum computing offers a powerful new perspective on probabilistic and collective behaviors traditionally taught in statistical physics. This paper presents two classroom-ready modules that integrate quantum computing into the undergraduate curriculum using Qiskit: the quantum random walk and the Ising model. Both modules allow students to simulate and contrast classical and quantum systems, deepening their understanding of concepts such as superposition, interference, and statistical distributions. We outline the quantum circuits involved, provide sample code and student activities, and discuss how each example can be used to enhance student engagement with statistical physics. These modules are suitable for integration into courses in statistical mechanics, modern physics, or as part of an introductory unit on quantum computing.
2510.27674Physics teaching in engineering programmes poses discipline-specific demands that intertwine conceptual modelling, experimental inquiry, and computational analysis. This study examines nine teaching competences for physics instruction derived from international and regional frameworks and interpreted within engineering contexts. Nineteen university instructors from the Technological Institute of Toluca completed an open-ended questionnaire; responses were analysed using a grounded theory approach (open and axial coding) complemented by descriptive frequencies. Results indicate stronger development in technical mastery, methodological/digital integration, technology-mediated communication, and innovation (C1, C2, C6, C9), while information literacy for digital content creation/adaptation and digital ethics/safety (C7, C8) remain underdeveloped. A recurrent understanding-application gap was identified, revealing uneven transfer from conceptual awareness to enacted classroom practice. We conclude that advancing physics education for engineers requires institutionally supported, discipline-specific professional development that aligns modelling, laboratory work, and computation with ethical and reproducible digital practices; such alignment can move instructors from adoption/adaptation toward sustained appropriation and innovation in multimodal settings.