Kaitlin Gili, Mainak Nistala, Kristen Wendell, Michael C. Hughes
STEM education researchers are often interested in identifying moments of students' mechanistic reasoning for deeper analysis, but have limited capacity to search through many team conversation transcripts to find segments with a high concentration of such reasoning. We offer a solution in the form of an interpretable machine learning model that outputs time-varying probabilities that individual students are engaging in acts of mechanistic reasoning, leveraging evidence from their own utterances as well as contributions from the rest of the group. Using the toolkit of intentionally-designed probabilistic models, we introduce a specific inductive bias that steers the probabilistic dynamics toward desired, domain-aligned behavior. Experiments compare trained models with and without the inductive bias components, investigating whether their presence improves the desired model behavior on transcripts involving never-before-seen students and a novel discussion context. Our results show that the inductive bias improves generalization -- supporting the claim that interpretability is built into the model for this task rather than imposed post hoc. We conclude with practical recommendations for STEM education researchers seeking to adopt the tool and for ML researchers aiming to extend the model's design. Overall, we hope this work encourages the development of mechanistically interpretable models that are understandable and controllable for both end users and model designers in STEM education research.
Sergey V. Samsonau, Matthew Pearce
Guiding others through authentic scientific research outside of PhD programs has been practiced for decades in specialized secondary schools, undergraduate research programs, and independent settings. These practitioners work in the middle, between the classroom science teacher and the PhD advisor, guiding learners with aptitude or serious interest. Sport and music have dedicated professions for this middle position (the school-team coach and the school band director); research does not. This paper names that missing profession the Research Guide: the practitioner who develops another person's capacity to do research, from framing a question to communicating findings. Hundreds of thousands of middle and high school students already pursue authentic research each year, even more college undergraduates participate in research with a faculty member, and millions of adults engage in citizen science. In current practice, the programs that serve this middle group mostly default to a simplified version of the PhD apprenticeship model structured around one mentor with a few students at a time, without systematic training; they overwhelmingly frame research as the hypothetico-deductive cycle alone. The role calls for cognitive apprenticeship, a pedagogical approach in which an expert's tacit moves on open-ended problems are made visible and scaffolded, then faded as the learner develops, while the research outcomes themselves remain unpredictable. It spans multiple modes of inquiry (not only the hypothetico-deductive cycle) and demands a combination that no existing training program produces: pedagogy, research methodology, developmental assessment, risk and productive struggle management, domain flexibility, and community building. Together these demands warrant a dedicated profession: a named role, a training pathway, a career ladder, hiring standards, and institutional recognition.
Ingrid Torres, Alex Krasnok
Flat optics is now judged by more than a strong simulation or a single laboratory demonstration. To reach release, a device must survive a chain of handoffs: requirements, model selection, verification, layout release, fabrication, calibrated validation, packaging, and qualification. Diffractive optics brings mature routes for beam shaping and compact wavefront control, while meta-optics expands the design space through wavelength-scale control of phase, amplitude, and polarization. In both families, projects often slow down not because the optical function is impossible, but because the evidence required at each handoff is incomplete, poorly documented, or mismatched to the next decision. This tutorial organizes that problem into a stage-gate workflow, a set of compact technical checks, worked device examples, an artifact-based skills map, and an educational translation into workforce models, course deliverables, and assessment logic. The emphasis is practical: reduce avoidable redesign loops, make performance claims auditable, and clarify what students, instructors, and employers should be able to produce, review, and approve. The broader aim is to make the path from flat-optics concept to qualified hardware easier to understand, easier to teach, and easier to repeat.
Jonan-Rohi S. Plueger, Bethany R. Wilcox, Steven J. Pollock, Gina Passante
The Controlled-Not (CNOT) gate is essential to algorithms in quantum computing for its ability to entangle qubits. As such, it is important to understand how students learning quantum computing reason around the function and use of this critical quantum gate. To investigate this, we conducted think-aloud interviews in which students solved problems involving the CNOT gate to understand students' `CNOT toolbox' -- the strategies and cognitive resources students use when reasoning about the effect of the CNOT gate. We identify three cognitive resources related to the CNOT gate: (1) the procedural resource of applying CNOT to specific states, (2) a qualitative description of CNOT's effect on the target qubit given the control qubit, and (3) the idea that the control qubit is not changed when CNOT is applied to computational basis states. We find that students' use of the first resource is foundational to their understanding of the second and third, that the second and third resources can sometimes lead students to incorrect conclusions, and that students can use each of these resources separately or in tandem. We also explore how students use these resources in conjunction with Dirac notation, superposition states, and entanglement to reason both productively and unproductively about quantum computing problems.
Joanna Masel, Anna Dornhaus
Theory and empirical science should be in constant dialogue, but often find it hard to understand one another. Here we describe a graduate-level university course we developed to improve matters. The course was designed to help empirically-focused biology graduate students read and understand theory papers, despite little prior mathematical training. It uses several evidence-based principles of modern teaching: backwards design, active learning, and just-in-time teaching. We believe that this or similar curricular content, emphasizing the nature of evidence and the role of theory in science, will improve critical thinking and scientific progress.
Yang Liu, Qianjie Lei, Xiaolong He, Yizhe Xue, Kexin He, Haitao Yang, Yong Wang, Xian Zhang, Li Yang, Yichun Zhou, Ruiqi Hu, Yong Xie
Machine learning (ML) is transforming modern physics research, but practical, hands-on experience with ML techniques remains limited due to cost and complexity barriers. To address this gap, we introduce an affordable, autonomous, Internet-of-Things (IoT)-enabled experimental platform designed specifically for applied physics education. Utilizing an Arduino microcontroller, a customizable multi-wavelength light emitting diode (LED) array, and photosensors, our setup generates diverse, real-time optical datasets ideal for training and evaluating foundational ML algorithms, including traversal methods, Bayesian inference, and deep learning. The platform facilitates a closed-loop, self-driving experimental workflow, encompassing automated data collection, preprocessing, model training, and validation. Through systematic performance comparisons, we demonstrate the superior ability of deep learning to capture complex nonlinear relationships compared to traversal and Bayesian methods. At approximately $60, this open-source IoT platform provides an accessible, practical pathway for students to master advanced ML concepts, promoting deeper conceptual insights and essential technical skills required for the next generation of physicists and engineers.
Marcus Kubsch, Natasha G. Holmes, Antti Lehtinen
The Physics Lab Inventory of Critical Thinking (PLIC) measures three components of students' critical thinking in physics labs: evaluating data, evaluating methods, and proposing next steps. Prior work has analyzed these components in isolation or as a composite score. In this study, we apply latent profile analysis (LPA) to the three PLIC scales using a large, multi-institutional dataset of 5,513 matched pre/post student records to identify characteristic response patterns across the three components simultaneously. At both pre- and post-instruction, a two-profile solution best fit the data. Profile composition shifted substantially over instruction, with 48.4\% of students in the lower-performing profile at pre-test transitioning to the higher-performing profile at post-test, while 43.6\% of students moved in the opposite direction. Course type was statistically associated with profile membership at both timepoints, though the effect was small (Cramér's $V \approx 0.10$). To examine the relationship between profile transitions and students' affective development, we estimated cross-lagged panel models (CLPMs) linking profile membership to belonging, recognition, self-efficacy, and agency. Belonging emerged as the principal upstream predictor, prospectively predicting recognition, self-efficacy, agency, and higher-knowledge profile membership. Agency and self-efficacy formed a reciprocal but asymmetric loop, with the path from agency to later self-efficacy being stronger. Recognition functioned primarily as a downstream construct over this timescale. These results provide the first person-centered, multidimensional characterization of PLIC performance and demonstrate that epistemic and identity-related constructs are interlinked in physics lab learning.
Shams El-Adawy, A. R. Piña, Benjamin M. Zwickl, H. J. Lewandowski
The growth of the Quantum Information Science and Engineering (QISE) industry has increased interest in how undergraduate programs prepare students for careers in this field. Prior research emphasizes the value of experiential learning as preparation for the quantum industry, but lacks specificity regarding the experimental skills needed for positions available to bachelor's degree graduates. In this study, we investigate the experimental skills associated with bachelor's-level quantum industry positions through 44 semi-structured interviews with quantum industry professionals. Guided by the American Association of Physics Teachers recommendations for the undergraduate physics laboratory curriculum, we characterize the experimental skills associated with positions described as requiring bachelor's-level preparation and thematically synthesize them into four categories: instrumentation, computation and data analysis, experimental and project design, and communication and collaboration. We further examine how these skills cluster across role types and articulate them as learning goals to provide guidance for educators interested in aligning undergraduate instruction with the needs of students wanting to pursue a career in the quantum industry. Our findings suggest the need to emphasize the discussion of hardware in QISE theory courses, expand experimental training through instructional laboratories, and intentionally integrate professional skills in undergraduate QISE education.
Dr James W. Trayford
Apr 10, 2026·astro-ph.IM·PDF The 2025 UK National Astronomy Meeting (NAM) in Durham played host to a session titled "Unseen Astronomy", involving a variety of astronomy researchers in diverse fields. This unique meeting focussed on a number of novel projects exploring alternatives to purely visual means of display in Astronomy, encompassing spheres of education, communication and research, and straddling both accessible and general use applications. The successful inclusion of such a session at a major conference reflects the explosion of interest in multimodal astronomy in recent years, and hints at its transformative potential. Here, I aim to outline and motivate the topic of multi-modal science and consider its exciting potential. I will discuss this in the context of our own work in the area, the community building being undertaken to bring together researchers considering multi-modality, and efforts to impact astronomy at large.
Jaya Shivangani Kashyap, Robert P. Devaty, Chandralekha Singh
The method of images (MoI) is a valuable technique for solving certain electrostatic boundary value problems consisting of charge density near conductor(s). We developed and validated an inquiry-based tutorial on MoI to help students learn to identify the problems related to the concept. We implemented the inquiry-based tutorial accompanied by pretest and posttest, across three instructors' classes to evaluate student learning. We also conducted think-aloud interviews with advanced physics students, which helped us gain insights into their problem-solving strategies, evaluate their understanding developed through the tutorial and make necessary refinements to the MoI tutorial. The study identified common student difficulties, which were subsequently integrated into the inquiry-based tutorial as a guide to provide support to students. We found that advanced students have common difficulties related to physics concepts similar to those found in introductory physics courses. The performance difference in the pretest administered after lecture-based instruction and the posttest administered after working through the tutorial reflects students' ability to apply what they learned from the inquiry-based tutorial compared to traditional lecture. Another important and unanticipated finding reveals how instructor's framing about inquiry-based instructional tasks can have a significant impact on student motivation, engagement, and performance. Overall, this iterative multi-year design-based comparative research with mixed-method triangulation provides valuable insights on the challenges involved in such studies that educators and researchers alike can greatly benefit from.
Andrea Barone, Henri M. J. Boffin, Beatrice Caccherano, Simona Di Stefano, Akhila Divakaran, Alexandra S. Murphy, María José Rain, Elyar Sedaghati, Paul V. Steimle
During the 2026 ESO La Silla Observing school, about twenty students attended lectures and performed observations to learn various aspects of observational astronomy. The school, which took place during the first two weeks of February 2026, made use of EFOSC2/NTT and HARPS+NIRPS/3.6m. One of the groups was devoted to the study of binary stars. Several projects were considered and followed up by some of the six students in this group. The first subgroup used HARPS to study the Rossiter-McLaughlin effect in binary stars to infer the relative inclination of the rotation axis of the primary with respect to the orbital plane. A detailed study of the contact binary system HD 115264 led to the conclusion that the primary is well aligned, likely as a result of strong tidal forces within the binary. The second subgroup analysed blue straggler stars (BSS) in open clusters, using both HARPS and EFOSC2. With HARPS, they looked at some well-known long-period binary with the aim of determining their chemical abundances, thereby confirming their membership to the cluster, as well as looking for any chemical anomalies that might be explained by mass transfer. EFOSC2 was used to derive radial velocities of rapidly varying BSS. For one of them - the star Rediet - the students clearly detected and analysed the radial velocity variations due to the second overtone pulsation, thereby confirming its delta Scuti character. Finally, one student used EFOSC2 to study planetary nebulae (PN) - taking nice images of some of these intricate objects, as well as doing time-resolved photometry and spectra of some others. In one case, the binary nature of the central star of the PN was proven, confirming some previous estimates done with ZTF. Each subgroup was thus able to obtain useful research results, which we present hereafter.
Sara Ayman Metwalli, Aryan Iliat, Steven Thomas, Suresh Nair, Zizwe A. Chase, Russell R. Ceballos
Quantum information science and engineering (QISE) is advancing rapidly, creating an urgent demand for a quantum-literate, technically proficient workforce. Despite this need, quantum education initiatives remain fragmented across regions, educational levels, and instructional approaches, which constrains their scalability and overall impact. This paper offers a structured analysis of the current quantum education ecosystem by synthesizing global initiatives, pedagogical strategies, and emerging trends. Quantum education is examined through a dual framework that considers both learner progression and instructional methodology, emphasizing the evolution of educational approaches from conceptual exposure to formal reasoning and practical application. Analysis of data from international programs and academic literature reveals key challenges, including inequitable access, absence of standardized curricula, limited empirical evaluation, and discontinuities between educational stages. Quantum education is more accurately conceptualized as a non-linear ecosystem rather than a traditional pipeline, characterized by multiple entry points, feedback mechanisms, and critical transition gaps. Based on this perspective, directions are proposed for developing more coherent, inclusive, and scalable educational frameworks that align with workforce requirements and technological progress. This work presents a unified perspective on the quantum education landscape and outlines actionable strategies to enhance global quantum literacy and workforce preparedness.
Roy Cruz Candelaria, Wouter Deconinck, Aman Desai, Guillermo Fidalgo Rodríguez, Michel Hernandez Villanueva, Kilian Lieret, Valeriia Lukashenko, Sudhir Malik, Marco Mambelli, Tetiana Mazurets, Alexander Moreno Briceño, Andres Rios-Tascon, Richa Sharma
We present the material and resources developed for training physicists on containerization technologies enabled by Apptainer. In the context of analysis preservation using Apptainer's capabilities, we have developed examples that execute common tools in High Energy Physics (HEP) and Nuclear Physics within containers. Training physicists on containerization technologies is of utmost importance in today's research landscape. By embracing these technologies, users can achieve enhanced reproducibility, portability, collaboration, and resource efficiency, assuring the conditions and integrity of the scientific analysis process. This training module,``Introduction to Apptainer/Singularity'', is part of the HEP Software Foundation Training Center, which aims to equip newcomers to the field of High Energy Physics with the necessary software skills and best practices.
Yi Zhou
The rapid integration of Large Language Models (LLMs) into scientific writing fundamentally challenges traditional definitions of authorship, responsibility, and scientific integrity. As researchers transition from using computers as deterministic tools to managing them as ``virtual collaborators,'' the nature of human contribution must be re-evaluated. Using the drafting process of a recent computational physics manuscript as a case study, this essay explores the indispensable role of the Human-in-the-Loop (HITL). We demonstrate that while AI excels at structural organization and syntax generation, the human author bears the ultimate responsibility for enforcing rigorous physical logic, maintaining academic diplomacy, and anticipating peer-review critiques. In this paradigm, the human contribution shifts from writing boilerplate text to acting as a Principal Investigator who actively mentors and steers the AI's reasoning. To ensure accountability and preserve the integrity of the scientific record in this new era, I argue that the community must mandate the publication of full, unedited AI interaction transcripts as standard supplementary material.
Sanjoy Kumar Pal, Papun Mondal, Pradipta Panchadhyayee, Anirban Samanta, Subhash Chandra Samanta
In both rural and urban educational settings, science education is often hindered by limited access to lab resources and intimidating, complex instruments. This paper introduces a low-cost, homemade experimental apparatus built using a mobile charger, nichrome wire, galvanometer, and digital multimeter that enables educators to perform key higher secondary electricity experiments. The Indigenous Metre Bridge (IMB) has proven to be an intuitive, user-friendly tool that not only bridges theoretical and practical learning but also reduces student apprehension toward lab work. Its simplicity and accessibility exemplify how frugal innovation can transform physics education.
Bayu Setiaji, Pramudya Wahyu Pradana, Febrina Siska Widyaningtyas, Purwoko Haryadi Santoso, Yusman Wiyatmo, Heru Kuswanto
In this paper, we describe a presentation on the physics of Gudeg, a traditional food from Indonesia specifically originated in the Special District of Yogyakarta. This learning context is designed for the high school physics curricula. The physics presentation focuses on the making processes of Gudeg. Qualitative interviews with Gudeg makers were carried out by the researchers to thematize the process of making Gudeg and highlight its educational connections for the physics learning. Five extracted learning themes are how the density concept behind peeling the jackfruit skin (main Gudeg ingredient), how the relation between the Youngs modulus concept and the jackfruit sections, how the texture-torque experiment of the sweet and tasty gudeg, how the effect of boiling mechanism on the texture of the jackfruit, and how the conduction and convection of the preserved Gudeg. Using our learning strategy which is so-called Collaborative Project based Teaching, we provide simple experimentations and demonstrations of the physical concepts behind these Gudeg processes that are promising for conceptual physics learning by managing triple educational roles between teachers, students, and Gudeg practitioners. This approach can be generally adopted beyond physics to promote the excitement of traditional knowledge which can enhance pedagogical approach in educational setting.
Apekshya Ghimire, Chandralekha Singh
Learning to think like a physicist (LTP) is often cited as a central goal of graduate physics education, yet what this means in practice and the extent to which physics graduate education prepares students to develop LTP and view LTP as valuable to their research and teaching remain unclear. This interview-based study, conducted with seven physics graduate students at one US public research university, explores how students define thinking like a physicist and how their coursework and research experiences correlate with this development. Students emphasized that physics uniquely requires integrating physical and mathematical concepts in ways that go beyond other science disciplines. Our findings show that physics core courses, particularly electricity and magnetism, frequently emphasize mathematical techniques and content coverage at a rapid pace at the expense of deeper conceptual engagement and development of LTP. In contrast, physics elective courses and research experiences were more synergistic with and effective in fostering conceptual understanding, problem-solving skills, and identity development as physicists. Because graduate students simultaneously take core courses, conduct research and teach introductory physics, their perspectives on LTP are particularly valuable in how physics departments may consider transforming their preparation. Their voices highlight how this transformative stage of training can either support or hinder the development of physicist thinking.
Harry Brough
We present TUNA, an open-source quantum chemistry program specifically designed for atoms and diatomic molecules. Within this narrow molecular domain, a broad and consistent set of electronic structure methods and calculation types is available. Energies, optimisations, vibrational frequencies, response properties, coordinate scans and ab initio molecular dynamics trajectories can be accessed through an intuitive command-line interface. A single principle underlies TUNA: once a method can be used to evaluate the energy, all properties follow from numerical differentiation. This makes the program both a transparent teaching platform and a compact environment for benchmarking methods on diatomics $\unicode{x2014}$ among the most simple yet instructive systems in quantum chemistry. Reference implementations including density functional theory, many-body perturbation theory and coupled cluster theory, supported by detailed theoretical documentation, make TUNA an accessible foundation for developing improved methods and algorithms in electronic structure.
Mauricio Echiburu, José L. Marcos, René Ríos, Robinson Moreno Martínez
In 1949, Captain Alberto Larraguibel and his horse Huaso set the world record for equestrian high jump in Viña del Mar, Chile, by clearing a height of 2.47 meters, a mark that remains unbeaten. This work proposes the use of this historical event as a teaching resource for physics, integrating perspectives from biomechanics and veterinary medicine. Based on the analysis of an audiovisual record of the jump, a kinematic model is developed using the \textit{Tracker} software, determining variables such as displacement, velocity, and acceleration of the horse--rider system. The results make it possible to reflect on the biomechanical and physiological factors involved in animal performance, thus linking physics with real biological processes. It is proposed that this interdisciplinary approach, based on authentic cultural and scientific contexts, may promote meaningful learning, motivation, and a more comprehensive understanding of natural phenomena in science education.
Matt Bellis, Matthew Carberg, Chester Gould, Jackson Ingenito, Fasiha Khaliq, Emely Kintzel, Shane Kirschmann, Neha Matta, Sophia Pavia, Emmett Pearl, Payton Ramsdill, Grace Scherer, Cullen Wright
Two significant goals of the particle physics community is the precision study of the Higgs boson and the search for new particles. The Large Hadron Collider (LHC) is the current high-energy collider, soon to be superseded by the High-Luminosity LHC (HL-LHC). Much of the community has rallied around a muon-collider, though that is most likely 25 years in the future. In this paper, we argue for a bolder approach: {\it a tau-collider}, in which oppositely-charged $τ$-leptons are collided with energies on the yotta-eV scale and a potential radius that places it in the Oort cloud. Given the long time-scale and significant construction challenges, we strongly suggest the focus of the community shift to this discovery machine. We acknowledge that the technology necessary may require humanity to evolve to a Kardashev Level-I or Level-II civilization, which is all the more reason to begin R\&D now.