This paper estimates marginal returns to college for individuals induced to enroll in college by different marginal policy changes. The recent instrumental variables literature seeks to estimate this parameter, but in general it does so only under strong assumptions that are tested and found wanting. We show how to utilize economic theory and local instrumental variables estimators to estimate the effect of marginal policy changes. Our empirical analysis shows that returns are higher for individuals with values of unobservables that make them more likely to attend college. We contrast our estimates with IV estimates of the return to schooling.
Hirohisa Fujikawa, Hidetaka Tamune, Yuji Nishizaki
et al.
Abstract Although considerable bodies of literature have elucidated various determinants of burnout and job satisfaction among medical residents, one aspect that remains under-examined is the impact of patient care ownership (PCO). Therefore, we aimed to examine the associations between PCO, burnout, and job satisfaction among residents. This was a nationwide cross-sectional study, using online anonymous surveys from January 17 to March 31, 2024. The participants were residents who participated in the General Medicine In-Training Examination, a nationwide examination in Japan. The primary outcome was burnout, assessed using the Single-item Measure of Burnout Scale. The secondary outcome was job satisfaction, measured by the item included in the Mini-Z 2.0. The explanatory variable was PCO, as assessed by the Japanese version of the PCO Scale. 1816 participants were in the analysis. Multivariable logistic regression analyses revealed that, after adjustment for possible confounders, PCO showed a negative association with burnout, and that there was a positive association between PCO and job satisfaction. The findings suggest the importance of emphasizing PCO in the context of exploring burnout and job satisfaction among medical residents. This knowledge will inform educational interventions to help residents work with less burnout and greater job satisfaction, ultimately leading to better patient outcomes.
As artificial intelligence and digital technologies reshape every aspect of our daily lives, we – educators and perhaps all of humanity – face an urgent question: What kinds of learning experiences best prepare children to function and flourish in a rapidly evolving world? This column contends that music activities provide precisely the kinds of human interactions and competences that technology cannot replace. Sustained attention, emotional expression, collaboration, problem solving, and executive self-regulation are a few that seem to jump to the forefront of the discourse. Contemporary research appears to offer compelling evidence that music education is not merely compatible with a tech-driven future, it is foundational to it as a path to retain our humanity.
Introduction: Gamma Knife Perfexion™ delivers 192 Cobalt-60 sources to the focal point (isocenter), and the patient is fixed using a stereotactic frame. In conformal techniques, the width of the penumbra resulting in an out-of-field dose of normal tissue adjacent to the tumor must be accurately determined. The purpose of this study was to calculate the penumbra widths of a single beam and 192 beams for different collimator sizes of the Gamma Knife Perfexion™ using the BEAMNRC/DOSXYZNRC Monte Carlo simulation code and compare the results with EBT3 film dosimetry data.
Material and Methods: To investigate the physical penumbra width (80-20%), the single beam and 192 beam profiles were obtained using the DOSXYZNRC code and EBT3 films located at the isocenter point in a spherical solid water phantom with a diameter of 160 mm.
Results: The results showed that the Gamma Passing Rate (GPR) value for all collimator sizes has a value above 97%. The single-beam penumbra widths obtained from simulation data for 4, 8, and 16 mm collimator sizes along the X-axis were 0.75, 0.77, and 0.87 mm, respectively. The data for 192 beams obtained from the simulation were 2.60, 4.80, and 8.70 mm along the X-axis.
Conclusion: The differences between measured and simulated penumbra widths are in an acceptable range. However, for more precise measurement in the penumbra region with a high dose gradient, a Monte Carlo simulation is recommended.
Medical physics. Medical radiology. Nuclear medicine
Víctor Álvarez Rojo, M. Teresa Padilla Carmona, Javier Rodríguez Santero
et al.
La investigación ha explorado las formas, grados y estrategias con las que los estudiantes de la Universidad de Sevilla participan en su evaluación. Se ha realizado un estudio descriptivo en el que se aplicaron dos instrumentos de recogida de datos: una escala para valorar el grado en que los programas docentes propician participación de los estudiantes en su evaluación, y un cuestionario (versión para estudiantes y para docentes) sobre actitudes, creencias y prácticas en torno a este tema. Se ha recogido información de 75 programas (n1), 65 docentes (n2) y 463 estudiantes (n3). Si bien una mayoría de docentes considera necesaria la participación de los estudiantes, su aplicación práctica es muy limitada, siendo el docente el único evaluador en un 85% de casos.Asimismo, aunque la mitad del profesorado se muestra proclive a utilizar la autoevaluación y la evaluación de compañeros como contraste a su propia valoración, este grupo es reacio a consensuar las calificaciones con el alumnado.
Descriptores: •
evaluación de compañeros
Juliana Yimabel Ballesteros Menéndez, Joe Moisés Gallegos Burnham, Johana del Carmen Parreño Sánchez
et al.
La presente investigación tiene como tema central el estudio de las herramientas digitales para mejorar la evaluación del aprendizaje en la educación superior. De igual forma, identificar los fundamentos teóricos del uso de herramientas digitales en la evaluación. La investigación adoptó un diseño no experimental con un enfoque mixto. La modalidad de estudio fue documental bibliográfico, dado que se centró en la búsqueda, recuperación de la información obtenida de fuentes documentales. La población se enfocó en los estudiantes y docentes de la Facultad de Educación de la carrera de Educación Básica, en la Universidad Bolivariana del Ecuador. La población objetiva está constituida por aquellos que se encuentran cursando los últimos años de la carrera, estudiantes totales 4677 la muestra 55 estudiantes del grupo 30 y 10 docentes que imparten asignaturas pedagógicas en la misma carrera. El método de selección fue un muestreo intencional no probabilístico que aporta información relevante sobre su efectividad. Para la recolección de datos se empleó la encuesta para docentes y estudiantes las cuales están diseñadas para garantizar la validez y la relevancia de los datos. Los resultados mostraron que el 35,7% de los encuestados manifiestan que siempre emplean herramientas digitales en el proceso de evaluación. Así también, un 35,7% manifiestan casi siempre emplean herramientas digitales. En cambio, un 28.6% manifiestan que rara vez emplean herramientas digitales. Se concluye que las herramientas digitales para mejorar la evaluación del aprendizaje en la educación superior son fundamentales, puesto que promueve el desarrollo profesional y reflexivo del estudiante.
Plant-based diets are increasingly attracting attention as they play a significant role in human health and environmental sustainability and are believed to be key components of sustainable food systems. In the present study, both pros and cons of the adoption of plant-based diets are analyzed using a bibliometric method integrated with a qualitative examination of the scientific literature. For the bibliometric study, Bibliometrix software was utilized, examining 3245 scientific articles, downloaded from the Scopus database, and printed between the years 1957 and 2025. The analyses were conducted using R software, version 4.4.1, with access to the Bibliometrix package, version 4.1. The results indicate a remarkable rise, in the last two decades, in the scholarly focus on the influence of plant-based diets on the individual’s health condition as well as the environment. Keyword co-occurrence studies and international collaborations demonstrate a dominance of research focus in both the United States and Europe, with significant contributions from the Asia–Pacific region. Furthermore, the current work offers qualitative identification of the benefits of plant diets from various perspectives like nutritional, economic, ecological, and cultural. It also explores the main dissuaders from adhering to these diets, including perceived nutritional hazards, cost perceptions, low availability, and social prohibitions. Findings emphasize that, in spite of all the barriers, plant food-based diets have a wide-ranging ability to provide tangible benefits at both the individual and population levels, and documented in the scientific literature are recommendations of expert-led education programs, economic incentives, and judiciously framed public policies to overcome these barriers and to make this transition possible towards sustainable food choices. Findings provide a comprehensive understanding of the current lines of inquiry and stage the subsequent work on how to motivate sustainability among the general population.
Pete Leihy , Upasana Singh, Suriamurthee Moonsamy Maistry
et al.
This article aims to complement and contribute to the discussion of increasingly acute pressures facing Southern Africa’s education systems due to migration trends, by placing such pressures within the broader context of instability across Africa and comparing this with other global conflict- and scarcity-driven migration patterns. Historically, during the Cold War —spanning from the end of World War II to the early 1990s— certain states, such as apartheid-era South Africa, Chile under political polarisation culminating in the 1973-1990 dictatorship, and communist Romania, witnessed repressive regimes forcing citizens into exile. In the wake of subsequent and ongoing conflicts elsewhere, these countries have now evolved into becoming recipients of exiles, a role informed by national reconciliation processes. While they share a common thread of exile and migration, their transitions to educational hosting reveal unique challenges rooted in historical legacies, economic conditions, and policy responses. Meanwhile, Mauritius provides a point of comparison, as what has historically been a place of exile increasingly loses educated people.
The introduction of generative artificial intelligence (GenAI) has been met with a mix of reactions by higher education institutions, ranging from consternation and resistance to wholehearted acceptance. Previous work has looked at the discourse and policies adopted by universities across the U.S. as well as educators, along with the inclusion of GenAI-related content and topics in higher education. Building on previous research, this study reports findings from a survey of engineering educators on their use of and perspectives toward generative AI. Specifically, we surveyed 98 educators from engineering, computer science, and education who participated in a workshop on GenAI in Engineering Education to learn about their perspectives on using these tools for teaching and research. We asked them about their use of and comfort with GenAI, their overall perspectives on GenAI, the challenges and potential harms of using it for teaching, learning, and research, and examined whether their approach to using and integrating GenAI in their classroom influenced their experiences with GenAI and perceptions of it. Consistent with other research in GenAI education, we found that while the majority of participants were somewhat familiar with GenAI, reported use varied considerably. We found that educators harbored mostly hopeful and positive views about the potential of GenAI. We also found that those who engaged more with their students on the topic of GenAI, tend to be more positive about its contribution to learning, while also being more attuned to its potential abuses. These findings suggest that integrating and engaging with generative AI is essential to foster productive interactions between instructors and students around this technology.
In this paper, in order to reduce the energy leakage caused by the discretized representation in sparse channel estimation for Orthogonal Frequency Division Multiplexing (OFDM) systems, we systematically have analyzed the optimal locations of atoms with discrete delays for each path reconstruction from the perspective of linear fitting theory. Then, we have investigated the adverse effects of the non-ideal inner product function on the iteration in one of the most widely used channel estimation method, Orthogonal Matching Pursuit (OMP). The study shows that the distance between the selected atoms for each path in OMP can be larger than the sampling interval, which prevents OMP-based methods from achieving better performance. To overcome this drawback, the image deblurring-based channel estimation method, in which the channel estimation problem is analogized to one-dimensional image deblurring, was proposed to improve the large compensation distance of traditional OMP. The advantage of the proposed method was validated by the results of numerical simulation and sea trial data decoding.
Purpose Although interest in various forms of learning media is increasing due to the coronavirus disease 2019 (COVID-19) pandemic there is relatively little research on influencing student motivation by intervening in cognitive processing. The purpose of this study was to present the optimal form of learning materials provided to medical students. Methods This study provided learning materials in class at a level according to social cues (script, video [artificial intelligence (AI) voice], video [professor voice]) based on the principle of voices among the principles of personalization, voices, image, and embodiment of social cues in multimedia learning, and surveyed students’ opinions. Results There was no statistically significant difference according to social clues in satisfaction and learning help, but both appeared in the order of silent videos containing the professor’s voice, followed by videos containing the AI voice. Conclusion This study is significant in that there is no research on the impact of student motivation on the provision of learning materials for medical school education in Korea, and we hope that it will help provide learning materials for self-directed learning of medical students in the post-COVID-19.
Jannik Henze, André Bresges, Sebastian Becker-Genschow
The integration of artificial intelligence (AI) in physics education enables novel approaches to data analysis and conceptual learning. A comparative analysis of AI-supported and traditional Excel-based methods reveals distinct strengths and limitations in fostering understanding of pendulum experiments. This study explores the integration of AI-assisted tools, such as a custom chatbot based on ChatGPT, and traditional Excel-based methods in physics education, revealing that while both approaches produce comparable quantitative learning gains, AI tools provide significant qualitative advantages. These include enhanced emotional engagement and higher motivation, highlighting the potential of AI to create a more positive and supportive learning environment. Adaptive AI technologies offer significant promise in supporting structured, data-intensive tasks, emphasizing the necessity for thoughtfully balanced integration into educational practices.
Trust plays a pivotal role in Lecturer-Student-Collaboration, encompassing teaching and research aspects. The advent of Large Language Models (LLMs) in platforms like Open AI's ChatGPT, coupled with their cost-effectiveness and high-quality results, has led to their rapid adoption among university students. However, discerning genuine student input from LLM-generated output poses a challenge for lecturers. This dilemma jeopardizes the trust relationship between lecturers and students, potentially impacting university downstream activities, particularly collaborative research initiatives. Despite attempts to establish guidelines for student LLM use, a clear framework mutually beneficial for lecturers and students in higher education remains elusive. This study addresses the research question: How does the use of LLMs by students impact Informational and Procedural Justice, influencing Team Trust and Expected Team Performance? Methodically, we applied a quantitative construct-based survey, evaluated using techniques of Structural Equation Modelling (PLS- SEM) to examine potential relationships among these constructs. Our findings based on 23 valid respondents from Ndejje University indicate that lecturers are less concerned about the fairness of LLM use per se but are more focused on the transparency of student utilization, which significantly influences Team Trust positively. This research contributes to the global discourse on integrating and regulating LLMs and subsequent models in education. We propose that guidelines should support LLM use while enforcing transparency in Lecturer-Student- Collaboration to foster Team Trust and Performance. The study contributes valuable insights for shaping policies enabling ethical and transparent LLMs usage in education to ensure effectiveness of collaborative learning environments.
The integration of artificial intelligence (AI) in education has shown significant promise, yet the effective personalization of learning, particularly in physics education, remains a challenge. This paper proposes Physics-STAR, a framework for large language model (LLM)- powered tutoring system designed to address this gap by providing personalized and adaptive learning experiences for high school students. Our study evaluates Physics-STAR against traditional teacher-led lectures and generic LLM tutoring through a controlled experiment with 12 high school sophomores. Results showed that Physics-STAR increased students' average scores and efficiency on conceptual, computational, and on informational questions. In particular, students' average scores on complex information problems increased by 100% and their efficiency increased by 5.95%. By facilitating step-by-step guidance and reflective learning, Physics-STAR helps students develop critical thinking skills and a robust comprehension of abstract concepts. The findings underscore the potential of AI-driven personalized tutoring systems to transform physics education. As LLM continues to advance, the future of student-centered AI in education looks promising, with the potential to significantly improve learning outcomes and efficiency.