Hasil untuk "Education"

Mauricio Echiburu, José L. Marcos, René Ríos et al.

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.

Yang Ni, Fanli Jia

Artificial intelligence (AI)-enabled digital interventions, including Generative AI (GenAI) and Human-Centered AI (HCAI), are increasingly used to expand access to digital psychiatry and mental health care. This PRISMA-ScR scoping review maps the landscape of AI-driven mental health (mHealth) technologies across five critical phases: pre-treatment (screening/triage), treatment (therapeutic support), post-treatment (remote patient monitoring), clinical education, and population-level prevention. We synthesized 36 empirical studies implemented through early 2024, focusing on Large Language Models (LLMs), machine learning (ML) models, and autonomous conversational agents. Key use cases involve referral triage, empathic communication enhancement, and AI-assisted psychotherapy delivered via chatbots and voice agents. While benefits include reduced wait times and increased patient engagement, we address recurring challenges like algorithmic bias, data privacy, and human-AI collaboration barriers. By introducing a novel four-pillar framework, this review provides a comprehensive roadmap for AI-augmented mental health care, offering actionable insights for researchers, clinicians, and policymakers to develop safe, effective, and equitable digital health interventions.

Géssika Mendes Vieira, Vania Maria de Oliveira Vieira

Este artigo faz parte de um estudo maior, vinculado a uma pesquisa de mestrado desenvolvida em 2020, financiada pela CAPES e inserida na RIDEP - Rede Internacional de Pesquisas sobre o Desenvolvimento Profissional de Professores[1]. No estudo maior, o objetivo geral foi compreender as Representações Sociais dos alunos de um curso de Publicidade e Propaganda de uma IES mineira sobre as implicações dos instrumentos de avalição da aprendizagem utilizados pelos seus professores. Para o alcance desse objetivo foi realizado um estudo a partir da obra de Mizukami (1986) sobre as diferentes abordagens de ensino-aprendizagem e como elas se manifestam na prática avaliativa. É disso que trata o presente artigo, cujo objetivo é analisar como as diferentes abordagens de ensino-aprendizagem descritas por Mizukami (1986) se manifestam na prática avaliativa, destacando suas características, processos e representantes, e avaliar a relevância dessas abordagens na atualidade. A partir de um estudo bibliográfico e exploratório, discutiu-se as abordagens Tradicional, Comportamentalista, Humanista, Cognitivista e Sócio-cultural e suas características, bem como os seus principais representantes. Foi possível verificar que cada abordagem percebe o processo avaliativo de uma forma diferente -  a tradicional tem a perspectiva de medir as informações que o estudante reproduz, a comportamentalista busca constatar o que foi aprendido, a humanista não trabalha com padrões e considera o indivíduo como o centro do seu processo de aprendizagem, a cognitivista considera a assimilação e as noções do conhecimento e, por fim, a sócio-cultural trabalha com um processo contínuo de avaliação mútua da prática educativa entre estudante e professor.      

Gal Puris, Angela Chetrit, Eldad Katorza

As medical imaging continues to expand, concerns about the potential risks of ionizing radiation to the developing fetus have led to a preference for non-radiation-based alternatives such as ultrasonography and fetal MRI. This review examines the current evidence on the safety of MRI during pregnancy, with a focus on 3 T MRI and contrast agents, aiming to provide a comprehensive synthesis that informs clinical decision-making, ensures fetal safety and supports the safe use of all available modalities that could impact management. We conducted a comprehensive review of studies from 2000 to 2024 on MRI safety during pregnancy, focusing on 3 T MRI and gadolinium use. The review included peer-reviewed articles and large database studies, summarizing key findings and identifying areas for further research. Fetal MRI, used alongside ultrasound, enhances diagnostic accuracy for fetal anomalies, particularly in the brain, thorax, gastrointestinal and genitourinary systems, with no conclusive evidence of adverse effects on fetal development. While theoretical risks such as tissue heating and acoustic damage exist, studies show no significant harm at 1.5 T or 3 T, though caution is still advised in the first trimester. Regarding gadolinium-based contrast agents, the evidence is conflicting: while some studies suggest risks such as stillbirth and rheumatological conditions, animal studies show minimal fetal retention and no significant toxicity, and later clinical research has not substantiated these risks. The existing literature on fetal MRI is encouraging, suggesting minimal risks; however, further investigation through larger, prospective and long-term follow-up studies is essential to comprehensively determine its safety and late effects.

Wei Meng

This study addresses the structural complexity and semantic ambiguity in stakeholder interactions within the Education-Industry Integration (EII) system. The scarcity of real interview data, absence of structured variable modeling, and lack of interpretability in inference mechanisms have limited the analytical accuracy and policy responsiveness of EII research. To resolve these challenges, we propose a structural modeling paradigm based on the National Institute of Standards and Technology (NIST) synthetic data quality framework, focusing on consistency, authenticity, and traceability. We design a five-layer architecture that includes prompt-driven synthetic dialogue generation, a structured variable system covering skills, institutional, and emotional dimensions, dependency and causal path modeling, graph-based structure design, and an interactive inference engine. Empirical results demonstrate the effectiveness of the approach using a 15-segment synthetic corpus, with 41,597 tokens, 127 annotated variables, and 820 semantic relationship triples. The model exhibits strong structural consistency (Krippendorff alpha = 0.83), construct validity (RMSEA = 0.048, CFI = 0.93), and semantic alignment (mean cosine similarity > 0.78 via BERT). A key causal loop is identified: system mismatch leads to emotional frustration, reduced participation, skill gaps, and recurrence of mismatch, revealing a structural degradation cycle. This research introduces the first NIST-compliant AI modeling framework for stakeholder systems and provides a foundation for policy simulation, curriculum design, and collaborative strategy modeling.

Welington Fabrício dos Santos Costa, Jesuíno Alves Martins Júnior, André Flávio Gonçalves Silva et al.

In recent years, the frequency of extreme weather events on Earth has increased significantly. This phenomenon is driven by the intensification of the greenhouse effect caused by anthropogenic activities, leading to temperature variations in urban environments that affect thermal comfort and quality of life. Given this context, the present study investigates temperature mapping in urban biomes using an infrared thermometer, conducted as part of a hands-on workshop offered during the 21st National Science and Technology Week. The initiative involved students from the public school system and was grounded in Physics education, aiming to foster scientific enculturation. Participants engaged in a problem-based learning experience, actively contributing to all stages of the knowledge construction process. The objective was to examine the relationship between vegetation presence and its impact on temperature in urban environments. A qualitative and quantitative methodological approach was adopted, enabling the identification of scientific literacy indicators such as information sequencing, data organization, logical reasoning, hypothesis formulation, justification, and explanation of observed phenomena. The analysis of students' statements and activity guidelines provided insights into their critical thinking development. The findings indicate that students developed essential skills for understanding physical and environmental phenomena, effectively linking collected data to scientific concepts and proposing well-supported interpretations. Moreover, the experience reinforced the perception of science as a dynamic and investigative process, fostering curiosity and enhancing students' argumentative abilities. Thus, the workshop proved to be an effective strategy for promoting scientific literacy and engaging participants in the study of environmental impacts in urban contexts.

Lic. Ernesto Sixto Carcassés Sánchez, Dra. C. Ada Iris Infante Ricardo, Lic. Celys Bárbara Milán Guevara

Durante el proceso pedagógico es preciso desarrollar cualidades laborales, tales como: ser laborioso, responsable, solidario, independiente, sensible, creativo y perseverante, que propicien la formación integral de los estudiantes para lograr su desempeño a la altura que demanda la sociedad de hoy. El presente trabajo tiene el objetivo de exponer un proyecto formativo realizado en el Instituto Preuniversitario Enrique José Varona, de Holguín: el periódico estudiantil El Varona dice, que estimula la actividad de investigación social, la crónica, el artículo periodístico y la orientación hacia carreras universitarias como Periodismo, Historia, Ciencias Exactas, Sociales, Humanísticas y Pedagógicas, como continuidad de la prensa de los años 40 y 50 del siglo pasado en el instituto. Fueron de utilidad los métodos de análisis–síntesis, la inducción-deducción, el análisis documental, los talleres de opinión crítica y construcción colectiva y las entrevistas individuales y grupales.  El resultado fundamental se concreta en el cambio de actitudes de los estudiantes respecto a la actividad laboral, el desarrollo de cualidades y la generalización e impacto del periódico en otros centros educacionales y en la juventud estudiantil holguinera como ejercicio de democracia y formación de valores.  

Kyrie Zhixuan Zhou, Yilin Zhu, Jingwen Shan et al.

Sex education helps children obtain knowledge and awareness of sexuality, and protects them against sexually transmitted diseases, pregnancy, and sexual abuse. Sex education is not well taught to children in China -- both school-based education and parental communication on this topic are limited. To interrogate the status quo of sex education in China and explore suitable interventions, we conducted a series of formative studies including interviews and social media analysis. Multiple stakeholders such as children, parents, education practitioners, and the general public were engaged for an in-depth understanding of their unique needs regarding teaching and learning sex education. We found that school-based sex education for Chinese children was currently insufficient and restrictive. Involving parents in sex education posed several challenges, such as a lack of sexuality and pedagogy knowledge, and embarrassment in initiating sex education conversations. Culture and politics were major hurdles to effective sex education. Based on the findings, we reflect on the complex interactions between culture, politics, education policy, and pedagogy, and discuss situated design of sex education in broader cultural and social contexts.

John C. Howell, Brian Flores, Juan Javier Naranjo et al.

We report on an educational pilot program for low-cost physics experimentation run in Ecuador, South Africa, and the United States. The program was developed after having needs-based discussions with African educators, researchers, and leaders. It was determined that the need and desire for low-cost, skills-building, and active-learning tools is very high. From this, we developed a 3D-printable, Raspberry Pi-based multispectral camera (15 to 25 spectral channels in the visible and near-IR) for as little as $100. The program allows students to learn 3D modeling, 3D printing, feedback, control, image analysis, Python programming, systems integration and artificial intelligence as well as spectroscopy. After completing their cameras, the students in the program studied plant health, plant stress, post-harvest fruit ripeness, and polarization and spectral analysis of nanostructured insect wings, the latter of which won the ``best-applied research" award at a conference poster session and will be highlighted in this paper. Importantly, these cameras can be an integral part of any developing country's agricultural, recycling, medical, and pharmaceutical infrastructure. Thus, we believe this experiment can play an important role at the intersection of student training and developing countries' capacity building.

Kristin A. Oliver, Victoria Borish, Bethany R. Wilcox et al.

As quantum technologies transition out of the research lab and into commercial applications, it becomes important to better prepare students to enter this new and evolving workforce. To work towards this goal of preparing physics students for a career in the quantum industry, a senior capstone course called "Quantum Forge" was created at the University of Colorado Boulder. This course aims to provide students a hands-on quantum experience and prepare them to enter the quantum workforce directly after their undergraduate studies. Some of the course's goals are to have students understand what comprises the quantum industry and have them feel confident they could enter the industry if desired. To understand to what extent these goals are achieved, we followed the first cohort of Quantum Forge students through their year in the course in order to understand their perceptions of the quantum industry including what it is, whether they feel that they could be successful in it, and whether or not they want to participate in it. The results of this work can assist educators in optimizing the design of future quantum-industry-focused courses and programs to better prepare students to be a part of this burgeoning industry.

Ande Shen, Jiwei Zhou

This paper explores the causal impact of education opportunities on rural areas by exploiting the higher education expansion (HEE) in China in 1999. By utilizing the detailed census data, the cohort-based difference-in-differences design indicates that the HEE increased college attendance and encouraged more people to attend senior high schools and that the effect is more significant in rural areas. Then we apply a similar approach to a novel panel data set of rural villages and households to examine the effect of education opportunities on rural areas. We find contrasting impacts on income and life quality between villages and households. Villages in provinces with higher HEE magnitudes underwent a drop in the average income and worse living facilities. On the contrary, households sending out migrants after the HEE experienced an increase in their per capita income. The phenomenon where villages experienced a ``brain drain'' and households with migrants gained after the HEE is explained by the fact that education could serve as a way to overcome the barrier of rural-urban migration. Our findings highlight the opposed impacts of education opportunities on rural development and household welfare in rural areas.

Ikpe Justice Akpan, Yawo M. Kobara, Josiah Owolabi et al.

Artificial intelligence (AI) as a disruptive technology is not new. However, its recent evolution, engineered by technological transformation, big data analytics, and quantum computing, produces conversational and generative AI (CGAI/GenAI) and human-like chatbots that disrupt conventional operations and methods in different fields. This study investigates the scientific landscape of CGAI and human-chatbot interaction/collaboration and evaluates use cases, benefits, challenges, and policy implications for multidisciplinary education and allied industry operations. The publications trend showed that just 4% (n=75) occurred during 2006-2018, while 2019-2023 experienced astronomical growth (n=1763 or 96%). The prominent use cases of CGAI (e.g., ChatGPT) for teaching, learning, and research activities occurred in computer science [multidisciplinary and AI] (32%), medical/healthcare (17%), engineering (7%), and business fields (6%). The intellectual structure shows strong collaboration among eminent multidisciplinary sources in business, Information Systems, and other areas. The thematic structure of SLP highlights prominent CGAI use cases, including improved user experience in human-computer interaction, computer programs/code generation, and systems creation. Widespread CGAI usefulness for teachers, researchers, and learners includes syllabi/course content generation, testing aids, and academic writing. The concerns about abuse and misuse (plagiarism, academic integrity, privacy violations) and issues about misinformation, danger of self-diagnoses, and patient privacy in medical/healthcare applications are prominent. Formulating strategies and policies to address potential CGAI challenges in teaching/learning and practice are priorities. Developing discipline-based automatic detection of GenAI contents to check abuse is proposed.

A. Hwong, Y. Li, R. Morin et al.

Introduction Older adults with schizophrenia often have multiple chronic conditions, or multimorbidity, yet most prior research has focused on single medical conditions. Objectives To characterize multimorbidity patterns and utilization among older adults with schizophrenia to understand how multimorbidity affects this population and their clinical service needs. Methods This retrospective cohort study included veterans aged 50 years and older with schizophrenia and followed their comorbid diagnoses and utilization (outpatient, inpatient, and emergency) from 2012 to 2019. Comorbid diagnoses included myocardial infarction, congestive heart failure, stroke, chronic obstructive pulmonary disease (COPD), cancer, dementia, traumatic brain injury, hepatitis C, osteoarthritis, renal disease, chronic pain, sleep disorder, depression, dysthymia, posttraumatic stress disorder (PTSD), general anxiety disorder, alcohol use disorder, other substance use disorder, and tobacco use disorder. Latent class analysis was used to identify latent profiles of psychiatric and medical comorbidity. Chi-square and F-tests were used to assess differences in demographics, comorbidities, and utilization across the latent classes. Results The cohort included 82,495 adults with schizophrenia. Three distinct multimorbidity classes were identified: Minimal Comorbidity (67.0% of the cohort), High Comorbidity (17.6%) and Substance Use Disorders and Related Conditions (SUDRC) (15.4%). The Minimal Comorbidity class had <10% prevalence of all comorbid diagnoses. The High Comorbidity class had >20% prevalence of congestive heart failure, COPD, dementia, renal disease, sleep disorder, and depression. The SUDRC class had >70% prevalence of alcohol and drug use disorders and >20% prevalence of COPD, hepatitis C, depression, and PTSD. Although the High Comorbidity class had the highest rates of chronic medical conditions, the SUDRC class had the highest rates of emergency and inpatient medical care and emergency, inpatient, and outpatient mental health care utilization. Comparing across classes, all p-values were <.001 for utilization. Conclusions Older adults with schizophrenia are a heterogeneous group with distinct multimorbidity classes and different patterns of utilization. Those with high prevalence of substance use disorders had the highest rates of emergency and inpatient medical and overall mental health care utilization. Tailoring integrated care services to target specific clinical needs could improve outcomes for this population. Disclosure of Interest None Declared

Andy Schang, Matthew Dew, Emily M. Stump et al.

Uncertainty is an important and fundamental concept in physics education. Students are often first exposed to uncertainty in introductory labs, expand their knowledge across lab courses, and then are introduced to quantum mechanical uncertainty in upper-division courses. This study is part of a larger project evaluating student thinking about uncertainty across these contexts. In this research, we investigate advanced physics student thinking about uncertainty by asking them conceptual questions about how a hypothetical distribution of measurements would change if `more' or `better' data were collected in four different experimental scenarios. The scenarios include both classical and quantum experiments, as well as experiments that theoretically result in an expected single value or an expected distribution. This investigation is motivated by our goal of finding insights into students' potential point- and set-like thinking about uncertainty and of shining light on the limitations of those binary paradigms.

Shabir Ahmad, Sabina Umirzakova, Ghulam Mujtaba et al.

We are currently in a post-pandemic era in which life has shifted to a digital world. This has affected many aspects of life, including education and learning. Education 5.0 refers to the fifth industrial revolution in education by leveraging digital technologies to eliminate barriers to learning, enhance learning methods, and promote overall well-being. The concept of Education 5.0 represents a new paradigm in the field of education, one that is focused on creating a learner-centric environment that leverages the latest technologies and teaching methods. This paper explores the key requirements of Education 5.0 and the enabling technologies that make it possible, including artificial intelligence, blockchain, and virtual and augmented reality. We analyze the potential impact of these technologies on the future of education, including their ability to improve personalization, increase engagement, and provide greater access to education. Additionally, we examine the challenges and ethical considerations associated with Education 5.0 and propose strategies for addressing these issues. Finally, we offer insights into future directions for the development of Education 5.0, including the need for ongoing research, collaboration, and innovation in the field. Overall, this paper provides a comprehensive overview of Education 5.0, its requirements, enabling technologies, and future directions, and highlights the potential of this new paradigm to transform education and improve learning outcomes for students.

José Luis Di Laccio, Andrés Monetta, Rodrigo Alonso-Suárez et al.

The global transition towards cleaner and more sustainable energy production is a major challenge. We present an innovative solution by utilizing smartphone light sensors to measure direct normal solar irradiance, the primary component of ground-level solar radiation. We provide comprehensive guidelines for calibrating the sensor using two methods: a professional reference measurement and clear-sky satellite estimates. The latter method is particularly advantageous in resource-constrained environments. Once calibrated, the smartphone becomes a valuable tool for measuring the solar resource. We propose an instructional laboratory focusing on the physics of solar radiation and its interaction with the Earth's atmosphere, exploring solar variations across locations, cloud conditions, and time scales. By integrating irradiance values measured throughout a day the daily irradiation can be estimated. This approach enhances students' understanding of solar radiation attenuation and its relationship with atmospheric interactions. This method offers a practical and educational solution for promoting renewable energy knowledge and addressing the challenges of the energy transition.

Jaromir Savelka, Arav Agarwal, Christopher Bogart et al.

We evaluated the capability of generative pre-trained transformers (GPT), to pass assessments in introductory and intermediate Python programming courses at the postsecondary level. Discussions of potential uses (e.g., exercise generation, code explanation) and misuses (e.g., cheating) of this emerging technology in programming education have intensified, but to date there has not been a rigorous analysis of the models' capabilities in the realistic context of a full-fledged programming course with diverse set of assessment instruments. We evaluated GPT on three Python courses that employ assessments ranging from simple multiple-choice questions (no code involved) to complex programming projects with code bases distributed into multiple files (599 exercises overall). Further, we studied if and how successfully GPT models leverage feedback provided by an auto-grader. We found that the current models are not capable of passing the full spectrum of assessments typically involved in a Python programming course (<70% on even entry-level modules). Yet, it is clear that a straightforward application of these easily accessible models could enable a learner to obtain a non-trivial portion of the overall available score (>55%) in introductory and intermediate courses alike. While the models exhibit remarkable capabilities, including correcting solutions based on auto-grader's feedback, some limitations exist (e.g., poor handling of exercises requiring complex chains of reasoning steps). These findings can be leveraged by instructors wishing to adapt their assessments so that GPT becomes a valuable assistant for a learner as opposed to an end-to-end solution.

Philippe Charlier, Philippe Charlier, Philippe Charlier et al.

Nur Asrawati, Sitti Fatimah Sangkala Sirate

This study aims to determine the increase in students' mathematical creativity through the auditory, intellectual, repetition (AIR) learning model in class XI students of SMK Techno Terapan Makassar. Creativity referred to in this study pays attention to 3 aspects of indicators, namely fluency, flexibility, and novelty. This research is research class action (PTK). The subjects of this study were students of class XI at SMK Techno Terapan Makassar. The results showed that there was an increase in creativity in learning mathematics through the auditory, intellectual, repetition (AIR) learning model. Student test results seen based on the percentage per indicator increased from cycle I to cycle II seen in the aspect of fluency 66.66% increasing to 81.48%, the aspect of flexibility 62.96% increasing to 77.78%, and the novelty aspect increasing 33.33% to 48.14%. the learning completeness criteria in cycle I was 55.55% and classically complete in cycle II was 77.77% or as many as 22 people who scored . Data from the analysis of teacher activity in cycle 1 increased by 60.42% to 72.90% while the results of student activity analysis in cycle 1 amounted to 56.26% increased to 70.92%. From the research results obtained, it can be concluded that the Auditory, Intellectual, Repetition (AIR) learning model can increase the mathematical creativity of class XI students of SMK Techno Terapan Makassar.

Rogerio Rossi, Pollyana Notargiacomo Mustaro

Digital solutions have substantially contributed to the growth and dissemination of education. The distance education modality has been presented as an opportunity for worldwide students in many types of courses. However, projects of digital educational platforms require different expertise including knowledge areas such as pedagogy, psychology, computing, and digital technologies associated with education that allow the correct development and application of these solutions. To support the evolution of such solutions with satisfactory quality indicators, this research presents a model focused on quality of online educational solutions grounded in an approach aimed to continuous process improvement. The model considers of three maturity levels and six common entities that address the specific practices for planning and developing digital educational solutions, targeting quality standards that satisfy their users, such as students, teachers, tutors, and other people involved in development and use of these kinds of educational solutions.