Hasil untuk "Education"

Ian Westbury

C. Strickland

N. Noddings

G. Duncan, S. Hoffman

R. Harden, S. Sowden, W. Dunn

Martinek Milan, Zapletal Jan, Drochytek Vit et al.

Abstract The Vojta’s method (VRL) is a neurophysiological rehabilitation method used to support and induce reflex responses of locomotor and vegetative systems. It uses involuntary motor reaction of the body during pressure stimulation of so-called trigger zones. Pregnancy is currently considered a contraindication for the use of VRL due to the potential risk of inducing regular uterine activity and, consequently, triggering labor. The aim of the study is to evaluate changes in uterine activity during Vojta’s reflex locomotion and to determine whether the method is associated with the induction of labor. Secondary goal is to assess its safety in term pregnancy and its potential use for rehabilitative purposes. This single-center, single-blinded, parallel-group randomized controlled pilot trial included 40 pregnant patients between 40 + 0 to 41 + 0 weeks of gestational age. Participants were randomized (sealed envelope method) to receive either stimulation of trigger zones according to VRL (n = 20) or sham stimulation (n = 20). Cardiotocographic (CTG) recordings were conducted right before and immediately after stimulation and evaluated by two independent obstetricians. Additionally, participants completed a questionnaire evaluating subjective responses to stimulation. Primary outcomes were CTG-detected uterine changes and time from stimulation to delivery. Secondary outcomes included self-reported sensations and pain intensity (VAS). None of the patients delivered as a result of VRL stimulation. CTG showed increased uterine activity in 45% of VRL stimulated participants vs. 10% in the control group. Median time to labor onset in the VRL group was 5 days (1–8), compared to 4 days (1–9) in the control group. VRL was well tolerated (mean VAS 1.85), but rated significantly less pleasant than sham (p = 0.043). Our findings suggest that the use of VRL in term pregnancy is likely safe and well tolerated. While uterine activity was observed in 45% of cases, this activity was not sufficient to induce labor. Our findings, however, do not support pregnancy as a blanket contraindication. Trial registration: This clinical trial was registered at http://clinicaltrials.gov (ID: NCT06339528).

M. Ainscow, R. Slee, Marnie Best

ABSTRACT June 2019 saw the 25th anniversary of the World Conference on Special Needs Education, which was co-organized by UNESCO and the Ministry of Education and Science of Spain, and held in the city of Salamanca. It led to the Salamanca Statement and Framework for Action on Special Needs Education, arguably the most significant international document that has ever appeared in the field of special education. In so doing, it endorsed the idea of inclusive education, which was to become a major influence in subsequent years. The articles in this special issue illustrate the ways in which the Salamanca Statement has and still is influencing the development of policies and practices across the world. In this editorial, we provide readers with some relevant background to these developments.

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.

Zaid M. Altukhi, Sojen Pradhan

Explainable AI (XAI) seeks to transform black-box algorithmic processes into transparent ones, enhancing trust in AI applications across various sectors such as education. This review aims to examine the various definitions of XAI within the literature and explore the challenges of XAI in education. Our goal is to shed light on how XAI can contribute to enhancing the educational field. This systematic review, utilising the PRISMA method for rigorous and transparent research, identified 19 relevant studies. Our findings reveal 15 definitions and 62 challenges. These challenges are categorised using thematic analysis into seven groups: explainability, ethical, technical, human-computer interaction (HCI), trustworthiness, policy and guideline, and others, thereby deepening our understanding of the implications of XAI in education. Our analysis highlights the absence of standardised definitions for XAI, leading to confusion, especially because definitions concerning ethics, trustworthiness, technicalities, and explainability tend to overlap and vary.

Sasa Maric, Sonja Maric, Lana Maric

The AI revolution is gathering momentum at an unprecedented rate. Over the past decade, we have witnessed a seemingly inevitable integration of AI in every facet of our lives. Much has been written about the potential revolutionary impact of AI in education. AI has the potential to completely revolutionise the educational landscape as we could see entire courses and degrees developed by programs such as ChatGPT. AI has the potential to develop courses, set assignments, grade and provide feedback to students much faster than a team of teachers. In addition, because of its dynamic nature, it has the potential to continuously improve its content. In certain fields such as computer science, where technology is continuously evolving, AI based applications can provide dynamically changing, relevant material to students. AI has the potential to replace entire degrees and may challenge the concept of higher education institutions. We could also see entire new disciplines emerge as a consequence of AI. This paper examines the practical impact of ChatGPT and why it is believed that its implementation is a critical step towards a new era of education. We investigate the impact that ChatGPT will have on learning, problem solving skills and cognitive ability of students. We examine the positives, negatives and many other aspects of AI and its applications throughout this paper.

Ishaan Masilamony

In recent years, ChatGPT \cite{openai_2023_gpt4} along with Microsoft Copilot have become subjects of great discourse, particularly in the field of education. Prior research has hypothesized on potential impacts these tools could have on student learning and performance. These have primarily relied on trends from prior applications of technology in education and an understanding of the limitations and strengths of Generative AI in other applications. This study utilizes an experimental approach to analyze the impacts of Generative AI on high school STEM education (physics in particular). In accordance with most findings, generative AI does have some positive impact on student performance. However, our findings have shown that the most significant impact is an increase in student engagement with the subject.

Martin Nizon-Deladoeuille, Brynjólfur Stefánsson, Helmut Neukirchen et al.

Cybersecurity education is challenging and it is helpful for educators to understand Large Language Models' (LLMs') capabilities for supporting education. This study evaluates the effectiveness of LLMs in conducting a variety of penetration testing tasks. Fifteen representative tasks were selected to cover a comprehensive range of real-world scenarios. We evaluate the performance of 6 models (GPT-4o mini, GPT-4o, Gemini 1.5 Flash, Llama 3.1 405B, Mixtral 8x7B and WhiteRabbitNeo) upon the Metasploitable v3 Ubuntu image and OWASP WebGOAT. Our findings suggest that GPT-4o mini currently offers the most consistent support making it a valuable tool for educational purposes. However, its use in conjonction with WhiteRabbitNeo should be considered, because of its innovative approach to tool and command recommendations. This study underscores the need for continued research into optimising LLMs for complex, domain-specific tasks in cybersecurity education.

Raphael Fischer, Youssef Abdelrahim, Katharina Poitz

Generative artificial intelligence (GenAI) presents both challenges and opportunities across all areas of education. Facing the municipal elections in North Rhine-Westphalia, the Young AI Leaders in Dortmund asked themselves: Could GenAI be used to make political programs more accessible, in order to facilitate political education? To explore respective potentials and limitations, we therefore performed an experimental study that combines different GenAI approaches. Language models were used to automatically translate and analyze the contents of each program, deriving five potential visual appearance changes to the city of Dortmund. Based on each analysis, we then generated images with diffusion models and published all results as an interactive webpage. All GenAI models were locally deployed on a Dortmund-based computing cluster, allowing us to also investigate environmental impacts. This manuscript explores the project in full depth, discussing technical details and critically reflecting on the results. As part of the global Young AI Leaders Community, our work promotes the Sustainable Development Goal Quality Education (SDG 4) by transparently discussing the pros and cons of using GenAI for education and political agendas.

Jaya Shivangani Kashyap, Robert Devaty, Chandralekha Singh

The electrostatic potential in certain types of boundary value problems can be found by solving Laplace's Equation (LE). To develop students' ability for solving problems that can be solved effectively using Laplace's equation in an upper-level electricity and magnetism course, we developed and validated a tutorial focused on finding electrostatic potential in a Cartesian coordinate system. The tutorial was implemented across three instructors' classes, accompanied by scaffolded pretest and posttest. We also conducted think-aloud interviews with advanced students using both unscaffolded and scaffolded versions of the pretest and posttest. Findings reveal common student difficulties that were included in the tutorial as a guide to help address them. The difference in the performance of students from the pretest to the posttest was similar on the scaffolded version of the tests for all three instructors' classes and interviewed students. Equally importantly, interviewed students demonstrated greater differences in scores from the pretest and posttest on the unscaffolded versions, suggesting that the scaffolded version of the tests may have obscured evidence of actual learning from the tutorial. While a scaffolded test is typically intended to guide students through complex reasoning by breaking a problem into sub-problems and offering structured support, it can limit opportunities to demonstrate independent problem-solving and evidence of learning from the tutorial. Additionally, one instructor's class underperformed relative to others even on the pretest. This instructor had mentioned that the tests and tutorial were not relevant to their current course syllabus and offered a small amount of extra credit for attempting to help education researchers, highlighting how this type of instructor framing of instructional tasks can negatively impact student engagement and performance.

Janice Mak, Joyce Nakatumba-Nabende, Tony Clear et al.

Generative AI (GenAI) presents societal and ethical challenges related to equity, academic integrity, bias, and data provenance. In this paper, we outline the goals, methodology and deliverables of their collaborative research, considering the ethical and societal impacts of GenAI in higher computing education. A systematic literature review that addresses a wide set of issues and topics covering the rapidly emerging technology of GenAI from the perspective of its ethical and societal impacts is presented. This paper then presents an evaluation of a broad international review of a set of university adoption, guidelines, and policies related to the use of GenAI and the implications for computing education. The Ethical and Societal Impacts-Framework (ESI-Framework), derived from the literature and policy review and evaluation, outlines the ethical and societal impacts of GenAI in computing education. This work synthesizes existing research and considers the implications for computing higher education. Educators, computing professionals and policy makers facing dilemmas related to the integration of GenAI in their respective contexts may use this framework to guide decision-making in the age of GenAI.

M. Mcallister, J. McKinnon

A. Howe, A. Smajdor, A. Stöckl

Ana Cecília Chaves Silva, Alex Rocha

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Sourojit Ghosh, Sarah Coppola

Traditional and currently-prevalent pedagogies of design perpetuate ableist and exclusionary notions of what it means to be a designer. In this paper, we trace such historically exclusionary norms of design education, and highlight modern-day instances from our own experiences as design educators in such epistemologies. Towards imagining a more inclusive and sustainable future of design education, we present three case studies from our own experience as design educators in redesigning course experiences for blind and low-vision (BLV), deaf and hard-of-hearing (DHH) students, and students with other disabilities. In documenting successful and unsuccessful practices, we imagine what a pedagogy of care in design education would look like.