Hasil untuk "Special aspects of education"

Leanna Woods, Kayley Lyons, Anton Van Der Vegt et al.

Abstract Background Artificial intelligence (AI) is increasingly integrated into healthcare, yet upskilling the health workforce remains a challenge. We addressed the research question: What evidence exists on the effectiveness of AI education and training programs in improving AI literacy among healthcare workers? Methods Following PRISMA guidelines and PROSPERO registration, five databases (PubMed, Scopus, CINAHL, Embase, ERIC) were searched on 20 August 2024, focusing on studies with an intervention of AI training or education for the healthcare workforce, in any study design that reported an evaluation. Results 27 studies were included. Programs improved AI literacy outcomes mapped to levels 1–3 of the Kirkpatrick-Barr training evaluation hierarchy including improved learner reactions, shifts in attitudes and perceptions, enhanced knowledge and skills, and behavior changes. Programs did not map to level 4, where healthcare workers learn to metacognition levels, including organizational change and patient benefit. Programs were short in length (44%), delivered in academic settings (56%), to doctors (44%) or medical students (44%), at entry-to-practice level (56%). Most taught an introduction to AI (67%), with technical AI skills less frequent. Conclusions These programs are a promising start but often lack sufficient depth to build advanced competencies. Improving AI literacy in healthcare will require appropriate course design, an evolving understanding of this rapidly changing area, and evaluating learning effectiveness. As the adoption of AI accelerates across healthcare, health systems may seek to standardise and assess the efficacy of these courses.

Nong Ming, Sachin Sharma, Jiho Noh

Questioning is a fundamental aspect of education, as it helps assess students' understanding, promotes critical thinking, and encourages active engagement. With the rise of artificial intelligence in education, there is a growing interest in developing intelligent systems that can automatically generate and answer questions and facilitate interactions in both virtual and in-person education settings. However, to develop effective AI models for education, it is essential to have a fundamental understanding of questioning. In this study, we created the YouTube Learners' Questions on Bloom's Taxonomy Dataset (YouLeQD), which contains learner-posed questions from YouTube lecture video comments. Along with the dataset, we developed two RoBERTa-based classification models leveraging Large Language Models to detect questions and analyze their cognitive complexity using Bloom's Taxonomy. This dataset and our findings provide valuable insights into the cognitive complexity of learner-posed questions in educational videos and their relationship with interaction metrics. This can aid in the development of more effective AI models for education and improve the overall learning experience for students.

Yuhan He

This study examines the influence of employee education and health on firm-level Total Factor Productivity (TFP) in China, using panel data from A-share listed companies spanning from 2007 to 2022. The analysis shows that life expectancy and higher education have a significant impact on TFP. More optimal health conditions can result in increased productivity through decreased absenteeism and improved work efficiency. Similarly, higher levels of education can support technological adaptation, innovation, and managerial efficiency. Nevertheless, the correlation between health and higher education indicates that there may be a point where further improvements in health yield diminishing returns in terms of productivity for individuals with advanced education. These findings emphasise the importance of implementing comprehensive policies that improve both health and education, maximising their impact on productivity. This study adds to the current body of research by presenting empirical evidence at the firm-level in China. It also provides practical insights for policymakers and business leaders who want to improve economic growth and competitiveness. Future research should take into account wider datasets, more extensive health metrics, and delve into the mechanisms that contribute to the diminishing returns observed in the relationship between health and education.

Talha Enes Ayranci, Florent P. Audonnet, Gerardo Aragon-Camarasa et al.

Student engagement is one of the key challenges in robotics and artificial intelligence (AI) education. Tangible learning approaches, such as educational robots, provide an effective way to enhance engagement and learning by offering real-world applications to bridge the gap between theory and practice. However, existing platforms often face barriers such as high cost or limited capabilities. In this paper, we present Curio, a cost-effective, smartphone-integrated robotics platform designed to lower the entry barrier to robotics and AI education. With a retail price below $50, Curio is more affordable than similar platforms. By leveraging smartphones, Curio eliminates the need for onboard processing units, dedicated cameras, and additional sensors while maintaining the ability to perform AI-based tasks. To evaluate the impact of Curio on student engagement, we conducted a case study with 20 participants, where we examined usability, engagement, and potential for integrating into AI and robotics education. The results indicate high engagement and motivation levels across all participants. Additionally, 95% of participants reported an improvement in their understanding of robotics. Findings suggest that using a robotic system such as Curio can enhance engagement and hands-on learning in robotics and AI education. All resources and projects with Curio are available at trycurio.com.

Kristian A. Groth, A. Skakkebæk, Christian Høst et al.

Chris Davis Jaldi, Eleni Ilkou, Noah Schroeder et al.

Education is poised for a transformative shift with the advent of neurosymbolic artificial intelligence (NAI), which will redefine how we support deeply adaptive and personalized learning experiences. NAI-powered education systems will be capable of interpreting complex human concepts and contexts while employing advanced problem-solving strategies, all grounded in established pedagogical frameworks. This will enable a level of personalization in learning systems that to date has been largely unattainable at scale, providing finely tailored curricula that adapt to an individual's learning pace and accessibility needs, including the diagnosis of student understanding of subjects at a fine-grained level, identifying gaps in foundational knowledge, and adjusting instruction accordingly. In this paper, we propose a system that leverages the unique affordances of pedagogical agents -- embodied characters designed to enhance learning -- as critical components of a hybrid NAI architecture. To do so, these agents can thus simulate nuanced discussions, debates, and problem-solving exercises that push learners beyond rote memorization toward deep comprehension. We discuss the rationale for our system design and the preliminary findings of our work. We conclude that education in the era of NAI will make learning more accessible, equitable, and aligned with real-world skills. This is an era that will explore a new depth of understanding in educational tools.

Basileal Imana, Aleksandra Korolova, John Heidemann

Digital ads on social-media platforms play an important role in shaping access to economic opportunities. Our work proposes and implements a new third-party auditing method that can evaluate racial bias in the delivery of ads for education opportunities. Third-party auditing is important because it allows external parties to demonstrate presence or absence of bias in social-media algorithms. Education is a domain with legal protections against discrimination and concerns of racial-targeting, but bias induced by ad delivery algorithms has not been previously explored in this domain. Prior audits demonstrated discrimination in platforms' delivery of ads to users for housing and employment ads. These audit findings supported legal action that prompted Meta to change their ad-delivery algorithms to reduce bias, but only in the domains of housing, employment, and credit. In this work, we propose a new methodology that allows us to measure racial discrimination in a platform's ad delivery algorithms for education ads. We apply our method to Meta using ads for real schools and observe the results of delivery. We find evidence of racial discrimination in Meta's algorithmic delivery of ads for education opportunities, posing legal and ethical concerns. Our results extend evidence of algorithmic discrimination to the education domain, showing that current bias mitigation mechanisms are narrow in scope, and suggesting a broader role for third-party auditing of social media in areas where ensuring non-discrimination is important.

Mine Dogucu, Sinem Demirci, Harry Bendekgey et al.

The presence of data science has been profound in the scientific community in almost every discipline. An important part of the data science education expansion has been at the undergraduate level. We conducted a systematic literature review to (1) portray current evidence and knowledge gaps in self-proclaimed undergraduate data science education research and (2) inform policymakers and the data science education community about what educators may encounter when searching for literature using the general keyword 'data science education.' While open-access publications that target a broader audience of data science educators and include multiple examples of data science programs and courses are a strength, significant knowledge gaps remain. The undergraduate data science literature that we identified often lacks empirical data, research questions and reproducibility. Certain disciplines are less visible. We recommend that we should (1) cherish data science as an interdisciplinary field; (2) adopt a consistent set of keywords/terminology to ensure data science education literature is easily identifiable; (3) prioritize investments in empirical studies.

Cíntia Guirra da Cruz, Maryluce Albuquerque da Silva Campos , Luciana Freitas de Oliveira França et al.

A presente pesquisa visa analisar a presença do tema educação ambiental (EA) nos Projetos Políticos Pedagógicos (PPP) das escolas do ensino fundamental II, no município de Campo Formoso-BA, com o intuito de investigar se os PPP’s das Escolas contemplam a temática da Educação Ambiental, desde a construção de seus conceitos, concepções e metodologias até as ações desenvolvidas pelos professores por meio da práxis educativa. Este trabalho de pesquisa adota uma abordagem qualitativa utilizando técnica documental por meio da análise dos Projetos Políticos Pedagógicos de quatro Escolas do Município de Campo Formoso/BA. O método científico utilizado foi o indutivo, com o objetivo de identificar os padrões e tendências das informações coletadas. Foi verificado que apenas uma escola contempla o tema EA, constando no PPP desta escola alguns projetos voltados para o tema, bem como referências. Os demais PPPs analisados não contemplam uma visão sobre a temática ambiental, nem mesmo como tema transversal, como prevê os PCNs. Para a viabilização da implantação da Educação Ambiental como tema transversal no Projeto Político Pedagógico se faz necessário abrir uma discussão mais abrangente e ao mesmo tempo mais aprofundada com os mais diversos atores educacionais, sendo um desafio a ser enfrentado pelos gestores escolares na elaboração de seus Projetos Políticos Pedagógicos no âmbito escolar, juntamente com a comunidade que auxilia neste processo.

Cecilia Ka Yuk Chan, Louisa H. Y. Tsi

This paper explores the potential of artificial intelligence (AI) in higher education, specifically its capacity to replace or assist human teachers. By reviewing relevant literature and analysing survey data from students and teachers, the study provides a comprehensive perspective on the future role of educators in the face of advancing AI technologies. Findings suggest that although some believe AI may eventually replace teachers, the majority of participants argue that human teachers possess unique qualities, such as critical thinking, creativity, and emotions, which make them irreplaceable. The study also emphasizes the importance of social-emotional competencies developed through human interactions, which AI technologies cannot currently replicate. The research proposes that teachers can effectively integrate AI to enhance teaching and learning without viewing it as a replacement. To do so, teachers need to understand how AI can work well with teachers and students while avoiding potential pitfalls, develop AI literacy, and address practical issues such as data protection, ethics, and privacy. The study reveals that students value and respect human teachers, even as AI becomes more prevalent in education. The study also introduces a roadmap for students, teachers, and universities. This roadmap serves as a valuable guide for refining teaching skills, fostering personal connections, and designing curriculums that effectively balance the strengths of human educators with AI technologies. The future of education lies in the synergy between human teachers and AI. By understanding and refining their unique qualities, teachers, students, and universities can effectively navigate the integration of AI, ensuring a well-rounded and impactful learning experience.

Mursal Dawodi, Jawid Ahmad Baktash, Sayed Mohammad Reza Dawodi

The educational landscape of Afghanistan, besieged by infrastructural inadequacies and socio-political tribulations, presents a compelling case for the integration of mobile learning platforms. This article embarks on an exploratory voyage into the realms of mobile learning as a potential harbinger of educational transformation in Afghanistan. It delineates the pervasive educational challenges, underscores the technological innovations powering mobile learning platforms, and illuminates the pathways through which mobile learning can transcend the extant barriers to education. Enriched by real-world case studies, the narrative unravels the pragmatic lessons that can be harnessed to tailor mobile learning solutions to Afghanistan's unique context. The discussion further traverses the collaborative horizon, elucidating the synergistic interplay among academia, government, the private sector, and international bodies essential for the successful implementation of mobile learning platforms. The article also furnishes pragmatic recommendations, emphasizing the triad of policy formulation, infrastructure enhancement, and capacity building as cornerstone imperatives. The envisioned integration of mobile learning platforms augurs a paradigmatic shift towards a more accessible, inclusive, and resilient educational framework in Afghanistan, with far-reaching implications for socio-economic development. Through a meticulous amalgamation of technology, policy, and collaborative endeavors, this article posits that Afghanistan stands on the cusp of an educational renaissance, with mobile learning platforms serving as a pivotal conduit toward this envisioned horizon.

Equipe Editorial

King J, Taylor J

Jalysa King, Jennifer Taylor Department of Family Medicine, Indiana University School of Medicine, Indianapolis, IN, USACorrespondence: Jennifer Taylor, Email jtaylor8@iu.eduBackground and Objectives: With the ever-growing diversity within our communities, it is imperative that we integrate social determinants of health (SDOH) such as racial disparity, economic instability, lack of transportation, intimate partner violence, and limited social supports, and the importance of health literacy into undergraduate medical education. By incorporating evidence-based curriculum on the disproportionality within healthcare faced by racial and ethnic minorities, we have the opportunity to develop more culturally sensitive providers. The purpose of this study was to assess the impact of a case-based debrief experience on medical students’ knowledge about how social determinants of health can impact health and healthcare within a family medicine clinical setting and their intent to practice in an underserved community.Methods: We utilized a retrospective paired-sample t-test analysis of program data from 640 third-year medical students who engaged in a family medicine clerkship between July 2020, and April 2022. For inclusion in the study, students must have engaged in a case-based exercise and corresponding small group debrief around the impact of social determinants of health on patient care.Results: We found a statistically significant improvement in students’ reported knowledge about SDOH, as well as the confidence and intent to work with and care for individuals of diverse cultural and socioeconomic backgrounds.Conclusion: Medical students must have the knowledge and self-efficacy to understand how social determinants of health can impact health and healthcare within a family medicine clinical setting. As a result of integrating more active learning strategies such as the case-base and debrief experience, students may have a more robust medical education experience.Keywords: social determinants of health, problem-based learning, vulnerable populations, education, medical, patient care

Nikolche Vasilevski, James R. Birt

Mixed reality (MR) and mobile visualisation methods have been identified as important technologies that could reimagine spatial information delivery and enhance higher education practice. However, there is limited research on the impact of mobile MR (MMR) within construction education and improvement of the learners’ experience. With new building information modelling (BIM) workflows being adopted within the architecture, engineering and construction industry, innovative MMR pedagogical delivery methods should be explored to enhance this information-rich spatial technology workflow. This paper outlines qualitative results derived through thematic analysis of learner reflections from two technology-enhanced lessons involving a lecture and a hands-on workshop focussed on MMR-BIM delivered within postgraduate construction education. Seventy participants across the two lessons recruited from an Australian university participated to answer the research question: ‘Does applied mobile mixed reality create an enhanced learning environment for students?’ The results of the analysis suggest that using MMR-BIM can result in an enhanced learning environment that facilitates unique learning experiences, engagement and motivation. However, the study outcome suggests that to understand the processes leading to these learning aspects, further empirical research on the topic is required. This paper is part of the special collection Mobile Mixed Reality Enhanced Learning edited by Thom Cochrane, James Birt, Helen Farley, Vickel Narayan and Fiona Smart. More papers from this collection can be found here.

Hui Han, Silvana Trimi

Cloud computing has become the infrastructure that supports people's daily activities, business operations, and education delivery around the world. Cloud computing-based education platforms have been widely applied to assist online teaching during the COVID-19 pandemic. This paper examines the impact and importance of cloud computing in remote learning and education. This study conducted multiple-case analyses of 22 online platforms of higher education in Chinese universities during the epidemic. A comparative analysis of the 22 platforms revealed that they applied different cloud computing models and tools based on their unique requirements and needs. The study results provide strategic insights to higher education institutions regarding effective approaches to applying cloud computing-based platforms for remote education, especially during crisis situations.

Koby Mike, Orit Hazzan

Machine learning (ML) algorithms are gaining increased importance in many academic and industrial applications, and such algorithms are, accordingly, becoming common components in computer science curricula. Learning ML is challenging not only due to its complex mathematical and algorithmic aspects, but also due to a) the complexity of using correctly these algorithms in the context of real-life situations and b) the understanding of related social and ethical issues. Cognitive biases are phenomena of the human brain that may cause erroneous perceptions and irrational decision-making processes. As such, they have been researched thoroughly in the context of cognitive psychology and decision making; they do, however, have important implications for computer science education as well. One well-known cognitive bias, first described by Kahneman and Tversky, is the base rate neglect bias, according to which humans fail to consider the base rate of the underlying phenomena when evaluating conditional probabilities. In this paper, we explore the expression of the base rate neglect bias in ML education. Specifically, we show that about one third of students in an Introduction to ML course, from varied backgrounds (computer science students and teachers, data science, engineering, social science and digital humanities), fail to correctly evaluate ML algorithm performance due to the base rate neglect bias. This failure rate should alert educators and promote the development of new pedagogical methods for teaching ML algorithm performance.

Pedro P. Ladeira, Leandro M. de Lima, Renato A. Krohling

Through the analysis of cultural, socioeconomic and academic performance aspects it is possible to map the profile of the students and their motivations to drop out. This article aims to create a computational tool for data visualization that allows drawing the profile of students to support educational institutions managers in the definition of dropout avoidance policies. We present a method to treat data collected by higher education institutions over the years, analyze them to understand the dropout and provide that information to the university and the general public. Eight questions were proposed to clarify the dropout from the Federal University of Espírito Santo, Brazil. The questions were answered through the dashboard that helps to understand the causes of dropout. It is expected that this tool can be used by others educational institutions to draw student profiles contributing to possible resolution of the problem.

Mohit Singh, Yoav Tsori

Anisotropic particles oriented in a specific direction can act as artificial atoms and molecules, and their controlled assembly can result in a wide variety of ordered structures. Towards this, we demonstrate the orientation transitions of uncharged peanut-shaped polystyrene colloids, suspended in a non-ionic aprotic polar solvent, near a flat surface whose potential is static or time-varying. The charged surface is coated with an insulating dielectric layer to suppress electric currents. The transition between several orientation states such as random, normal or parallel orientation with respect to the surface, is examined for two different colloid sizes at low-frequency ($\sim 10-350$ kHz) or static fields, and at small electric potentials. In time-varying (AC) field, a detailed phase diagram in the potential-frequency plane indicating the transition between particles parallel or normal to the surface is reported. We next present the first study of orientation switching in static (DC) fields, where no electro-osmotic or other flow is present. A reversible change between the two colloidal states is explained by a theory showing that the sum of electrostatic and gravitational energies of the colloid is bistable. The number of colloids in each of the two states depends on the external potential, particle and solvent permittivities, particle aspect ratio, and distance from the electrode.

José Geovanny Boza Mendoza, Danilo Charchabal Pérez

Introducción: Los contenidos reflejados en este artículo sobre las actividades lúdicas posibilitaron la optimización de las habilidades motrices básicas en las clases de Educación Física, donde se incluyen actividades variadas que facilitaran mejorar los movimientos motrices de los sujetos motivo de estudio.  Objetivo: validar un sistema de actividades lúdicas para perfeccionar los movimientos motrices básicos en los estudiantes de 6to. grado del colegio Alemán Humboldt Guayaquil. Materiales y métodos: La investigación es de tipo descriptiva-correlacional, estudiando dos grupos independientes (Grupo Control: diez estudiantes: y Grupo Experimental: diez estudiantes), manteniendo el proceso tradicional de participación en actividades lúdicas al grupo de control e implementando la nueva variante de un sistema de actividades lúdicas al grupo experimental. Previamente se realizó una validación teórica de la propuesta de intervención con 15 especialistas nacionales e internacionales, valorando cuatro indicadores de análisis (Validez “V”; Integralidad “I”; Asequibilidad “A”; Variedad “Va”). Resultados: Una vez analizado cada indicador de estudio, la Prueba W de Kendall evidenció un nivel de concordancia entre especialistas de Nivel Alto (w=0.376), existiendo diferencias significativas en el puntaje individual alcanzado por cada indicador de análisis. El nivel de Significación asintótica (p=0.001˂0.05), demuestra un alto nivel de concordancia entre los especialistas sobre las cualidades del sistema de actividades lúdicas. Conclusiones: Se concluye que el sistema de actividades lúdicas propuesto para el desarrollo de las habilidades motrices básicas, es pertinente y deben extender su aplicación a otros grupos clases de Educación Física.

Julius Berner, Philipp Grohs, Gitta Kutyniok et al.

We describe the new field of mathematical analysis of deep learning. This field emerged around a list of research questions that were not answered within the classical framework of learning theory. These questions concern: the outstanding generalization power of overparametrized neural networks, the role of depth in deep architectures, the apparent absence of the curse of dimensionality, the surprisingly successful optimization performance despite the non-convexity of the problem, understanding what features are learned, why deep architectures perform exceptionally well in physical problems, and which fine aspects of an architecture affect the behavior of a learning task in which way. We present an overview of modern approaches that yield partial answers to these questions. For selected approaches, we describe the main ideas in more detail.