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Por Mercedes Leticia Sánchez Ambriz y Carlos Bravo Reyes En colaboración con la Dra Mercedes Leticia Sánchez venimos desarrollando el conce... Via LGA No comment yet.
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Juan Domingo Farnos El concepto de Diseño Universal de Aprendizaje (DUA) ha evolucionado a medida que la educación se ha transformado mediante el uso de tecnologías inteligentes y enfoques disruptivos. DUA 9, dentro del contexto de la educación disruptiva y la integración de IA (Inteligencia Artificial), presenta una visión innovadora de cómo personalizar y adaptar el aprendizaje en el ámbito…
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La tecnología, por sí sola, no transforma la educación. Son los docentes, con una sólida formación pedagógica y un uso estratégic
Via Yashy Tohsaku
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La IA generativa multimodal está cada vez más presenta, ahora los chatbots de IA no solo generan texto, también imágenes, vídeos, apps, etc.
Via Yashy Tohsaku
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From
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AI agents represent the next evolutionary leap beyond generative AI, capable of taking autonomous action rather than just responding to prompts. Via Yashy Tohsaku
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Juan Domingo Farnós En el vasto y desconocido horizonte de la educación, donde la era del conocimiento compartido y fragmentado se encuentra con las aguas de la tecnología, estamos al borde de una revolución que no solo reformula lo que significa aprender, sino también lo que significa ser humano en un ecosistema donde las máquinas…
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When we can show students that the extraordinary has a place in their online academic journey, educators can ignite a sense of awe, thus leading to elevated learning, collaboration, critical thinking, and ideas exchange. Via Vladimir Kukharenko
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This free comprehensive guide explores AI’s transformative role across industries, emphasizing the need for AI literacy to remain competitive.
Key sectors include healthcare, engineering, cybersecurity, marketing, and education, with insights into AI-driven automation, predictive analytics, and personalized experiences.
The author highlights essential skills for adapting to AI advancements while addressing ethical concerns and workforce implications. Via Ana Cristina Pratas
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Juan Domingo Farnos El seguimiento ocular, el procesamiento visual y el aprendizaje personalizado se integran de manera innovadora dentro de sistemas de IA, deep learning y redes neuronales, con un enfoque disruptivo en la educación superior. Utilizando tecnologías como el seguimiento ocular, podemos personalizar el aprendizaje, adaptando el contenido en tiempo real según las reacciones…
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From
mindmatters
Perhaps the AI apocalypse will paradoxically encourage educators to adopt more traditional approaches to teaching and giving assignments. Via EDTECH@UTRGV 
EDTECH@UTRGV's curator insight,
March 24, 1:59 PM
"Psychologist Jordan Peterson, in one of his older recorded lectures in his own classroom, extols the importance of learning how to write. 'The best way to teach people critical thinking is to teach them to write'”
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In a historic move, the Computer History Museum, in partnership with Google, has released the original 2012 source code for AlexNet, the neural network that revolutionized AI.
Developed by Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton, AlexNet's source code release is a monumental moment for AI enthusiasts. Via Tony Shan
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Discover how Generative AI can enhance student competency through the assessment flywheel model, providing personalized feedforward comments and automating low-stakes formative assessments for deeper learning. Via Vladimir Kukharenko |
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![[Google Drive] Inteligencia Artificial en la Educación | E-Learning-Inclusivo (Mashup) | Scoop.it](https://img.scoop.it/ajAF4MNDCjStwNAainecpjl72eJkfbmt4t8yenImKBVvK0kTmF0xjctABnaLJIm9)
From
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La presente guía sobre Inteligencia Artificial (IA) en educación está Via Edumorfosis
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Por Lorenzo García Aretio Pues ya está. La semana pasada cumplí mis 80 años y, al menos hasta ahora, sigo con alguna fuerza y ganas par Via LGA
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"The emergence of the augmented mind is not a futuristic speculation – it is the new condition of learning. It calls for a paradigm shift in how ..." Via Leona Ungerer, Ricard Lloria
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This article explores AI's historical evolution, critically assesses its benefits and challenges for teaching, and provides evidence-based strategies for faculty to integrate AI effectively. Via Vladimir Kukharenko
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Juan Domingo Farnós La propuesta de Juan Domingo Farnós sobre educación disruptiva e inteligencia artificial redefine los paradigmas educativos al integrar enfoques transdisciplinarios, multimodales y adaptativos. La "hermenéutica algorítmica" se alinea perfectamente con este marco, utilizando tecnologías avanzadas como procesamiento del lenguaje natural (NLP), visión computacional, y redes neuronales profundas para analizar patrones cognitivos y personalizar el aprendizaje. A continuación, se…
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If we were to design higher education from scratch in an AI-driven world, would it look anything like what we have now? Via Edumorfosis
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Although I often share about the beneficial ways AI can help educators and students, I also focus on the potential concerns about AI i
Via Yashy Tohsaku
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Juan Domingo Farnos La educación superior se encuentra en un punto de inflexión sin precedentes. La microcredencial en formación superior continuada en educación disruptiva & IA en educación superior surge como una respuesta audaz y desafiante a los sistemas académicos tradicionales, esos mismos que se han estancado en estructuras rígidas y metodologías obsoletas. En un…
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For eLearning to be effective, include clear learning objectives. Here are some useful tips to set effective learning objectives for your eLearning courses. Via CommLab India
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From
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As artificial intelligence (AI) becomes increasingly integrated into various fields, the need to enhance learners’ AI literacy is more urgent than ever. Despite its growing importance, a comprehensive review of AI literacy education research has been lacking. This study addresses that gap by mapping the current landscape, tracing its evolution, and identifying key themes through a bibliometric analysis of research from 2014 to 2024, utilizing CiteSpace for data visualization and analysis. This study systematically selected 335 relevant articles from databases, including Web of Science Core Collection, Scopus, and Science Direct, following PRISMA guidelines. Our methodology involved keyword co-occurrence mapping to trace the development paths and thematic evolution within the field. By examining publication trends and thematic clusters, we provide insights into the progression and focal points of AI literacy education research over the past decade. The study reveals three key insights. First, AI literacy education research has shifted from an exploratory phase to rapid growth, with a marked increase in publications. Second, four distinct developmental trajectories have emerged, emphasizing the interdisciplinary nature of the field and its connections to information, digital, and algorithmic literacy. Third, nine prominent research themes have been identified, with data literacy, machine learning, AI literacy, the technology acceptance model, and computational thinking as focal points. These themes highlight AI’s evolving role, particularly in education, and shifts in research priorities. This review provides a comprehensive understanding of AI literacy education’s evolution and its implications for education, ethics, and society. As AI continues to influence modern education and industry, this analysis serves as a valuable resource for researchers, educators, and policymakers navigating the complex intersection of AI and literacy. Via EDTECH@UTRGV
EDTECH@UTRGV's curator insight,
March 24, 1:56 PM
"This study maps the evolution of AI literacy education from 2014 to 2024, revealing key themes, growth trends, and interdisciplinary trajectories through a bibliometric analysis of 335 research articles."
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As AI literary becomes an essential work skill, universities need to move beyond developing these competencies at ‘primary school’ level in their students. Here, Fun Siong Lim reflects on frameworks to support higher-order AI literacies Via Vladimir Kukharenko
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Juan Domingo Farnos Veremos que este ecosistema emergente, el aprendizaje se define no solo por la transmisión del conocimiento, sino por la transcendencia epistemológica que surge de la hiperconexión cognitiva entre agentes humanos y no humanos. Los algoritmos de metaconstrucción (o metaheurísticos de construcción) son técnicas de optimización utilizadas para resolver problemas complejos, especialmente cuando… |
