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onto E-Learning-Inclusivo (Mashup) June 12, 8:48 AM
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Discover top AI tools for creating blended learning formats for maximum learner engagement. Enhance corporate training programs for 10x results.
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![]() La Inteligencia Artificial facilita evaluaciones personalizadas, motiva a los estudiantes y genera mejores herramientas pedagógicas. Las instituciones tienen la obligación de evolucionar Via Mariano Ramos Mejia
![]() Discover top AI tools for creating blended learning formats for maximum learner engagement. Enhance corporate training programs for 10x results. Via CommLab India
![]() Blog de la "RIED. Revista Iberoamericana de Educación a Distancia". La Revista Iberoamericana de la Educación Digital. Via LGA
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From
www
Two studies indicate students are using chatbots in a way that undermines what they learn. Via EDTECH@UTRGV
EDTECH@UTRGV's curator insight,
June 11, 12:30 PM
"The two studies were conducted by a team of international researchers who studied how Chinese students were using ChatGPT to help with English writing, and by researchers at Anthropic, the company behind the AI chatbot Claude. They both come to a similar conclusion: Many students are letting AI do important brain work for them."
![]() The 2025 EDUCAUSE Horizon Report profiles key trends and emerging technologies and practices shaping the future of teaching and learning, and envision Via Peter Mellow, Dennis Swender
![]() Juan Domingo Farnos RESUMEN: La integración de la perspectiva educativa con IA en la propuesta de nuevos hardware y materiales avanzados se centra en la creación de un ecosistema disruptivo que fusiona la personalización radical del aprendizaje con la optimización energética. Mediante el uso de chips neuromórficos y tecnologías de computación cuántica, se establece una…
![]() Juan Domingo Farnos El marco en el me voy a mover no es una mera concatenación de innovaciones, sino un tapiz articulado de inteligencias—emocionales, colaborativas, predictivas—tejidas mediante algoritmos, redes, y sistemas. Éste es el cimiento de una Educación Disruptiva avanzada, donde cada estudiante es un nodo activo entrelazado con docentes, algoritmos y recursos, creando una…
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From
www
¿Nunca te has preguntado por qué todos seguimos el mismo patrón? Es decir, cuando vamos a la escuela, aunque de niños todos pensamos de manera diferente, nos imparten la misma educación, la misma ideología, los mismos contenidos. Via Edumorfosis
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From
wwwhatsnew
La inteligencia artificial generativa se ha vuelto una herramienta cotidiana para millones de personas. Desde redactar informes hasta generar ideas creativas, sus aplicaciones son tan amplias como inmediatas. Sin embargo, este crecimiento trae consigo una pregunta clave: ¿está esta tecnología fortaleciendo o debilitando nuestro pensamiento crítico? Cambios en la forma de pensar: menos esfuerzo, más Via Mariano Fernandez S.
![]() AI: Explore how Artificial Intelligence is reshaping human cognition, creativity, and the implications of an algorithm-driven world. Are we risking conformity and mediocrity or unlocking new intellectual potential? "
Representative image Is it now in the process of transforming the human brain's role in daily life? The Industrial Revolution diminished the need for manual labour. As someone who researches the application of AI in international business, I can't help but wonder whether it is spurring a cognitive revolution, obviating the need for certain cognitive processes as it reshapes how students, workers and artists write, design and decide. Advt The economic and cultural implications are profound. EVENT Thu, 05 Jun 2025 Advt We've been here before. The Industrial Revolution replaced artisanal craftsmanship with mechanised production, enabling goods to be replicated and manufactured on a mass scale. Shoes, cars and crops could be produced efficiently and uniformly. But products also became more bland, predictable and stripped of individuality. Craftsmanship retreated to the margins, as a luxury or a form of resistance. Today, there's a similar risk with the automation of thought. Generative AI tempts users to conflate speed with quality, productivity with originality. The danger is not that AI will fail us, but that people will accept the mediocrity of its outputs as the norm. When everything is fast, frictionless and "good enough," there's the risk of losing the depth, nuance and intellectual richness that define exceptional human work. The rise of algorithmic mediocrity Despite the name, AI doesn't actually think. Tools such as ChatGPT, Claude and Gemini process massive volumes of human-created content, often scraped from the internet without context or permission. Their outputs are statistical predictions of what word or pixel is likely to follow based on patterns in data they have processed. They are, in essence, mirrors that reflect collective human creative output back to users - rearranged and recombined, but fundamentally derivative. And this, in many ways, is precisely why they work so well. Consider the countless emails people write, the slide decks strategy consultants prepare and the advertisements that suffuse social media feeds. Much of this content follows predictable patterns and established formulas. It has been there before, in one form or the other. Generative AI excels at producing competent-sounding content - lists, summaries, press releases, advertisements - that bears the signs of human creation without that spark of ingenuity. It thrives in contexts where the demand for originality is low and when "good enough" is, well, good enough. When AI sparks - and stifles - creativity Yet, even in a world of formulaic content, AI can be surprisingly helpful. In one set of experiments, researchers tasked people with completing various creative challenges. They found that those who used generative AI produced ideas that were, on average, more creative, outperforming participants who used web searches or no aids at all. In other words, AI can, in fact, elevate baseline creative performance. However, further analysis revealed a critical trade-off: Reliance on AI systems for brainstorming significantly reduced the diversity of ideas produced, which is a crucial element for creative breakthroughs. The systems tend to converge toward a predictable middle rather than exploring unconventional possibilities at the edges. I wasn't surprised by these findings. My students and I have found that the outputs of generative AI systems are most closely aligned with the values and world views of wealthy, English-speaking nations. This inherent bias quite naturally constrains the diversity of ideas these systems can generate. More troubling still, brief interactions with AI systems can subtly reshape how people approach problems and imagine solutions. One set of experiments tasked participants with making medical diagnoses with the help of AI. However, the researchers designed the experiment so that AI would give some participants flawed suggestions. Even after those participants stopped using the AI tool, they tended to unconsciously adopt those biases and make errors in their own decisions. What begins as a convenient shortcut risks becoming a self-reinforcing loop of diminishing originality - not because these tools produce objectively poor content, but because they quietly narrow the bandwidth of human creativity itself. Navigating the cognitive revolution True creativity, innovation and research are not just probabilistic recombinations of past data. They require conceptual leaps, cross-disciplinary thinking and real-world experience. These are qualities AI cannot replicate. It cannot invent the future. It can only remix the past. What AI generates may satisfy a short-term need: a quick summary, a plausible design, a passable script. But it rarely transforms, and genuine originality risks being drowned in a sea of algorithmic sameness. The challenge, then, isn't just technological. It's cultural. How can the irreplaceable value of human creativity be preserved amid this flood of synthetic content? The historical parallel with industrialisation offers both caution and hope. Mechanisation displaced many workers but also gave rise to new forms of labour, education and prosperity. Similarly, while AI systems may automate some cognitive tasks, they may also open up new intellectual frontiers by simulating intellectual abilities. In doing so, they may take on creative responsibilities, such as inventing novel processes or developing criteria to evaluate their own outputs. This transformation is only at its early stages. Each new generation of AI models will produce outputs that once seemed like the purview of science fiction. The responsibility lies with professionals, educators and policymakers to shape this cognitive revolution with intention. Will it lead to intellectual flourishing or dependency? To a renaissance of human creativity or its gradual obsolescence? The answer, for now, is up in the air. Via Charles Tiayon
Charles Tiayon's curator insight,
June 3, 2:06 PM
AI: Explore how Artificial Intelligence is reshaping human cognition, creativity, and the implications of an algorithm-driven world. Are we risking conformity and mediocrity or unlocking new intellectual potential? "
Representative image Is it now in the process of transforming the human brain's role in daily life? The Industrial Revolution diminished the need for manual labour. As someone who researches the application of AI in international business, I can't help but wonder whether it is spurring a cognitive revolution, obviating the need for certain cognitive processes as it reshapes how students, workers and artists write, design and decide. Advt The economic and cultural implications are profound. EVENT Thu, 05 Jun 2025 Advt We've been here before. The Industrial Revolution replaced artisanal craftsmanship with mechanised production, enabling goods to be replicated and manufactured on a mass scale. Shoes, cars and crops could be produced efficiently and uniformly. But products also became more bland, predictable and stripped of individuality. Craftsmanship retreated to the margins, as a luxury or a form of resistance. Today, there's a similar risk with the automation of thought. Generative AI tempts users to conflate speed with quality, productivity with originality. The danger is not that AI will fail us, but that people will accept the mediocrity of its outputs as the norm. When everything is fast, frictionless and "good enough," there's the risk of losing the depth, nuance and intellectual richness that define exceptional human work. The rise of algorithmic mediocrity Despite the name, AI doesn't actually think. Tools such as ChatGPT, Claude and Gemini process massive volumes of human-created content, often scraped from the internet without context or permission. Their outputs are statistical predictions of what word or pixel is likely to follow based on patterns in data they have processed. They are, in essence, mirrors that reflect collective human creative output back to users - rearranged and recombined, but fundamentally derivative. And this, in many ways, is precisely why they work so well. Consider the countless emails people write, the slide decks strategy consultants prepare and the advertisements that suffuse social media feeds. Much of this content follows predictable patterns and established formulas. It has been there before, in one form or the other. Generative AI excels at producing competent-sounding content - lists, summaries, press releases, advertisements - that bears the signs of human creation without that spark of ingenuity. It thrives in contexts where the demand for originality is low and when "good enough" is, well, good enough. When AI sparks - and stifles - creativity Yet, even in a world of formulaic content, AI can be surprisingly helpful. In one set of experiments, researchers tasked people with completing various creative challenges. They found that those who used generative AI produced ideas that were, on average, more creative, outperforming participants who used web searches or no aids at all. In other words, AI can, in fact, elevate baseline creative performance. However, further analysis revealed a critical trade-off: Reliance on AI systems for brainstorming significantly reduced the diversity of ideas produced, which is a crucial element for creative breakthroughs. The systems tend to converge toward a predictable middle rather than exploring unconventional possibilities at the edges. I wasn't surprised by these findings. My students and I have found that the outputs of generative AI systems are most closely aligned with the values and world views of wealthy, English-speaking nations. This inherent bias quite naturally constrains the diversity of ideas these systems can generate. More troubling still, brief interactions with AI systems can subtly reshape how people approach problems and imagine solutions. One set of experiments tasked participants with making medical diagnoses with the help of AI. However, the researchers designed the experiment so that AI would give some participants flawed suggestions. Even after those participants stopped using the AI tool, they tended to unconsciously adopt those biases and make errors in their own decisions. What begins as a convenient shortcut risks becoming a self-reinforcing loop of diminishing originality - not because these tools produce objectively poor content, but because they quietly narrow the bandwidth of human creativity itself. Navigating the cognitive revolution True creativity, innovation and research are not just probabilistic recombinations of past data. They require conceptual leaps, cross-disciplinary thinking and real-world experience. These are qualities AI cannot replicate. It cannot invent the future. It can only remix the past. What AI generates may satisfy a short-term need: a quick summary, a plausible design, a passable script. But it rarely transforms, and genuine originality risks being drowned in a sea of algorithmic sameness. The challenge, then, isn't just technological. It's cultural. How can the irreplaceable value of human creativity be preserved amid this flood of synthetic content? The historical parallel with industrialisation offers both caution and hope. Mechanisation displaced many workers but also gave rise to new forms of labour, education and prosperity. Similarly, while AI systems may automate some cognitive tasks, they may also open up new intellectual frontiers by simulating intellectual abilities. In doing so, they may take on creative responsibilities, such as inventing novel processes or developing criteria to evaluate their own outputs. This transformation is only at its early stages. Each new generation of AI models will produce outputs that once seemed like the purview of science fiction. The responsibility lies with professionals, educators and policymakers to shape this cognitive revolution with intention. Will it lead to intellectual flourishing or dependency? To a renaissance of human creativity or its gradual obsolescence? The answer, for now, is up in the air.
![]() Discover Learning and Development (L&D) myths as Jane Bozarth challenges misconceptions and explores how emerging technologies enhance corporate training. Via CommLab India
![]() When Sir Ken Robinson delivered his now-iconic TED Talk in 2006, proclaiming that “schools kill creativity,” he struck a chord that continues to reverberate through education systems worldwide. Robinson’s argument that our schools systematically squash imagination in favor of conformity and compliance sparked a movement for more creative, learner-centered approaches. Yet, less than two decades later, a new fear is echoing through these same halls: that artificial intelligence will now be the force that finally kills critical thinking in schools. How did we get from blaming the system to blaming the tool? Via Edumorfosis
Edumorfosis's curator insight,
June 2, 8:01 AM
La nueva pregunta sería: La creatividad IA está matando la escuela?
![]() The current research landscape may be messy and contradictory, but it illuminates a crucial truth: the impact of AI on education isn’t predetermined by the technology itself—it’s determined by the educational system we choose to implement it within. Via Nik Peachey
Nik Peachey's curator insight,
May 31, 1:48 AM
Some interesting insights into the limited research into AI.
Richard Platt's curator insight,
May 31, 4:07 PM
The current research landscape may be messy and contradictory, but it illuminates a crucial truth: the impact of AI on education isn’t predetermined by the technology itself—it’s determined by the educational system we choose to implement it within. |
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From
eurocities
The ICT sector is responsible for approximately 4% of global CO₂ emissions, though its full impact is difficult to measure due to the complexity of supply chains and product lifecycles. The need for sustainable ICT is urgent, given the rapid digitalisation of daily life and the ever-increasing demand for electronic devices. Via EcoVadis, Ricard Lloria
![]() Blog de la "RIED. Revista Iberoamericana de Educación a Distancia". La Revista Iberoamericana de la Educación Digital. Via LGA
![]() Juan Domingo Farnos Estamos presenciando la creación de un entorno educativo donde el proceso cognitivo y la interacción pedagógica se redibujan completamente mediante algoritmos predictivos, plataformas inteligentes y sistemas adaptativos. Si bien el concepto de aprendizaje personalizado ha estado presente durante décadas, lo que desafía hoy el modelo tradicional no es solo la individualización, sino…
![]() Purpose The use of Artificial Intelligence (AI) in education has the potential to further customise and personalise students’ learning, and encourage self-directed learning. It can also augment teachers’ professional practice by automating routine tasks and allowing teachers to spend more time... Via Nik Peachey
Richard Platt's curator insight,
June 11, 1:29 AM
Purpose The use of Artificial Intelligence (AI) in education has the potential to further customise and personalise students’ learning, and encourage self-directed learning. It can also augment teachers’ professional practice by automating routine tasks and allowing teachers to spend more time...
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From
rcepunesco
As education shifts from traditional content delivery to students to teaching students how to develop and employ agile, critical thinking, and problem-solving skills, the teacher's role is being redefined. This transformation is essential to meet the United Nations' Sustainable Development Goal 4 (SDG 4), specifically targets 4.1 and 4.A, which aim to ensure inclusive and equitable quality education and promote lifelong learning opportunities for all.
This shift is driven by the imperative to prepare students for scenarios that do not yet exist, requiring a fundamental rethinking of teaching methodologies and the competencies that educators need to develop. This shift thus requires us to embrace change as Via Edumorfosis
Edumorfosis's curator insight,
June 10, 2:14 PM
Si bien los métodos tradicionales suelen contar con investigaciones de eficacia comprobada, los docentes necesitan adoptar y adaptar herramientas digitales que les ayuden en la preparación y la impartición de la instrucción (German et al., 2022).
En las aulas del futuro, el docente no será la única fuente de información ni el centro de atención del aula. En cambio, será guía y mentor, facilitando el aprendizaje mientras los estudiantes navegan por un mundo de pantallas holográficas, simulaciones de realidad virtual y herramientas de aprendizaje impulsadas por IA. El docente ayudará a los estudiantes a conectar conceptos, aplicar sus conocimientos creativamente y ampliar los límites de su pensamiento. El futuro docente es un facilitador de la creatividad y la innovación, experto en estrategias que ayudan a los estudiantes a dirigir sus propios procesos de aprendizaje (Royce, 2023; Shippee, 2019).
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From
time
What students need the most, beyond LLMs, is space to strengthen those muscles of focus, writes Michael Serazio. Via EDTECH@UTRGV
EDTECH@UTRGV's curator insight,
June 9, 12:04 PM
"Some of our students falsely assume that product—a final paper—is what we seek, because high-stakes testing has trained them transactionally, and that’s what grading tallies. But, of course, process is what we ultimately aim to sharpen: The steps and lessons learned along the way. AI rewires that relationship, short-circuiting effort from output."
![]() Juan Domingo Farnos Para integrar las herramientas de IA en el contexto de investigaciones en ingeniería dentro de la Educación Disruptiva & IA en la Educación Superior, podemos adaptar el enfoque a procesos que son comunes en proyectos de investigación en ingeniería, como el análisis de datos, la optimización de flujos de trabajo, la simulación…
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From
grezan
La revolución tecnológica ha transformado profundamente nuestra sociedad y, como consecuencia, los procesos de enseñanza-aprendizaje. Las nuevas generaciones, inmersas en un entorno digital desde su nacimiento, presentan características distintivas en la forma de acceder, procesar y construir... Via Mariano Fernandez S., Mariano Ramos Mejia
![]() Juan Domingo Farnos RESUMEN: Investigamos una transformación paradigmática en la concepción del aprendizaje en el siglo XXI, donde la IA cognitiva no solo se limita a anticipar comportamientos a partir de datos históricos, sino que se adentra en la comprensión profunda de los procesos mentales subyacentes. La transición de análisis predictivo a comprensión cognitiva implica…
![]() Juan Domingo Farnos Esta investigación invita a los científicos, ingenieros y educadores a un ejercicio de imaginación crítica y rigor científico, a soñar con un futuro donde el aprendizaje es un proceso vivo, interconectado y auto-evolutivo, guiado por agentes inteligentes que respetan la singularidad y promueven la emancipación cognitiva.... En la frontera vibrante entre la…
![]() Por Lorenzo García Aretio RESUMEN PODCAST-AUDIO Todas las entradas de la serie “80 años. Compendio EaD”, VER AQUÍ Quien esté siguiendo est... Via LGA
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From
www
AI 2027 is imaginative, vivid, and detailed. It “is definitely a prediction,” Kokotajlo told me recently, “but it’s in the form of a scenario, which is a particular kind of prediction.” Although it’s based partly on assessments of trends in A.I., it’s written like a sci-fi story (with charts); it throws itself headlong into the flow of events. Often, the specificity of its imagined details suggests their fungibility. Will there actually come a moment, possibly in June of 2027, when software engineers who’ve invented self-improving A.I. “sit at their computer screens, watching performance crawl up, and up, and up”? Will the Chinese government, in response, build a “mega-datacenter” in a “Centralized Development Zone” in Taiwan? These particular details make the scenario more powerful, but might not matter; the bottom line, Kokotajlo said, is that, “more likely than not, there is going to be an intelligence explosion, and a crazy geopolitical conflict over who gets to control the A.I.s.” Via Edumorfosis |