Edumorfosis.it

Su concepto del «knowmad» —el trabajador nómada del conocimiento, creativo, colaborativo y capaz de aprender en cualquier contexto— no es una simple etiqueta, sino el perfil del ciudadano que ya habita este presente líquido. Su propuesta de «leapfrogging» no es una invitación a la reforma, sino un llamado a dar un salto cuántico, a dejar de poner parches en un sistema que necesita ser reimaginado desde sus cimientos.

En un 2025 donde la inteligencia artificial generativa redefine a diario las fronteras del saber y la incertidumbre es la única constante, dialogar con John Moravec no es un ejercicio académico, es una necesidad estratégica. Es conversar con quien lleva más de una década advirtiéndonos sobre la tormenta que ya llegó y, más importante aún, enseñándonos a construir mejores barcos.

La lógica indica que un maestro o una maestra trabajarán mejor, podrán atender de forma más personalizada y dedicar más tiempo a sus alumnos si tienen 15 en clase que si tienen 25. Pero más allá de la lógica, ¿qué dice la evidencia empírica sobre el papel de la ratio en las diferentes etapas educativas?

La proporción entre estudiantes y docentes incide en la calidad del aprendizaje de manera diferente según la etapa educativa, las particularidades propias de la institución y las características del profesorado.

La mayoría de las universidades occidentales quedan malparadas. Mientras Beijing entrena a sus estudiantes en prompts y verificación, Oxford, Harvard o buena parte de la Russell Group siguen midiéndose la pureza textual con el absurdo y desfasado Turnitin, y amenazando con suspensos ejemplares. El negocio de la «detección de IA», nacido para combatir un supuesto tsunami de plagio, ya despierta recelos: el despliegue de Turnitin Originality ha generado críticas por su opacidad metodológica y su altísimo índice de falsos positivos. 

No es un problema meramente técnico: es convertir la clase en un juego del gato y el ratón que estropea la confianza y desperdicia horas que podrían dedicarse a enseñar, a contrastar y a pensar. El resultado es un clima en el que estudiantes inocentes ven su expediente manchado por «frases sospechosas» y profesores cansados de perseguir fantasmas absurdos y de cumplir reglas mal diseñadas recurren a un software que promete certezas imposibles.

El empleo de la IA en todas las actividades de investigación es una realidad que no se puede ocultar. Tan real como los problemas que se advierten en las tesis de los estudiantes universitarios. Los estudiantes suelen enfrentarse a deficiencias en el conocimiento del tema a investigar, la formación en investigación y las habilidades esenciales de redacción y ortografía (Rodríguez et al., 2023) Otros problemas comunes se relacionan con la gestión del tiempo, dificultades en la selección de temas y comentarios inconsistentes de los asesores (Sharma, 2024). 

Es común encontrarnos errores en la determinación de las categorías centrales como el problema, el objetivo, las variables, entre otras. Por lo general debemos revisar una y varias veces la relación entre problema y objetivo. Incluso días antes de las defensas se vuelven a realizar ajustes a estas categorías. Entonces cómo es posible que el resto del trabajo se evalúe correctamente, mientras que se siguen modificando las categorías antes mencionadas.

AI is transforming nearly every aspect of our society, from how work gets done to how companies operate. It’s changing how we talk with our doctors, our employees, and our customers, bridging language gaps and helping us communicate more clearly and effectively. And it’s transforming education too.

Across the globe, educators are using AI to increase student agency, giving them a greater sense of ownership over how they learn. Education leaders and institutions are leveraging AI to enhance operational and administrative processes and are tapping into real-time data to improve student success. And an exciting shift is starting when it comes to the benefits of using AI—no longer just a timesaver, it can empower everyone to reimagine opportunities for the future of education together.

To better understand the state of AI in education, Microsoft Education has conducted numerous studies and surveys and collaborated with academic institutions and organizations. We’ve also surveyed academic and IT leaders, educators, and students from around the world; explore the extended survey data for more insights.

A follow-up to our AI in Education Report in 2024, this year’s edition reveals much about the ongoing evolution of AI in education, from how audiences feel about it to how it’s being used in education today—and how it might be used in the future.

The three essential dimensions of education systems and curricula in terms of how students interact with that curriculum:

1. Engagement: Students might engage because they recognize the value of what they’re learning, even if they don’t particularly enjoy it. Multiple factors drive this engagement—teaching styles, content relevance, cultural factors—all contributing to whether students see value in what they’re learning.
2. Commitment: This describes how willing students are to invest effort and persist with the learning process, whether through following established structures or driving their own learning forward.
3. Agency: This means having the ability to make decisions appropriately at their age level, having choices that genuinely impact outcomes, and opportunities to make good choices. 

From some initial research conducted over the last month, I’ve found that the vast majority of Instructional Designers choose their AI tools based on UX preference and cost.

Meanwhile, in the workplace, most L&D teams are allocated AI tools based on the existing tech stack rather than tool performance. TLDR: If your org already uses Microsoft Office Suite and Teams, you will more than likely be allocated MS Copilot as your AI sidekick for the L&D workflow.

Artificial Intelligence promises to transform education by tailoring instruction, automating routine tasks, and reshaping teachers’ roles. UNESCO stresses that AI “has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and accelerate progress towards [Education 2030]”. Governments and experts foresee AI becoming pervasive in classrooms, but emphasize a human-centric approach. For example, UNESCO and OECD frameworks urge that AI should “support teachers in their educational and pedagogical responsibilities,” with human interaction remaining at the core of education. In practice, schools will use AI tools for everything from designing lessons to grading assignments, while policymakers plan to steer AI adoption carefully to ensure inclusion and equity.

In the last 2-3 years, AI avatars have evolved from futuristic novelty to an increasingly mainstream feature of corporate training. With platforms like Synthesia making avatar-based video creation accessible to every L&D team, we're already seeing a dramatic shift in how organisations deliver training at scale with AI avatars (literally) front and centre. This shift represents more than just a technological upgrade—it's fundamentally changing how we think about the relationship between instructor and learner.

The business case is compelling: avatar-based training can save hours of production time and millions of dollars each year by eliminating the need for human presenters, reducing reshoot costs, and enabling rapid content updates. Organisations can create consistent training experiences across global teams, overcome scheduling constraints with subject matter experts, and scale personalised instruction in ways that were previously impossible.

In Canada, some professors are making a similar move amid widespread reports of AI cheating, while others are testing out oral exams or finding ways to incorporate AI. Six in 10 Canadian students said they use generative AI for their schoolwork, according to an October 2024 study from KPMG in Canada.

"We are definitely in a moment of transition with a lot of our assessments," said Karsten Mundel, co-chair of the University of Alberta's AI steering committee.

The enthusiastic response highlights a growing recognition across industries: In an era of rapid technological change and artificial intelligence (AI) development, uniquely human abilities are more crucial than ever for workplace success. According to a recent Deloitte Insights report, 92% of companies now say that human capabilities and soft skills matter more than hard skills.

Clark uses a different term for these talents – power skills – to emphasize their critical importance. He and Sandra Sjoberg, associate dean and director of marketing and innovation programs at WGU School of Business, have become strong advocates for their central role in higher education today.

El documento de trabajo "Los retos de la IA en la educación superior y las respuestas institucionales: ¿Hay lugar para marcos de competencias?", publicado por UNESCO IESALC, ofrece una revisión sistemática del estado actual de la integración de la inteligencia artificial (IA) en la educación superior. Aunque la IA presenta oportunidades significativas para la transformación pedagógica y administrativa, las instituciones de educación superior (IES) tienen lagunas críticas para prepararse y responder eficazmente a esta realidad. Las autoras, Arianna Valentini y Alep Blancas, defienden la necesidad urgente de desarrollar un marco integral de competencias de IA adaptado específicamente al contexto de la enseñanza superior.

La metodología del informe incluyó una revisión bibliográfica de enero de 2021 a agosto de 2024, complementada con un ejercicio de evaluación de las iniciativas relacionadas con la IA en 16 instituciones de educación superior en cinco regiones de la UNESCO. Este doble enfoque permitió a las investigadoras identificar una brecha crítica entre el rápido ritmo de adopción de la IA y la falta de respuestas institucionales estructuradas.

Children who are provided with access to smartphones before the age of 13 are, per a jarring new study, far more likely to suffer severe mental health problems down the line.

Having run thousands of interviews with Instruction Designers over the years, one thing is very clear: one of the key challenges we face in optimizing both the speed and quality of our work is wrangling the right information from Subject Matter Experts (SMEs).

If you’ve ever spent hours chasing the right person, only to receive half-remembered insights and a tone of impenetrable acronyms, you’re not alone. As one L&D colleague at a big corporate said to me just this week:

Access to SMEs, and the ability to consistently get the right information from them is the single biggest challenge in our projects. We spend more far more time chasing clarity than actually building training.

The more sophisticated and arguably more urgent questions we must now ask are: "How will AI change my job?”. What we’re really asking here is, will AI degrade our skills? Will it automate the creative, satisfying parts of our work and - contrary to the promise of AI - leave us with the administrative drudgery?

This is the new reality check for the Instructional Design profession and education professionals more broadly. The greatest risk to our roles may not be a future of unemployment, but a future of profound professional dissatisfaction.

The data and testimonials emerging from across the knowledge economy suggest we are at a pivotal crossroads, facing two divergent paths for human-AI collaboration. One path sees AI as a tireless assistant, a tool that handles the toil and frees us to focus on the strategic and creative work we love. The other, more insidious path, sees the machine doing the "fun stuff" while the human is left with the functional drudgery of feeding it source files and managing its output.

This is the "inverted centaur" model—where the human becomes the machine's hands, not the other way around. This is not a distant fear; it is a choice being made right now in the design of our tools and the structure of our teams. It is the central fight for the soul of our work.

In the last 18 months amidst all of the hype we have seen a growing body of peer-reviewed research on AI & Instructional Design, providing us with systematic, robust and reliable data on how AI is being used in Instructional Design and how it’s impacting (for better or worse) the speed and quality of our work.

Perhaps unsurprisingly, the results are far more nuanced than either the AI evangelists or the skeptics would have you believe. Some findings might surprise you — others will validate concerns you've probably been too polite to voice in all those AI webinars you've attended recently.

As Artificial Intelligence (AI) increasingly influences how we access information, communicate, and make decisions, AI literacy becomes essential for navigating daily life, creating with purpose, and preparing for the future of learning and work. AI literacy equips learners and educators to understand both the risks and opportunities that AI presents, and to make meaningful and ethical decisions about its use.

It helps learners critically evaluate AI’s impact on their lives, education, and communities while preparing them to shape the future. However, to fully realize the potential of AI literacy to shape learning, key barriers to implementation must be addressed, including:

• A lack of a shared understanding of what AI literacy is and how to teach it.
• Uncertainty about how AI fits into various subject areas.

This publication serves as a starting point for teachers, education leaders, education policymakers, and learning designers to understand AI literacy and decide how it fits their needs. Establishing a common language about AI literacy is instrumental for consistency across diverse educational settings.

Parece evidente que estamos ante una tormenta perfecta: economía, inteligencia artificial y exceso de formación. La subida del desempleo juvenil (5.8 % en los Estados Unidos) y el aumento del subempleo (más del 40 %), apuntan a que no hablamos tan solo de un problema tecnológico: la economía está ralentizada, las empresas recortan puestos y hay una sobreproducción de graduados. En algunas compañías se están dedicando a pedir a los responsables de equipo que demuestren que la contratación que pretenden conseguir va a desempeñar funciones que una inteligencia artificial no podría llevar a cabo. Esta llamada «elite overproduction» o inflación de credenciales, está amenazando con devaluar los títulos universitarios.

The AFT, alongside the United Federation of Teachers and lead partner Microsoft Corp., founding partner OpenAI, and Anthropic, announced the launch of the National Academy for AI Instruction today. The groundbreaking $23 million education initiative will provide access to free AI training and curriculum for all 1.8 million members of the AFT, starting with K-12 educators. It will be based at a state-of-the-art bricks-and-mortar Manhattan facility designed to transform how artificial intelligence is taught and integrated into classrooms across the United States. 

The academy will help address the gap in structured, accessible AI training and provide a national model for AI-integrated curriculum and teaching that puts educators in the driver’s seat.

Younger generations must be raised to develop their own motivations and goals to prevent their physical and mental atrophy. It is urgent to replace the current productivity-driven education systems with an alternate model that fosters personal growth. This model will preserve children’s innate authenticity and alertness. Providing them with an environment that motivates them to reach their full potential will ensure that children will enjoy a life-long journey of personal growth in a society where AI replaces the need for survival-driven productivity.

Teams today aren’t just asked to execute tasks: They’re called upon to solve problems. You’d think that many brains working together would mean better solutions, but the reality is that too often problem-solving teams fall victim to inefficiency, conflict, and cautious conclusions. The two charts below will help your team think about how to collaborate better and come up with the best solutions for the thorniest challenges.

According to Harvard Business Review the use of GPT is becoming more intimate:

• A significant shift from traditional technical applications to more deeply personal and emotional uses of Generative AI, with custom GPTs enabling tailored solutions in therapy, personal organization, and self-improvement.
• Underscoring the transformative impact of GenAI on daily life and professional environments, demonstrating how effective, user-driven applications are accelerating behavioral change and redefining productivity and support in both personal and business contexts.

¿Ha empeorado la calidad del alumnado en las universidades españolas? Manuel Hidalgo asegura que sí. El profesor universitario ha compartido su hipótesis en su cuenta de X (antes Twitter), donde ha publicado un hilo que trata esta problemática actual.