Hearing the horror stories they have to share, it's not hard to see why Gehl and other educators feel that way. A Los Angeles-based teacher grimly estimated that 40% of the work that came across their desk "is touched by the hand of AI." Another who teaches postgrads was appalled that their students in a doctoral program about responsible AI gave in to lazily using the tech.

En este vídeo descubrirás el origen oscuro del sistema educativo y cómo fue diseñado por las élites para adoctrinar, manipular y fabricar obedientes trabajadores. Desde Prusia hasta Rockefeller, entenderás cómo convirtieron la educación en una herramienta de control masivo y en uno de los negocios más rentables de la historia. Esta no es una teoría: son hechos históricos que te abrirán los ojos. Si alguna vez sentiste que algo no cuadraba… esto lo explica todo.

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?

In much of the public debate, creativity and critical thinking are treated as either interchangeable or competing priorities, when in fact, both are essential to meaningful education and innovation. Yet, the same structures that kill creativity (e.g., expressed as imagination, originality, and divergent thinking) also discourage critical thinking (questioning, reasoning, and independent judgment). When students are rewarded for reproducing accepted answers rather than generating new ones or interrogating the old, neither skill is meaningfully developed.

For many college students these days, life is a breeze. Assignments that once demanded days of diligent research can be accomplished in minutes. Polished essays are available, on demand, for any topic under the sun. No need to trudge through Dickens or Demosthenes; all the relevant material can be instantly summarized after a single chatbot prompt.

Welcome to academia in the age of Artificial Intelligence. As several recent reports have shown, outsourcing one’s homework to AI has become routine. Perversely, students who still put in the hard work often look worse by comparison with their peers who don’t. Professors find it nearly impossible to distinguish computer-generated copy from the real thing — and, even weirder, have started using AI themselves to evaluate their students’ work.

You need resources for creating eLearning, videos, presentations, websites, and animations, right? Here are eleven sets of freebies to help you get the job done. There was no effort to list AI tools (there are so many of them now!), but some are AI-enhanced.

Some tools and assets require registration to download. Please be careful when downloading freebies to be sure there is nothing malicious. I attempt to list reputable sites, but cannot vouch for each one. Enjoy!

One of the goals we've long talked about—but often struggled to implement—in instructional design is rapid prototyping. In other industries - from design thinking to product development and programming - building and testing early versions of ideas is a critical part of their work and proven to lead to better outcomes. Working prototypes spark clearer stakeholder feedback than static documents, and early user testing saves costly rework down the line.

Research shows that the same is true in instructional design. Rapid prototyping of courses, modules or even discrete activities is shown to improve instructional product quality, shorten development cycles, and enhance collaboration between designers and stakeholders (Daugherty et al., 2007; Gerber & Carroll, 2012). Compared to traditional linear “waterfall” models, prototyping enables instructional designers to integrate formative evaluation at every step, improving usability, learner engagement and likelihood of impact (Tripp & Bichelmeyer, 1990; Nixon & Lee, 2001).

As the labor market evolves and as generative AI impacts industries, students and employers believe microcredentials play an important role in career success, according to a new report from Coursera.

Nearly 9 in 10 students view microcredentials as key to job success, and 96 percent of students favor the inclusion of GenAI credentials in degree programs, according to Microcredentials Impact Report 2025: Insights from Students and Employers.

AI also brings its share of challenges, particularly when it comes to assessing student performance. One of the most common questions educators ask me is, “How can we stop students from using AI to cheat?” I have to admit that it’s fascinating to me that we are suddenly so interested in addressing cheating. Research from Stanford University School of Education shows that the prevalence of cheating among U.S. high school and college students is nothing new. The study found that nearly 70 percent of U.S. high school and college students regularly engaged in cheating long before the emergence of generative AI. Other studies have shown similar results. 

This manifesto critically examines the unfolding integration of Generative AI (GenAI), chatbots, and algorithms into higher education, using a collective and thoughtful approach to navigate the future of teaching and learning. GenAI, while celebrated for its potential to personalize learning, enhance efficiency, and expand educational accessibility, is far from a neutral tool. Algorithms now shape human interaction, communication, and content creation, raising profound questions about human agency and biases and values embedded in their designs. As GenAI continues to evolve, we face critical challenges in maintaining human oversight, safeguarding equity, and facilitating meaningful, authentic learning experiences. This manifesto emphasizes that GenAI is not ideologically and culturally neutral. Instead, it reflects worldviews that can reinforce existing biases and marginalize diverse voices. Furthermore, as the use of GenAI reshapes education, it risks eroding essential human elements—creativity, critical thinking, and empathy—and could displace meaningful human interactions with algorithmic solutions. This manifesto calls for robust, evidence-based research and conscious decision-making to ensure that GenAI enhances, rather than diminishes, human agency and ethical responsibility in education.

The new publication includes guidance for students using AI in their college studies and offers practical advice about preparing for careers that require AI knowledge and skills. The content was developed with input from consulting scholars and students in 14 countries.

Students, faculty and staff at 1,900 colleges and universities around the world accessed the first Student Guide to AI when it was released in August 2024. Since then, the guide’s website has provided information to more than 36,000 users in 139 countries. The second publication supplements the first, and both are useful resources for students, faculty and staff who want to learn about AI.

“By providing a free resource written in a way all students can access, we hope to increase AI literacy and support students as they adapt to these rapidly changing technologies,” says Elon University President Connie Book. “From the outset, we knew that a second publication would be necessary, with rapid advances in AI changing the learning landscape. This current version will be especially useful as colleges and universities prepare for the upcoming academic year.”

¿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.

Nietzsche y Schopenhauer reflexionaron bastante sobre esto. De hecho, tenían ideas distintas, pero muy particulares sobre lo que representaba la educación y por qué cada estudiante debería ser educado de manera diferente.

En esta ocasión, haremos una exploración completa sobre la historia del sistema educativo: de dónde proviene, cómo llegó a Occidente y cómo se ha convertido en la mayor trampa del mundo moderno...

Picture this: a learner on a course you designed opens their laptop and types into ChatGPT: "I want to learn by teaching. Ask me questions about calculus so I can practice explaining the core concepts to you."

In essence, this learner has just become an instructional designer—identifying a gap in the learning experience and redesigning it using evidence-based pedagogical strategies.

This isn't cheating—it's actually something profound: a learner actively applying the protégé effect, one of the most powerful learning strategies in cognitive science, to redesign and augment an educational experience that, in theory, has been carefully crafted for them.

I honestly don’t know how I should be educating my kids. A.I. has raised a lot of questions for schools. Teachers have had to adapt to the most ingenious cheating technology ever devised. But for me, the deeper question is:

• What should schools be teaching at all? A.I. is going to make the future look very different.
• How do you prepare kids for a world you can’t predict?
• And if we can offload more and more tasks to generative A.I., what’s left for the human mind to do?

Rebecca Winthrop is the director of the Center for Universal Education at the Brookings Institution. She is also an author, with Jenny Anderson, of “The Disengaged Teen: Helping Kids Learn Better, Feel Better, and Live Better.” We discuss how A.I. is transforming what it means to work and be educated, and how our use of A.I. could revive — or undermine — American schools.

Over the past several years, educators have produced a seemingly endless string of task force reports, policy statements, op-eds, and other forms of hand-wringing about the role of AI in writing. But few have recognized what is abundantly obvious to pretty much everyone under the age of 25—that today’s young people will inhabit a future where the vast majority of writing will be produced using AI. 

Of course, there are exceptions. Novelists, reporters, screenwriters, columnists, attorneys, academics, and others in writing-intensive professions will still need to be skilled writers. For them, AI will complement and amplify—but not fully replace—human writing expertise.  

Research by the student accommodation company Yugo reveals that: 

• 43%of UK university students are using AI to proofread academic work
• 33% use it to help with essay structure
• 31% use it to simplify information
• Only 2% of the 2,255 students said they used it to cheat on coursework

Universities need to become more flexible, adaptable and agile to ensure that students are prepared for a fast-moving, disruptive world impacted by evolving technologies such as artificial intelligence, sweeping trade disruptions, and significant demographic changes, a meeting of Pacific Rim university leaders heard.

Meeting on the margins of the Asia-Pacific Economic Cooperation (APEC) education ministers meeting in Jeju, South Korea, the APEC University Leaders Forum (AULF) focused on the theme: “Leveraging AI in higher education to address Asia Pacific challenges”.

La Inteligencia Artificial ha penetrado con determinación en cada rincón de nuestra sociedad, y la educación no ha sido una excepción. Sus primeros pasos en las aulas e instituciones educativas ya han redefinido la forma en la que enseñamos y aprendemos. Pero, como cualquier odisea de exploración, tras pisar un terreno, siempre nos sentimos impulsados a descubrir el siguiente. Más allá de las aplicaciones inmediatas y palpables que ya hemos explorado, existe un futuro que todavía no está escrito, lleno de posibilidades, desafíos y preguntas sin respuesta.

Esta guía es una invitación a la reflexión profunda, a la imaginación y a la definición conjunta de posibles futuros en los que la IA y la educación deberán convivir.

Aunque el futuro es una entidad esquiva e imprevisible, nuestra capacidad para imaginar nos proporciona un camino para explorar, al menos en parte, lo que podría esperarnos. No tenemos una bola de cristal que nos permita prever con precisión los acontecimientos que vendrán, pero sí podemos esbozar escenarios probables, e incluso deseables, sobre la intersección entre la IA y Educación.

The push for A.I. in K-12 schools is now coming from the president, who issued an executive order on April 23 calling for the use of the technology in all grades. The secretary of education, Linda McMahon, previously said her goal is getting the federal government out of education, sending control back to the states and empowering parents, but apparently there’s a carve-out for nudging Big Tech’s continued incursion into the classroom.

The executive order claims that “A.I. education in kindergarten through 12th grade (K-12) is critical” because the United States needs “to develop an A.I.-ready work force and the next generation of American A.I. innovators.” The executive order commands the secretary of education to also “prioritize the use of A.I. in discretionary grant programs for teacher training” so that educators might “integrate the fundamentals of A.I. into all subject areas.

There was a time when educators feared that the use of handheld calculators would encourage students to cheat on math homework and ruin their mathematical reasoning skills because students would lose the ability to do mental math. Similarly dire predictions were made about the spell-check functions on word processors and, later, by programs that corrected grammar and usage errors in student essays. The latest concern over how technology might impair student learning is generative artificial intelligence (AI), including Chat GPT, HayoAI, Tailor, and many others. Teachers have legitimate concerns about the impact of AI on learning, with AI programs writing student essays, lab reports, and responding to test questions in a broad array of subjects. In a recent survey, 56 percent of students admit to using AI to craft answers on assignments despite the growing efforts of schools to curtail student’s use of it. 

El informe ofrece un análisis detallado sobre cómo los estudiantes universitarios en Estados Unidos están adoptando herramientas de inteligencia artificial, especialmente ChatGPT, y cómo esta tendencia influye en la preparación de la futura fuerza laboral.

Según el informe, más de un tercio de los jóvenes de 18 a 24 años en EE. UU. utilizan ChatGPT, y aproximadamente una cuarta parte de sus interacciones con la herramienta están relacionadas con el aprendizaje, la tutoría y el trabajo académico. Los estudiantes emplean ChatGPT para iniciar trabajos y proyectos, resumir textos extensos, explorar temas, revisar escritos y obtener ayuda en programación.

While Artificial Intelligence has already introduced significant disruption to educational systems, quantum computing stands to exponentially amplify these shifts. Quantum-AI Systems, which leverage probabilistic computing to process high-dimensional data and explore vast solution spaces in parallel, may redefine how learning environments adapt, how decisions are optimized, and how institutional systems are structured. This convergence of quantum computing and AI introduces fundamentally new computational logics that challenge conventional models of curriculum design, assessment, and pedagogical agency.