Learning new skills can be a great way to keep an aging brain in shape. There is great joy in reinventing yourself by discovering unfamiliar areas of expertise. Here are some general guidelines for how to learn a new skill (Vanderbilt, 2021).

While “polarization” was Merriam-Webster’s word of the year for 2024, we have some early frontrunners for 2025 — especially when it comes to higher education. Change. Agility. Uncertainty. Flexibility. As we take a deep dive into the trends on tap for higher education in the coming year, it’s important to note that, with an incoming administration who has vowed to shake things up, the current postsecondary system could be turned on its head. With that in mind, we wade into our yearly look at the topics and trends that will be making headlines — and making waves — in the year ahead.

While most people were talking about using AI to generate content or automate grading, this research pointed to something way more interesting: using AI to scale evidence-based instructional approaches that have traditionally been too resource-intensive to implement broadly.

La Educación nunca volverá a ser la misma. En esta conferencia magistral, el Profe Sang analiza el impacto de la inteligencia artificial en la educación, explorando cómo las herramientas tecnológicas están transformando el aprendizaje a través de la personalización, la automatización y la eliminación de barreras de espacio, tiempo e idioma.

Además, reflexiona sobre las oportunidades que estos avances ofrecen a educadores e instituciones educativas, así como los desafíos que enfrentan quienes no se preparen para este cambio. Una visión imprescindible sobre el futuro de la educación en la era de la IA. 

Education leaders and faculty recognize the value of AI in idea generation and developing personalized learning. However, many institutions have raced to create policies largely focused on how to control its use without giving much thought to how to leverage its full potential. The conversation should shift toward leveraging our teaching and learning approach and harnessing this new technology’s potential.

En un mundo transformado por la irrupción generalizada de la inteligencia artificial (IA) en el último año, nos enfrentamos a una encrucijada crucial en el ámbito educativo. Aunque la IA ha estado presente desde 1956, su desarrollo y aplicación recientes no representan simplemente un desafío tecnológico, sino que nos desafían a reconsiderar el propósito de la educación en todas sus etapas. Más allá de la integración de nuevas metodologías y tecnologías, estamos ante la oportunidad de co-crear un modelo educativo que no solo se ajuste a las necesidades actuales, sino que también prepare a los estudiantes para un futuro incierto y en constante cambio.

Una de las preocupaciones no solo de los educadores, sino también de los padres y madres, está relacionada con el desarrollo literario de sus hijos. La sociedad está inmersa en la cultura impresa y digital, y la literacidad funcional no es suficiente para suplir las carencias derivadas de un entrenamiento insuficiente de las habilidades lectoras. Por ello, lo importante es garantizar la motivación por la lectura, permitiendo el acceso a distintos tipos de texto y fomentando su comprensión. Centrar los espacios educativos en un único tipo de texto supone desperdiciar el potencial que nos puedan ofrecer otros tipos de lenguajes; en este sentido, centrar los espacios educativos (ya sean familiares como escolares) en un único tipo de narración va en detrimento del desarrollo de un cúmulo de habilidades necesarias para el desarrollo cognitivo y social del sujeto.

Schools are tackling questions such as: Should the technology be banned? What should an AI use policy and protocols look like? How can schools harness this technology for teaching and learning? And, alternatively, how can schools prevent students from using ChatGPT and other generative AI tools to cheat? 

As we kick off 2025, I've been thinking a lot about how we might use the AI tools we have in our toolkit to do more than just generate content or automate grading. As I’ve said before (and will say again!) the real opportunity of AI lies not in doing what we already do but faster and cheaper; it lies in scaling high-impact pedagogical approaches that have traditionally been difficult or impossible to implement broadly.

En el ámbito académico, la creación de artículos científicos constituye una de las tareas más esenciales, impulsando el conocimiento y la innovación. Tradicionalmente, este proceso ha requerido extensas horas de investigación meticulosa y redacción cuidadosa. Sin embargo, la introducción de la inteligencia artificial generativa (IA generativa) está marcando un cambio significativo en la forma en que se aborda la enseñanza y la investigación universitaria.

La educación, como la concebimos hoy, está al borde de una revolución tectónica, donde las estructuras tradicionales se disuelven y surgen nuevos horizontes posibles. Nos encontramos en un momento de transición, una fase crítica que dará paso a un modelo educativo algorítmico, centrado en la intersección entre la inteligencia artificial, el aprendizaje personalizado y la autogestión del conocimiento. Este nuevo paradigma no será una simple mejora incremental, sino una reconfiguración ontológica de lo que entendemos por aprendizaje y enseñanza. Las palabras de Kevin Kelly (2020) resuenan en este contexto: «La inteligencia del futuro no está en las máquinas, sino en la colaboración entre humanos y algoritmos».

En el mundo educativo actual, la evaluación tradicional ha seguido un camino lineal que limita las oportunidades de profundización y reflexión en los estudiantes. Un ensayo escrito, típico de esta metodología, se limita a ser evaluado y calificado, sin dejar espacio para reflexionar sobre los aprendizajes logrados ni para desarrollar habilidades críticas como la metacognición. Sin embargo, la integración de herramientas de inteligencia artificial (IA) y estrategias de retroalimentación formativa tiene el potencial de transformar este paradigma, promoviendo aprendizajes más profundos y el desarrollo de competencias digitales y de IA tanto en estudiantes como en docentes.

The Nigerian pilot program demonstrated something powerful: with the right tools, students can transcend the limits of traditional education. The efficiency was staggering. In just 30 school days, students achieved the equivalent of two academic years. That’s a 1,200 percent improvement—a statistic that would make any policymaker or educator stand up and take notice. But the numbers, as impressive as they are, tell only part of the story. The deeper magic lies in the possibilities unlocked by AI and this program.

These trends highlight the key shifts shaping education in 2025. From AI’s growing role to the focus on flexible learning models and practical workforce skills, education is heading toward smarter, more connected systems of impact. This momentum signals a move toward building education ecosystems that are more integrated, adaptable, and equipped to meet future challenges. 

En medio de la revolución tecnológica que vivimos en 2025, nos encontramos ante una paradoja educativa que merece nuestra atención inmediata. Mientras celebramos la integración de la Inteligencia Artificial (IA) en las aulas universitarias, debemos preguntarnos: ¿estamos realmente innovando o simplemente digitalizando viejos paradigmas?

The integration of generative artificial intelligence (AI) tools like ChatGPT in education has raised concerns that students may become dependent on AI-generated solutions, potentially stifling the development of critical thinking skills. Compounding this issue is the fact that Bloom’s Taxonomy—the widely used framework for designing educational goals—fails to address the cognitive demands of AI-assisted learning.

This exploratory study presents a revised framework that incorporates AI-specific competencies, offering a more relevant model for nurturing critical thinking in an AI-driven environment. Using a conceptual approach supported by empirical evidence from MSc Marketing students’ interactions with AI tools over 4 weeks, the study found that AI can both enhance and challenge critical thinking across cognitive, affective, and metacognitive domains.

Key elements such as melioration, ethical reasoning, collaboration, and reflective thinking were identified as critical for developing deeper engagement with AI-generated content. The framework proposes 12 propositions that inform future research and pedagogical strategies. This study outlines a research agenda for examining AI’s impact on cognitive development, serving as a resource for educators, policymakers, and researchers seeking to adapt teaching methods for AI-assisted education.

With the increasing prevalence of digital devices such as smartphones, tablets and e-readers, more and more reading is happening in digital formats – also in classrooms across the world. The present study focuses on lower secondary school students and their reading comprehension and attitudes toward reading on paper and screens.

The study uses an innovative methodological approach were eye-tracking technology is used to observe ten carefully sampled eight grade students with different reading levels. The students read a selection of texts and answered questions from the Norwegian national reading assessment on comparable versions on paper and on screen.

By analyzing eye movement data (reading transitions), including more than 25000 fixations, in combination with text reading comprehension outcomes, students' cued retrospective reporting from reading, and interview data we have obtained detailed and comprehensive data on students' reading comprehension, reading behavior, and reading experiences across different media. A key result is that reading on screen leads to more shallow processing and can hinder reading comprehension.

Importantly, our results from the students' cued retrospective reporting of their eye tracking, showed that they were unaware of their reading behavior and didn't reflect much on reading in different media. These findings have implications for the increasing shift to digital learning environments in the educational context. It is important to recognize the difference between reading processes, and policymakers and practitioners cannot assume that these processes are the same across individuals and different delivery modes.

In the constantly evolving landscape of Higher Education, the emergence of Artificial Intelligence (AI), its integration into technology and our daily lives, and its use in and outside of the classroom have brought incredible opportunities and complex challenges. As universities embrace this new age, understanding
the unique viewpoints of students and university leadership—the key stakeholders—is vital in capitalizing on the potential of AI while also addressing potential ethical, pedagogical, and operational challenges.

Anthology conducted a global survey of more than 5,000 higher education leaders and current students in eleven countries to provide context and perspective from those leaders and students about the opportunities, challenges, adoption, and impact of artificial intelligence. The study reveals insights highlighting the need for a collaborative approach regarding AI to help enrich the educational experience and ensure future-ready graduates.

This report focuses on the responses from students and university leaders in the United States, including where there are significant differences compared to their counterparts in other countries.
Through this research, Anthology aims to contribute to the enhancement of the Higher Education experience for students and universities as they work together to refine how teaching and learning take place.

Actualmente existe una gran cantidad de publicaciones sobre IA y
educación superior. La mayor parte de estas obras centran su atención sobre las distintas herramientas y aplicaciones inteligentes, así como sobre las promesas y desafíos educativos de la IA. Evidentemente comparto la mayoría de lo que se dice. Sin embargo, echo en falta propuestas o modelos sobre cómo articular estrategias didácticas de intervención docente destinadas a formar al alumnado universitario como un sujeto culto, competente y crítico ante la sociedad digital y la IA.

Por esta razón he escrito este libro. Fue concebido como un recurso de apoyo, a medio camino entre ser un ensayo y una guía de orientaciones didácticas, al módulo denominado La integración pedagógica de la IA en la docencia universitaria que se oferta dentro de un curso online abierto sobre la Inteligencia Artificial (IA) dirigido al profesorado de la Universidad de La Laguna.

Su finalidad es presentar, por una parte, una reflexión o análisis pedagógico sobre cómo la tecnología afecta y condiciona las creencias y prácticas de la docencia universitaria. Por otra también se ofrecen pautas o prescripciones sistematizadas en un modelo didáctico de cómo organizar las tareas de aprendizaje para favorecer en el alumnado universitario el desarrollo del pensamiento crítico y autónomo.

While the hype around ChatGPT and other artificial intelligence tools in K-12 has made it seem like most educators have tried them, new survey results from the EdWeek Research Center suggest that’s not the case.

Two of every three educators said they haven’t used AI-driven tools in their classrooms, according to the survey, which included 498 teachers and was conducted between Nov. 30 and Dec. 6.

When broken down, 37% said they’ve never used them and don’t plan to start, 29% say they haven’t used them but plan to start this school year or in the near future, according to the survey results.

Este esquema sintetiza las competencias clave que los docentes universitarios deben adquirir y desarrollar en el contexto de la inteligencia artificial y los agentes inteligentes, alineadas con los retos del siglo XXI. Representa una hoja de ruta integral para la transformación educativa, centrada en la innovación, la ética y la colaboración interdisciplinaria.

Advances in Generative Artificial Intelligence (GAI) show great potential for improving Education. Yet little is known about how this new technology should be used and how effective it can be. Here we report a randomized, controlled study measuring college students’ learning and their perceptions when content is presented through an AI-powered tutor compared with an active learning class.

The AI Tutor was developed with the same pedagogical best practices as the lectures. We find that students learn more than twice as much in less time when using an AI tutor, compared with the active learning class. They also feel more engaged and more motivated. These findings offer empirical evidence for the efficacy of a widely accessible AI-powered pedagogy in significantly enhancing learning outcomes, presenting a compelling case for its broad adoption in learning environments. 

For decades, futurists have speculated about the arrival of Artificial General Intelligence (AGI), pinpointing its debut to around 2025-ish. Now here we are, and AGI is no longer science fiction in our minds; it’s the natural progression of iterative improvements in existing models, coupled with breakthroughs yet to emerge.

When we reach the consensus that an era of AGI has arrived, the implications will be seismic. It will not only perform tasks currently done by humans but create entirely new domains of work that humans could have done. For many, the workplace will shift into an arena where AGI becomes both competitor and collaborator. The disruption is inevitable. The question everybody is asking is: are we ready? Of course not.