La innovación educativa no es un concepto nuevo. Desde los inicios de la educación masiva, han existido pioneros y pioneras que han buscado formas alternativas de enseñar, cuestionando el statu quo y proponiendo métodos más efectivos y significativos. Sin embargo, lo que distingue el momento actual es la creciente conciencia social de que la escuela necesita transformarse. Ya no se trata de iniciativas aisladas o de educadores visionarios trabajando en solitario; estamos presenciando un movimiento global hacia una educación más dinámica, inclusiva y relevante.

El desafío que enfrentamos no es solo tecnológico o metodológico; es fundamentalmente un desafío de concepciones y decisiones. Debemos estar dispuestos a cuestionar nuestras suposiciones, a experimentar con nuevas ideas y a abrazar el cambio. La educación del futuro debe ser capaz de desarrollar en los estudiantes no solo conocimientos, sino también habilidades críticas, creatividad, capacidad de adaptación y una mentalidad de aprendizaje permanente.

Especialistas en Tecnología Educativa, entre ellos Alejandro Artopoulos, advierten sobre las consecuencias negativas para la inclusión digital y el aprendizaje. En lugar de eliminar los dispositivos, proponen ideas para integrarlos de una manera pedagógica y consciente porque, coinciden, los celulares pueden ser herramientas clave para el desarrollo de competencias digitales y la ciudadanía crítica, aspectos esenciales en la educación del siglo XXI.

We live in the age of robots. Thanks to advances in AI, it is now theoretically possible to, say, make an entire feature-length film without hiring any humans to write a screenplay, act or compose the score.

Naturally, AI has found its way into just about every area of modern life, including academia. Their use at colleges and universities has not been entirely free of controversy, but AI and automation have a number of practical applications in the academic library. Indeed, these tools have the potential to transform academic librarianship for the better.

La universidad del futuro se enfrenta a un desafío sin precedentes: adaptarse a un entorno en constante cambio, impulsado por la tecnología disruptiva y la inteligencia artificial (IA). En lugar de resistirse a estos cambios, la institución debe aprender a reinventarse a sí misma. Esto implica adoptar una mentalidad de auto-innovación, que permita a los estudiantes y profesores diseñar sus propias rutas de adaptación y renovación permanente.

La auto-innovación incremental se refiere a la mejora continua de los procesos y métodos existentes. Por ejemplo, un profesor de matemáticas puede utilizar herramientas de IA para personalizar la enseñanza y hacerla más interactiva, utilizando plataformas de aprendizaje en línea que se adaptan a las necesidades individuales de cada estudiante.

Por otro lado, la auto-innovación radical (disruptiva), implica la creación de nuevos modelos y paradigmas que revolucionen la forma en que se enseña y se aprende. Un ejemplo de esto es la implementación de programas de aprendizaje automático que permiten a los estudiantes crear sus propios cursos y contenidos, utilizando tecnologías como la realidad virtual y aumentada.

La IA y la automatización pueden ayudar a los estudiantes a desarrollar habilidades como la resolución de problemas complejos, la creatividad y la colaboración. Por ejemplo, un estudiante de ingeniería puede utilizar herramientas de IA para diseñar y simular prototipos de productos, lo que le permite experimentar y aprender de manera más efectiva.

A private school in London is opening the UK's first classroom taught by artificial intelligence instead of human teachers. They say the technology allows for precise, bespoke learning while critics argue AI teaching will lead to a "soulless, bleak future".

Hoy en día, resulta imposible imaginar un mundo sin tecnología. Desde los teléfonos móviles hasta las redes sociales, la tecnología ha transformado todos los aspectos de nuestra vida, incluyendo, por supuesto, la educación. Pero, ¿realmente la tecnología en las Aulas mejora la tecnología la forma en que aprendemos?

En primer lugar, es importante entender qué tipo de tecnología estamos hablando. En las aulas, nos referimos principalmente al uso de ordenadores, tablets, pizarras digitales e incluso inteligencia artificial para apoyar el aprendizaje de los estudiantes. Estos recursos deberían facilitar la enseñanza y ayudar a los alumnos a adquirir habilidades necesarias para el siglo XXI. Sin embargo, en la práctica, no todo el mundo está de acuerdo con este enfoque.

Artificial Intelligence (AI) has sparked transformative possibilities in many facets of human life in the current era of rapid technological advancement. AI tools continue to make headlines, while critiques also emerge, citing algorithmic biases, privacy concerns, accountability issues, implications for equity and inclusion, and others. As a general-purpose technology, AI is expected to transform and is already changing a wide range of areas, from advertising, agriculture, and criminal justice, through education, finance, health, marketing, science and security to transport (OECD, 2019[1]). Benefits of AI use in these areas include improving the efficiency of decision making, saving costs and enabling better resource allocation (ibid.).

AI might also have profound impacts on education systems, including on equity and inclusion. Therefore, this working paper delves into some debates around the connection between AI, equity and inclusion in education. By exploring the opportunities and challenges that arise as AI tools reshape the educational
landscape, it aims to set the ground for a meaningful discourse on ensuring equitable and inclusive education in times of AI.

GPT-5: La Revolución de la IA con Inteligencia a Nivel de Doctorado (Nueva Actualización de GPT-5)

¿Estás listo para descubrir el futuro de la IA con GPT-5? En este video, exploraremos la última actualización de GPT-5 y sus capacidades revolucionarias. ¿Qué hace que GPT-5 se destaque en el mundo de la inteligencia artificial?

GPT-5 está preparado para transformar la forma en que interactuamos con la tecnología, contando con inteligencia a nivel de doctorado. Analizaremos cómo las características avanzadas y mejoras de GPT-5 pueden impactar diversos campos, desde la investigación hasta las tareas cotidianas. Este es un avance significativo respecto a GPT-4, y querrás entender todo su potencial.

¿Cómo cambiará GPT-5 la inteligencia artificial? ¿Cuáles son las nuevas características de GPT-5? ¿Cómo se compara GPT-5 con GPT-4? ¿Cómo puede usarse GPT-5 en la investigación? ¿Qué industrias se beneficiarán de GPT-5? Este video responderá todas estas preguntas. Asegúrate de verlo hasta el final para no perderte nada.

This year’s survey includes updates on online investment priorities and pricing approaches, which were covered in past CHLOE surveys. New questions illuminate where COLOs see friction between online efforts, the legacy institution and mission, and the direction and adequacy of online budgets and support. There is also a discussion on how COLOs view brewing regulatory changes on third-party servicers (TPS) and online program management (OPM) companies, as well as existing regulations for regular and substantive interaction (RSI). As online learning (and education in general) faces a new era of artificial intelligence (AI), CHLOE 9 quizzed COLOs about where the technology is beginning to make an impact (or at least have a presence) and the extent to which institutional policy is taking shape to address AI use and challenges.

It may feel as though generative artificial intelligence (GenAI) has leapt from ChatGPT to every nook and cranny of our digital lives: the search results we see from Google, the productivity tools we use from Microsoft, and of course, customer-support chatbots all over the Web. As fascinating as GenAI is, though, this new type of AI that has driven the most excitement (and anxiety) in recent years is still very much in its infancy.

As those of us in education think about how GenAI can be used responsibly and effectively to support learners and educators, we need to think carefully about the future we want to build. Educators already see a range of benefits for AI broadly, but 70% also have concerns about its unknown impacts, according to our recent Global Education Insights Report. The unknown impact of GenAI specifically is an area where I’m both excited and anxious.

There are significant implications of artificial intelligence (AI) for education, teaching and learning, and for teachers’ roles and competencies. Indeed, AI can process vast amounts of information and text far beyond any human capacity and can produce new content across the range of symbolic representations of human thinking, identify patterns in data presented in various formats, and can facilitate human decision-making by predictive analyses. Emerging practices in the use of AI in education clearly demonstrate the potential of AI to enable new forms of teaching, learning and education management and enhance learning experiences and support teacher tasks.

However, AI can pose significant risks to students, the teaching community, education systems and society at large. AI may threaten human agency, intensify climate change, violate data privacy, deepen long-standing systemic inequalities and exclusion, and lead to new forms of discrimination. In education, AI can reduce teaching and learning processes to calculations and automated tasks in ways that devalue the role and influence of teachers and weaken their relationships with learners. It can narrow education to only that which AI can process, model and deliver. Finally, it can also exacerbate the worldwide shortage of qualified teachers through disproportionate spending on technology at the expense of investment in human capacity development.

The use of AI in education therefore requires careful consideration, including an examination of the evolving roles teachers need to play and the competencies required of teachers to make ethical and effective use of AI. Teachers are the primary users of AI in education, and they are expected to be the designers and facilitators of students’ learning with AI, the guardians of safe and ethical practice across AI-rich educational environments, and to act as role models for lifelong learning about AI. To assume these responsibilities, teachers need to be supported to develop their capabilities to leverage the potential benefits of AI while mitigating its risks in education settings and wider society.

David Game College in London, UK, is planning to allow students around the age of 15 to use  AI tools before taking standardized exams next year. This initiative, despite concerns from experts about the limitations of AI compared to human teachers, aims to support both students who struggle to keep up and those who excel.

Para aplicar un enfoque creativo y disruptivo utilizando inteligencia artificial (IA) en una comunidad de universidades (interuniversidades) se puede diseñar un escenario innovador basado en la analogía de sinapsis algorítmicas y sinergias neuronales. Este enfoque se inspira en la estructura del cerebro humano, donde las neuronas se conectan a través de sinapsis para procesar y transmitir información de manera eficiente y adaptativa. Del mismo modo, una red de universidades puede funcionar como un ecosistema inteligente que optimiza el aprendizaje y la colaboración mediante el uso de IA avanzada.

Las sinergias neuronales en la inteligencia artificial (IA) se refieren a la manera en que los sistemas de IA se inspiran en el funcionamiento del cerebro humano para mejorar su eficiencia y capacidad de aprendizaje. La sinapsis, que es la conexión entre las neuronas en el cerebro, ha sido un modelo para el diseño de redes neuronales artificiales, que son la base de muchos algoritmos de IA.

Este libro surge con la intención de revisar las porosidades y vínculos entre la didáctica y la tecnología, en clave crítica y disidente. Aborda discusiones sobre las transformaciones digitales, los algoritmos, los desarrollos tecnológicos vertiginosos y los multiterritorios donde habitan el aprendizaje y la enseñanza.

Esta obra se propone revisitar el campo de la didáctica desde los
aportes de un grupo de referentes y especialistas que interrogan, de manera implícita o explícita, el estatus epistemológico de la disciplina, en escenarios polifónicos y en el marco de profundas transformaciones sociales y educativas.

Los atravesamientos tecnológicos, la expansión digital y las propuestas híbridas cada vez más presentes en la enseñanza de nivel superior dan cuenta de la necesaria reconceptualización y revisión del campo de la didáctica y de las encrucijadas y tensiones entre la didáctica y la tecnología en los nuevos escenarios educativos.

Las indagaciones que componen este libro se proponen explorar
algunas cuestiones que suponen opciones no instrumentales en los
vínculos entre la didáctica y la tecnología y que plantean desafíos importantes para pensar la enseñanza. Al involucrar aspectos sociales, culturales, políticos, epistémicos y comunicacionales, el análisis reclama un debate profundo acerca de los sentidos y las posibilidades de creaciones educativas en diálogo con atravesamientos tecnológicos cada vez más complejos.

La didáctica, tradicionalmente vinculada con propuestas de enseñanza articuladas con diseños curriculares más o menos prescriptivos, se ve interpelada por los entornos expansivos, las nuevas formas de corporeidad, las promesas, las oportunidades y las constantes demandas de la cultura digital. Esta mirada requiere de posicionamientos críticos, fundamentados y reflexivos para llevar adelante adaptaciones o cambios en los modos de concebir los espacios de enseñanza y de aprendizaje con fuerza epistemológica y comprometidos con lo social.

The proliferation of artificial intelligence (AI) technologies and chatbots has the potential to significantly reshape higher education. It is now imperative for stakeholders in this sector to grasp the fundamental aspects of AI technologies and understand their implications. This paper not only introduces basic AI concepts but also explains their specific applications and relevance in the higher education context. Moreover, it outlines the prospects of using AI technologies and chatbots to boost student engagement, presenting a synthesis of the opportunities available. Concurrently, we discuss the concerns and challenges associated with integrating AI into higher education settings. Several articles included in this special issue explore these opportunities and challenges from diverse viewpoints and within various contexts, across countries such as Australia, the United Kingdom, Vietnam, Cyprus, and GCC nations. Finally, we propose several avenues for future research aimed at enhancing student engagement through AI, charting a path forward for empirical evidence and practical application of AI and chatbots in enhancing student engagement.

When Generative AI (a version of artificial intelligence that focuses on creating new content) rapidly became more prevalent in educational settings, it sparked fear and skepticism among some educators. Many saw it primarily as a high-tech cheating tool, a way for students to outsource their thinking and writing. But as the dust settled, a more nuanced and exciting possibility emerged: AI as a powerful tool to enhance students’ metacognition—the ability to think about one’s own thinking processes.

US Universities are engaging with AI in ways beyond anything I see in the UK, Europe and elsewhere. I’ve written about Harvard before but Yale seems like the strongest in intent, widest in access and deepest in enabling research, teaching and learning. Well funded at $150 million, they understand the need for the necessary IT infrastructure.

What really matters is top-down management intent. Scott Strobel has been the Provost of Yale since 2020. As a successful science researcher and Caltech graduate he understands the technology and has sought, through his Yale Task Force on Artificial Intelligence, recommendations that were delivered in June. It has taken only two months to get a plan and funding in place. That is impressive.

How does the introduction of AI into the process of teaching and learning impact the day-to-day work of Instructional Designers (IDs) at ASU? And what does this tell us about the “post AI” ID role?

Based on the experiments that are happening at ASU, I put together a list of the impact on the role and skills of instructional designers. This provides an insight into the day to day work of IDs at ASU right now and a reliable glimpse into the very-near “post AI” future of Instructional Design.

When Generative AI (a version of artificial intelligence that focuses on creating new content) rapidly became more prevalent in educational settings, it sparked fear and skepticism among some educators. Many saw it primarily as a high-tech cheating tool, a way for students to outsource their thinking and writing. But as the dust settled, a more nuanced and exciting possibility emerged: AI as a powerful tool to enhance students’ metacognition—the ability to think about one’s own thinking processes.

David Game College in London, UK, is planning to allow students around the age of 15 to use AI tools before taking standardized exams next year. This initiative, despite concerns from experts about the limitations of AI compared to human teachers, aims to support both students who struggle to keep up and those who excel.

According to co-principal John Dalton, the pilot project will leverage AI-powered adaptive learning, enabling each student to learn at their own pace. Dalton highlights the benefits of this approach, as it addresses the issue of traditional classroom settings where the pace may be too fast for some and too slow for others.

Educators face many challenges, from heightened concerns over student mental health, longstanding issues surrounding teacher pay, and a growing debate on the use of AI in education. To learn more about global education, as well as how educators are thinking about these issues and their impact on student success, Morning Consult, on behalf of McGraw Hill, surveyed over 1,000 PreK-12 and Higher Education educators in 19 countries across the globe. The findings offer a glimpse into potential solutions to help overcome barriers to student success – and how classroom technology can be deployed most effectively to help students achieve the best possible outcomes around the world.