True experiments are a critical research methodology because the sample groups must be assigned randomly between control or experimental groups, and all variables except the one being studied are controlled, in order to best determine causality. We’re designing true experiments that explore prescriptive questions about the ways the technology should be deployed as an instructional tool — this is a key element of advancing teaching and learning in higher ed. When it comes to investigating generative AI tools through an SoTL Research framework, essential questions combine elements that are discipline specific with more general considerations of the student experience.

In the denouement of the COVID-19 pandemic, talk of a return to “normalcy” in higher education belies the great challenges and
ongoing disruptions that yet lie ahead for many institutions. Public perceptions of the value of postsecondary education continue
their downward slide, placing institutions in the position of having to demonstrate their worth and find solutions to declining
enrollments. Data and analytics capabilities continue to evolve, introducing new opportunities and new risks to the institution. Chief among these capabilities, Generative AI promises to change teaching and learning in ways many of us have yet to fully understand or prepare for.

For this year’s teaching and learning Horizon Report, expert panelists’ discussions highlighted and wrestled with these present and looming challenges for Higher Education. This report summarizes the results of those discussions and serves as one vantage point on where our future may be headed. This project was grounded in a modified Delphi methodology that seeks to elevate the collective perspectives and knowledge of a diverse group of experts, and the panelists’ activities were facilitated using tools adapted from the Institute for the Future.

GenAI can democratize Education, tailor learning experiences to individual needs and bridge disparity gaps, giving it potential as an immense and versatile student success tool. But educators must take the helm of research and development, steering the integration of AI with intention and expertise. Following are six areas around which to focus action.

In a world where knowledge is power and innovation drives progress, the role of universities in society stands at a pivotal crossroads. The traditional image of ivory towers of academia is changing as we navigate the complexity of the 21st century. Today, universities are not only centers of learning and research but dynamic hubs of innovation, collaboration and societal impact.

Have you ever wondered how your brain creates thoughts or why something randomly popped into your head? It may seem like magic – but actually the brain is like a supercomputer inside your head that helps you think, learn and make decisions.

Imagine your brain as a busy city with lots of streets and buildings. Each part of the brain has a specific job to do, just like certain areas of a city or certain buildings serve different purposes. When you have a thought, it’s like a message traveling through the city, passing from one area to another.

What do neurons use this special ability for? The answer to the question may lie in the theoretical findings shown in Naud’s paper, “Burst-dependent synaptic plasticity can coordinate learning in hierarchical circuits”, published three years ago in Nature Neuroscience. In this paper, Naud’s team examined how the ability to communicate and process two signals at once can solve a dilemma about how learning takes place in the brain.

As artificial intelligence tools continue to evolve, their potential to transform academic research is becoming increasingly apparent. From facilitating comprehensive literature reviews and identifying hidden research gaps to analyzing massive datasets and visually presenting complex information, AI is empowering researchers to tackle tasks once thought insurmountable.

Amidst the excitement and promise of this new frontier, it is crucial to acknowledge the challenges and ethical considerations it presents.

A recent study shows that almost half (49%) of college students are using general purpose GenAI writing tools such as ChatGPT.  

However, despite students increasingly turning to these GenAI tools, they remain apprehensive when it comes to using them for learning. A recent global student survey shows that only 4% of U.S. students said they turn to GenAI first when stuck on a concept or assignment.

La autorregulación en la educación disruptiva se refiere a la capacidad de los estudiantes para regular y controlar sus propios procesos de aprendizaje de manera independiente. En el contexto de la inteligencia artificial (IA) en la transformación universitaria, esto implica el uso de tecnologías de IA para personalizar y adaptar la experiencia educativa a las necesidades individuales de los estudiantes.

La autorregulación en los procesos de investigación en la Universidad del siglo XXI puede ser potenciada mediante el uso estratégico de la inteligencia artificial (IA) y otras tecnologías disruptivas:

Turnitin referenced a study conducted in Spring 2023 it contributed to with Tyton Partners, showing academic cheating as the number one concern of educators, as high numbers of students revealed they were "likely or extremely likely to use generative AI writing tools, even if they were prohibited."

The study also showed that 97% of academic institutions were woefully unprepared to deal with the issue — only 3% had developed a policy about it.

Por un lado, encontramos una corriente que idealiza y sobredimensiona el potencial de la tecnología, considerándola como la solución mágica que resolverá todos los desafíos y problemas que enfrenta la educación en la actualidad. Pero, por otro lado, también existen voces que rechazan completamente la incorporación de la tecnología en los procesos de enseñanza y de aprendizaje, argumentando que socava los métodos tradicionales y el rol fundamental del docente.

¿Es posible encontrar un equilibrio entre estas visiones extremas? ¿Cómo podemos aprovechar el potencial transformador de la tecnología sin caer en su idealización o demonización? ¿Qué enfoque debemos adoptar para integrar la tecnología de manera efectiva y complementaria en la educación?

La inteligencia artificial (IA) y la inteligencia humana difieren en varios aspectos clave. En el ámbito educativo disruptivo, estas diferencias son fundamentales para comprender cómo se pueden integrar de manera efectiva.

Podemos encontrar una serie de disparidades entre ellas así como su aplicación en la educación disruptiva:

En una universidad que adopta un enfoque de educación disruptiva y utiliza inteligencia artificial (IA), la carga cognitiva desempeña un papel crucial en el proceso educativo. La carga cognitiva se refiere a la cantidad de esfuerzo mental requerido para completar una tarea o actividad de aprendizaje.

En este contexto, la IA se emplea para personalizar la experiencia educativa de cada estudiante, lo que implica adaptar el contenido del curso, los recursos y las actividades según las necesidades individuales y preferencias de aprendizaje. Esto busca reducir la carga cognitiva al proporcionar un enfoque más centrado y relevante para cada estudiante, optimizando así su capacidad de absorción y retención de información.

The problem is not that universities are lacking in innovation, but rather that they suffer from a poverty of imagination of what that innovation might be. “This is an existential moment for universities,” writes the philosopher of higher education Ronald Barnett. “All systems of higher education across the world are moving inexorably in the direction of the marketized university. Consequently, the pool of ideas through which the university is comprehended is shrinking.” Indeed, the main existential crisis facing the university is a poverty of ideas about what universities can become. We must look elsewhere, more broadly and with greater imagination, for potential sources of innovation. 

The digital environment has become an integral aspect of children’s lives. It offers many opportunities such as enhancing educational opportunities, expanding social interactions and having fun. However, the digital environment also exposes children to risks such as cyberbullying, the viewing of violent and other inappropriate content, sexual exploitation and abuse and breaches of privacy. Much current debate also centers on concerns that digital technologies can detract from human interaction and reduce the quality of children’s social and emotional experiences.

All of these issues have fueled concerns from parents, teachers, governments and young people themselves that digital technologies and social media may be exacerbating feelings of anxiety and depression, disturbing sleep patterns and distorting body image. As we integrate new digital technologies into education, we must acknowledge the challenges and complexities that arise. As stated in the OECD Recommendation on Children in the Digital Environment, it is crucial to establish conditions for a safe and beneficial digital environment. Education systems have a vital role in supporting children to navigate the risks while reaping the benefits.

In two major studies in Denmark, experts in computer science and in the sociology of science are exploring how researchers are using generative AI – and how rapidly evolving AI tools might change ways in which scientific knowledge is produced and diffused.

The research will map the growing influence of AI on science and how AI technology is spreading across scientific communities. And it will analyse AI’s impacts currently and in the future. It will combine computational social science methods with controlled experiments.

There are at least four very serious scholarly papers that tested these “AI Detectors” and found they are completely ineffective. However, the worst thing about them is not that they don’t work, It is that they are prone to flagging our most vulnerable students as cheaters! In GPT detectors are biased against non-native English writers, by Weixin Liang, Mert Yuksekgonul, Yining Mao, Eric Wu, James Zou and published in Liang, Weixin in the publication arXiv in July 2023, they showed that:

It’s also somewhat eclipsed conversations about the ethics of how these tools are implemented, according to one observer. Nevertheless, teachers are already deciding how — or even whether — to adopt these tools into the classroom. And the decisions those teachers make may be influenced by factors like how familiar they are with the technology or even what gender they are, according to a new study.

La inteligencia artificial (IA) está redefiniendo las estructuras de enseñanza y aprendizaje que conocíamos. Este cambio no se limita a la incorporación de nuevas herramientas tecnológicas en el aula, sino que se extiende a cómo concebimos la educación y su capacidad para adaptarse a las necesidades individuales de cada estudiante.

La promesa de la IA en la Educación es doble: personalización a gran escala y democratización del acceso al conocimiento. El aprendizaje marca el comienzo de una era donde la educación para el futuro se vuelve más inclusiva, adaptativa y eficaz.

Recently, we announced several expansions for education audiences. Microsoft Copilot with commercial data protection is available to all faculty and higher education students ages 18 and above. And, Copilot for Microsoft 365 eligibility will now include education faculty and staff.  

Our efforts are guided by our Responsible AI principles and standard and build on decades of research on grounding and privacy-preserving machine learning. Additionally, our Customer Copyright Commitment means education customers can be confident using our services and the output they generate without worrying about copyright claims. We look forward to exploring the potential for these offers in education, iterating and improving, and supporting all education organizations in the era of AI.

No conozco a nadie que afirme que el sistema educativo es maravilloso y que no hay que cambiarlo en nada. Pero sí conozco a demasiados que se niegan por principio a introducir tecnología en él, supongo que por miedo a «desvirtuarlo». ¿Cuáles son esas supuestas «virtudes» que pretenden proteger? ¿No llevamos ya suficiente tiempo comprobando los efectos de prácticamente no cambiar nada, o simplemente introducir tecnología sin cambiar para nada la metodología más que de manera cosmética? ¿No deberíamos cambiar de estrategia y dar la oportunidad a los que creen que se pueden introducir muchos elementos nuevos en la educación para intentar adaptarla al contexto tecnológico y al papel que esa tecnología juega en la sociedad?

La IA ha demostrado ser excepcionalmente competente en la imitación de estilos de escritura y la generación de textos coherentes. Modelos de lenguaje como GPT de OpenAI pueden generar respuestas y contenidos que se alinean estrechamente con las instrucciones proporcionadas, haciéndolas herramientas valiosas en campos como el periodismo, la creación de contenido web y la asistencia académica. Estas capacidades permiten a la IA realizar tareas de redacción voluminosas o repetitivas, liberando a los humanos para enfocarse en aspectos más creativos y analíticos de la escritura.