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    Research conversation with CLEHN Lab
    (GRIAL reserarch group, 2025-05-16) García-Peñalvo, Francisco José; Rodríguez-Conde, María José
    Research coversation with Le Laboratoire Communication, Linguistique, Éducation et Humanités (CLEHN) of the Mohamed Premiere University at Oujda.
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    Workshop about developing educative scenarios with GenAI tools
    (Zenodo, 2024-06-12) García-Carrasco, J.
    The document outlines a workshop designed for Master’s students in ICT applied to education at the University of Salamanca. Led by Francisco José García-Peñalvo, the workshop aims to explore the application of generative AI (GenAI) tools like ChatGPT in education. The objectives include learning to integrate GenAI in teaching, reflecting on its potential and risks, and designing educational scenarios collaboratively. The eight-hour session is part of a course on "Design and Assessment of Digital Resources." Students, mostly with educational backgrounds, engage in a structured process involving an introduction, AI-focused discussions, and hands-on sessions with ChatGPT. Teams of three work to develop and present educational scenarios using GenAI. Examples of tasks include creating stories for primary school, designing gamified learning activities, or developing subject-specific assessments. The emphasis is on the process over the final product. Teams document prompts and workflows and present findings to facilitate peer discussion on lessons learned, focusing on benefits and challenges. Key takeaways stress the importance of an initial introduction to GenAI, collaborative work, and reflection. The workshop highlights the transformative potential of GenAI in education while advocating for critical engagement with its ethical and practical implications.
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    Embracing GenAI literacy in education: A roadmap for empowerment
    (Zenodo, 2024-06-12) García-Peñalvo, Francisco José
    The paper discusses the emergence of Generative Artificial Intelligence (GenAI) as a transformative force in education and the necessity of GenAI literacy for both educators and students. GenAI literacy involves understanding generative AI systems, their societal impacts, and ethical implications. It encompasses skills ranging from basic knowledge of how these systems work to critical evaluation and innovative application. For teachers, fostering GenAI literacy requires integrating GenAI concepts into existing curricula without overhauling them, organizing professional development workshops with hands-on training, and forming collaborative learning communities to share best practices. For students, the focus should be on developing critical thinking and ethical reasoning skills, engaging in active-based learning using GenAI tools, and promoting interdisciplinary approaches that span STEM, humanities, and social sciences. The paper argues that GenAI literacy is not limited to mastering tools but also involves cultivating a critical perspective on technology’s role in society. By emphasizing complex thinking competencies, it aims to prepare future generations for AI-augmented environments. This literacy is positioned as a cornerstone for responsibly harnessing AI’s potential and addressing challenges like bias, privacy, and intellectual property. Ultimately, the paper presents a roadmap for empowering individuals and institutions to navigate and shape the evolving AI landscape responsibly and innovatively. It underscores the importance of equipping society with the knowledge and skills necessary to engage meaningfully with one of the most influential technologies of the 21st century.
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    Generative Artificial Intelligence in Education: From Deceptive to Disruptive
    (Universidad Internacional de la Rioja, 2024-03-12) Alier, M.; García-Peñalvo, F. J.; Camba, J. D.
    Generative Artificial Intelligence (GenAI) has emerged as a promising technology that can create original content, such as text, images, and sound. The use of GenAI in educational settings is becoming increasingly popular and offers a range of opportunities and challenges. This special issue explores the management and integration of GenAI in educational settings, including the ethical considerations, best practices, and opportunities. The potential of GenAI in education is vast. By using algorithms and data, GenAI can create original content that can be used to augment traditional teaching methods, creating a more interactive and personalized learning experience. In addition, GenAI can be utilized as an assessment tool and for providing feedback to students using generated content. For instance, it can be used to create custom quizzes, generate essay prompts, or even grade essays. The use of GenAI as an assessment tool can reduce the workload of teachers and help students receive prompt feedback on their work. Incorporating GenAI in educational settings also poses challenges related to academic integrity. With availability of GenAI models, students can use them to study or complete their homework assignments, which can raise concerns about the authenticity and authorship of the delivered work. Therefore, it is important to ensure that academic standards are maintained, and the originality of the student's work is preserved. This issue highlights the need for implementing ethical practices in the use of GenAI models and ensuring that the technology is used to support and not replace the student's learning experience.
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    Generative Artificial Intelligence in Higher Education: A 360° Perspective
    (Grupo GRIAL, 2024-01-23) García-Peñalvo, F. J.
    Keynote at the IFE Conference Special Event; Artificial Intelligence in Education Summit, held in the context of the IFE Conference 2024, Tecnológico de Monterrey, Monterrey, Mexico, January 23-25, 2024. Generative Artificial Intelligence (GenAI) has become a focal point in the higher education landscape. This innovative approach promises to revolutionize how students learn, teachers teach, and educational institutions evolve. In this conference, we will explore how GenAI affects different actors in the educational field, from teachers and students to decision-makers and technology development experts. The pros and cons will be analyzed from each actor's perspective for a comprehensive and holistic view. We will also discuss the ethical and social challenges of incorporating these technologies, such as data privacy and equity in access to advanced educational resources. From the perspective of the teaching staff, how GenAI can be a tool to enrich course content and offer more interactive and engaging teaching methodologies will be addressed. On the other hand, the impact of this technology on institutional decision-making is examined, with a special emphasis on curriculum planning and resource management. This conference aims to provide a comprehensive understanding of how GenAI is shaping the future of education, looking at all the stakeholders involved in this transformative process. The presentation is also available in Spanish.
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    Generative Artificial Intelligence: New Scenarios in Teaching, Learning, and Communication
    (Grupo GRIAL, 2023-09-06) García-Peñalvo, F. J.
    Keynote at the VIII Congreso Internacional de Estudios sobre Medios de Comunicación, held in Universidad Complutense de Madrid on September 6th, 2023. In recent years, the landscape of Artificial Intelligence (AI) has witnessed a seismic shift with the emergence of Generative Artificial Intelligence (GenAI). This keynote explored the ground-breaking applications of GenAI in reshaping the arenas of teaching, learning, and communication. The historical trajectory of AI, from its inception to its current pinnacle, has been meteoric. Traditional AI models, mainly rule-based and deterministic, have evolved into sophisticated generative models capable of creating content that is often indistinguishable from that crafted by humans. Key exemplars in this category include the GPT series and DALL-E from OpenAI. Nevertheless, what exactly is GenAI? Unlike traditional AI models that are primarily reactive, GenAI models can produce new, previously unseen content. Their inherent characteristics enable them to simulate the process of human creation. Algorithms such as Generative Adversarial Networks (GAN), Long Short-Term Memory networks (LSTM), and Transformers stand as a testament to the diversity and capability of generative models. Applying these models transcends sectors, presenting immense opportunities and challenges in equal measure. The sphere of education stands on the cusp of a revolution thanks to GenAI. Personalised learning, a goal long sought by educators, is now a palpable reality. GenAI can tailor educational pathways to fit individual student needs, thus ensuring that no student is left behind. Beyond personalisation, virtual tutoring systems have started to bridge the gap in areas with teacher shortages. Equipped with GenAI, these systems can provide instantaneous feedback, ensuring continual student progress. Content creation, an integral facet of education, has also benefitted from GenAI. GenAI is pivotal in generating reading materials customised to each student’s reading level and formulating challenging questions based on current curricula. Moreover, GenAI fosters creativity among students. Tools equipped with generative models can assist students in crafting art, composing music, or even writing essays, all tailored to their unique style and preferences. Shifting the lens to communication, the potential of GenAI is equally profound. Automated content generation, once a lofty ideal, is now commonplace. News articles, financial reports, and even creative pieces can be produced by GenAI, often at speeds unmatched by humans. Personalised marketing campaigns harnessing the power of GenAI can target potential consumers with unparalleled precision, ensuring maximum outreach and engagement. Real-time translation, a boon in our increasingly globalised world, has seen leaps in accuracy thanks to generative models. Lastly, natural language processing, a subset of GenAI, has augmented human-computer interactions, making them more intuitive and organic. However, with immense power comes immense responsibility. The adoption of GenAI is full of challenges. Ensuring the accuracy and appropriateness of generated content is paramount. We need robust quality control mechanisms to mitigate the risk of misinformation or inappropriate content generation. Moreover, the sheer dependency on machines raises concerns. More reliance on AI could lead to cognitive stagnation in students, thwarting the very purpose of education. Additionally, the scalability of these models, given their intensive processing power and data requirements, is an area of concern. Ethically, the canvas of GenAI is mottled with grey. AI models, reflecting the data they are trained on, can inadvertently perpetuate societal biases. Ensuring these models are equitable and do not further deepen societal divides is crucial. The potential job displacement due to the widespread adoption of GenAI is a looming concern. GenAI takes over tasks once reserved for humans, so we must ensure a just transition for those affected. Lastly, the issue of authenticity remains salient. In a world where distinguishing between human and AI-generated content becomes increasingly challenging, ensuring trust and transparency is paramount. In conclusion, the future illuminated by Generative Artificial Intelligence is both promising and perplexing. As GenAI continues to reshape teaching, learning, and communication paradigms, our collective responsibility is to ensure that its journey is anchored in ethics, equity, and excellence.
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