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Item From Ethics to Agency: Participatory Design of a Teacher Training Course for AI in Education(Grupo GRIAL, 2025-09-18) Mouta, AnaArtificial Intelligence is increasingly being integrated into educational settings, yet its ethical implications and impact on pedagogical agency remain underexplored. This thesis investigates the ethical challenges and agency-related concerns in education through an educational design research process, with the aim of developing a teacher training course for K-12 educators, designed through their own voices. The study begins with a systematic literature review (2011–2022), conducted using PRISMA guidelines, which maps the current state of research on AI in education. This phase identifies substantial gaps in ethical frameworks, teacher-specific guidance, and the preservation of educational agency. Building on this foundation, the research adopts a participatory futures methodology, using the Delphi Method to co-construct eight future scenarios. These scenarios explore the socio-technical imaginaries shaping AI's pedagogical implications, including issues of equity, assessment, student voice, and professional autonomy. Subsequent research phases engage teacher educators through iterative focus groups, exploring how AI alters agency dynamics, subjective, intersubjective, and collective, within educational contexts. Findings reveal a pressing need to move beyond dominant techno-solutionist narratives and instead support teachers in reclaiming their roles as ethical and relational agents. These insights inform the co-design of a professional development course, which integrates dialogic, experiential, and reflective learning practices. The course is hosted on a custom-designed Canva platform and structured around a three-layered framework of educational agency, offering educators conceptual and practical tools to critically engage with AI. By foregrounding the symbolic, relational, and ethical dimensions of education, this thesis argues that responsible AI integration must not only be technically sound but also aligned with the core purposes of education: subjectification, qualification, and socialisation. It proposes that sustaining teacher agency requires special attention to the preservation and care of the educational lexicon, one that sustains complexity, openness, ethical discernment, as well as desire and memory in the face of algorithmic pressures. For it is through desire that alternative imaginaries of socio-technical systems and comprehensive educational ecosystems are made possible. This dissertation contributes four main outcomes: (1) a comprehensive ethical mapping of AI in education, (2) a participatory ethical dilemma toolkit, (3) a conceptual framework of agency in AI-mediated education, and (4) a context-responsive, agency-centred professional 8 Ana Mouta. 2025 development course for K–12 educators. Together, these outcomes constitute a theoretically grounded and empirically informed contribution to ongoing scholarly and professional efforts aimed at cultivating educational environments in which decisions regarding the use of AI, and the conditions under which it is integrated, are co-constructed through dialogic, participatory processes that uphold educational purpose, human agency, and the democratic ethos of schooling. It counters the depoliticising and deprofessionalising tendencies of technocratic models by supporting teachers in critically engaging with AI, resisting unreflective automation, and challenging algorithmic normativisation.Item Safe AI in Education Manifesto. Version 0.4.0(2024-10-08) Alier-Forment, Marc; García-Peñalvo, Francisco José; Casañ, María José; Pereira, Juanan; Llorens-Largo, FaraónThe Safe AI in Education Manifesto outlines ethical principles for integrating AI into educational environments. It emphasizes the need for human oversight, ensuring AI complements rather than replaces educators. Decision-making must remain transparent and appealable, protecting the educational process's integrity. Confidentiality is paramount; institutions must safeguard student data and ensure AI systems comply with stringent privacy standards. AI tools should align with educational strategies, supporting learning objectives without enabling unethical practices or adding complexity. The manifesto calls for AI systems to respect didactic practices, adapting seamlessly to instructional designs without burdening educators or students. It stresses accuracy and explainability, requiring AI outputs to be reliable, transparent, and verifiable. Interfaces must be intuitive, communicating their limitations to foster trust and critical engagement. Ethical training and transparency in AI model development are essential, including minimizing biases and disclosing data sources. The manifesto commits to advancing AI’s potential in education while prioritizing privacy, fairness, and educational integrity, providing a living framework adaptable to technological evolution. It can be signed at: https://manifesto.safeaieducation.org/Item Evaluating the Effectiveness of Human-Centered AI Systems in Education(Departamento de Informática y Automática. Universidad de Salamanca, 2024-03-01) Shoeibi, N.; Therón, R.; García-Peñalvo, F. J.This thesis examines how AI can improve human-computer interaction (HCI) and user experience in education. A systematic litera-ture review (SLR) and LATILL case study show how AI can be used in education. The SLR examines existing literature to determine how AI af-fects user experience and HCI in education, highlighting personalization and adaptability of learning experiences, improved task performance, and improved user experience for teachers and students. AI implementation in education faces obstacles. Using CEFR levels and linguistic traits, the LATILL project uses a user-centered design to give students personali-zed guidance and support. It transforms language instruction and fosters engaging and successful learning by encouraging educator collaboration and resource sharing. This study emphasizes the importance of user ex-perience and HCI principles in designing AI-driven educational systems. AI and user-centered design can improve learning, student engagement, and educational outcomes.Item Systematic review of Erasmus+ projects labelled as good practice and related to e-learning and ICT: Some case studies(2023-11-22) Alonso de Castro, M. G.; García-Peñalvo, F. J.This article focuses on the methodology applied for the review of European educational projects, within the framework of Erasmus+, labelled as good practices and that are related to electronic learning or the use of Information and Communication Technologies (ICT) in education. In addition, some of the projects that have passed all the research phases and have proven to be sustainable over time are analyzed. The projects presented represent different educational sectors and propose learning systems through ICT with the involvement of students and/or teachers. As they are good practice projects, the article can contribute both to the use or transfer of the resources developed in these projects, and to be able to inspire new projects in those lines of work. The main factors that have contributed to the success of the projects are their usefulness for the educational community beyond the time of funding, the use of innovative methodologies applied with teachers and students, establishing them in the participating institutions. Another notable fact is the good collaboration and rapport between all the project partners who worked to get common objectives.Item Education and generative artificial intelligence. Open challenges, opportunities, and risks in higher education(Grupo GRIAL, 2023-09-28) García-Peñalvo, F. J.Keynote at the 14th International Conference on eLearning ELEARNING23, held in Belgrade Metropolitan University, Belgrade, Serbia, on September 28th, 2023.Item 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.Item The perception of Artificial Intelligence in educational contexts after the launch of ChatGPT: Disruption or Panic?(Ediciones Universidad de Salamanca, 2023-02-06) García-Peñalvo, F. J.The year 2022 has ended with one of those technological innovations that have a hard-to-predict behaviour, a black swan, hogging the limelight in traditional media and digital media. Indeed, it is ChatGPT. Although artificial intelligence had already been in the news and often masked under various other meanings, the ChatGPT phenomenon has once again brought this discipline and its positive and negative effects on our society to the forefront. Reactions to its launch, influenced mainly by its ease of access and use, have been varied, ranging from the enthusiasm of innovators and early adopters to the almost apocalyptic terror of the Terminator movie. Of the multiple applications of this tool, the most significant debate focuses on its implications in Education and Academia due to its tremendous power to generate texts that could very well pass for human creations. We are at the dawn of a technology that has gone from being a toy tool to bidding to become a disruptive innovation. Whether it succeeds or not will depend on many factors, but if it does not, it will be another one like it. Denying it or banning it will do absolutely nothing to stop the tsunami effect that has already begun. For all these reasons, we must first understand these technologies based on large language models and know their benefits and weaknesses, as well as what they really mean for a specific sector of activity, such as Education. After getting to know the technology and the tool, one would be in a position to use (or not) its potential and to prevent or detect its possible pernicious effects, presumably by changing and adapting processes that are probably profoundly rooted and that, therefore, forced to leave the comfort zone, which is always the cause of resistance to change and extreme reactions. These responses usually will not stop technology from reaching its productivity plateau when it becomes part of the daily life of a sufficient majority of users. This is always the cause of resistance to change and extreme reactions that will not usually stop technology from reaching its productivity plateau when it becomes part of the daily lives of a sufficient majority of users, especially when it is also a question of transversal tools that will spread their usage patterns among the different application domains.Item A systematic mapping about simulators and remote laboratories using hardware in the loop and robotic: Developing STEM/STEAM skills in pre-university education(IEEE, 2021-09-23) Mena Mamani, N.; García-Peñalvo, F. J.; Conde, M. Á.; Gonçalves, J.In recent years and after the strong impact of the last global health emergency (COVID-19) information and communication technologies have had a great impact on society but particular in the teaching-learning process. Education has been impacted at all its levels. Therefore, education models have been to be adapted to this new challenging paradigm by using different tools such as videoconferences, simulations, on-line interactive applications, virtual and remote laboratories, robots, etc. The objective of this work is to elaborate a systematic mapping to know what scientific from its beginning to 2020, identifying the most literature exists regarding simulators, remote and virtual laboratories focused on STEM/STEAM skills development in the educational context. To do so, bibliographical data gathered of four of the most popular and complete electronic databases (ACM, IEEE, Scopus and Web of Science). At the begging we selected 1232 articles after applying the acceptance criteria defined as part of the search and select strategy, we had 61 articles that help us to answer some questions like what are the most popular virtual and remote labs? or what are the current trends and issues of these tools? and the future ones?Item AI-Driven Assessment of Students: Current Uses and Research Trends(Springer, 2020-07-19) Sánchez-Prieto, J. C.; Gamazo, A.; Cruz-Benito, J.; Therón, R.; García-Peñalvo, F. J.During the last decade, the use of AIs is being incorporated into the educational field whether to support the analysis of human behavior in teaching-learning contexts, as didactic resource combined with other technologies or as a tool for the assessment of the students. This proposal presents a Systematic Literature Review and mapping study on the use of AIs for the assessment of students that aims to provide a general overview of the state of the art and identify the current areas of research by answering 6 research questions related with the evolution of the field, and the geographic and thematic distribution of the studies. As a result of the selection process this study identified 20 papers focused on the research topic in the repositories SCOPUS and Web of Science from an initial amount of 129. The analysis of the papers allowed the identification of three main thematic categories: assessment of student behaviors, assessment of student sentiments and assessment of student achievement as well as several gaps in the literature and future research lines addressed in the discussion.