This research area investigates several aspects related to the design, implementation, use and evaluation of technologies (Internet-based, mobile and other devices) to support learning and teaching processes.
One of the main issues in this line of research is which are the most appropriate technologies and how can they support different pedagogical approaches. This includes the study of the mechanisms and strategies used by learners to communicate and collaborate with peers and tutors in an online learning context. The use of techniques and methodologies from artificial intelligence and machine learning areas for modeling learners' behavior is also considered.
Keywords:
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Thesis Poposals |
Reserchers |
Research Group |
Keywords |
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Technology for learning oral language and reading
Reading is a fundamental academic skill that serves as the foundation for most forms of learning. However, the acquisition of reading skills relies heavily on the development of oral language abilities during the preschool years. This doctoral research aims to design, develop and evaluate a technology-based intervention programme to enhance key oral language components – namely phonics, phonological awareness, vocabulary and morphosyntax – in preschool children identified as being at risk for reading disabilities
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Dr Llorenç Andreu Barrachina landreub@uoc.edu |
GRECIL |
Language intervention,
Early literacy,
Educational technology
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Advanced technology for early children's learning research.
In this interdisciplinary research line, we study children’s interactions with educational technology and how these interactions are influenced by the pupil’s age and developmental progress. From the fields of psychology, education and child-computer interaction, the questions we address are: How can technology be used as an educational resource with young children? And how can we improve interactive and digital content to make it age-appropriate? To answer these questions, we study the spontaneous interactions of young children with digital educational games, robots, AItoys and apps in educational contexts, applying innovative methods, and addressing ethical issues for research using advanced technology with children.
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lcrescenzi@uoc.edu
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ChildTech Lab | child-computer interaction, advanced technology; early children learning |
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Emotional and behavioral research with children in collaborative learning settings
In order to improve our understanding of students' socio-emotional behavior in educational settings, we aim to explore the interface between learning and emotions by examining children's interactions in collaborative learning settings. What is the potential impact of collaborative play and learning with digital content? We will explore cutting-edge applications of AI using mixed methods research with three- to six-year-old children in an efficient, ethical and unobtrusive way.
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lcrescenzi@uoc.edu
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ChildTech Lab |
collaborative learning, socio-emotional behaviour; child-computer interaction I
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ICT for learning about the sciences and engineering
Experimental sciences in general – and physics in particular – are usually a very challenging courses for students and teachers, and even more in an e learning environment. How can a graphic or an idea be shown and explained? How can a question regarding a specific point of a drawing be addressed? How can we perform an experiment? |
Dr Antoni Pérez Navarro |
eHealthLab | sciences learning, physics |
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Artificial Intelligence and Personalized Learning in Mathematics Education
This research line explores how artificial intelligence can support mathematics learning through personalized adaptations and automated feedback in digital environments. The aim is to identify models capable of adjusting content and activities based on students' interaction data, enhancing conceptual understanding, autonomy and motivation. The research will also address the pedagogical and ethical implications of automated personalization, as well as the evolving role of teachers in these new learning contexts.
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Dr Teresa Sancho Vinuesa
Dr Marc Guinjoan Francisco |
LAIKA |
artificial intelligence, personalized learning, automated feedback, mathematics
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Potentialities of artificial intelligence in STEM
This research line focuses on the rapidly evolving field of artificial intelligence (AI) and its transformative potential impact on education. Given that technology is shaping the way we learn, teach and access information, this research aims to explore the full range of possibilities AI offers in educational contexts, particularly online higher education, through case studies. Four subareas are contemplated: personalized learning, intelligent tutoring systems, AI-driven intervention design, and automation of assessment and grading.
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Dr Teresa Sancho Vinuesa
tsancho@uoc.edu
Juan Antonio Martínez Carrascal
jmartinezcarra@uoc.edu
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LAIKA | artificial intelligence; STEM education; assessment |
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Online Collaborative Learning for Mathematical Problem Solving
This proposal investigates how digital collaborative environments can foster joint problem solving in mathematics. It will analyse the use of tools such as forums, shared documents and synchronous platforms to understand which collaboration structures and interaction types best promote mathematical reasoning and communication. The research will also examine the teaching skills required to design and facilitate collaborative learning in online or hybrid settings.
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Dr Teresa Sancho Vinuesa
Dr Marc Guinjoan Francisco |
LAIKA |
collaborative learning, problem solving, peer interaction, mathematics |
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Use Technology to Support Adaptive and Significant Teaching and Learning Experiences
Take advantage of technology to create personalized, meaningful and adaptive teaching and learning experiences. It emphasizes design, prototyping and integration of advanced technologies, such as conversational agents, adaptive learning environments and personalized feedback systems. The objective is to improve the commitment and the results of both students and teachers, ensuring an ethical and effective implementation (focus on instruments).
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Dr Montse Guitert
Dr Josep M. Duart Dr Gizéh Rangel-de Lázaro grangel@uoc.edu
Dr Teresa Romeu
Dr Albert Sangrà
Dr Lourdes Guàrdia
Dr Marcelo Fabián Maina
scaballe@uoc.edu
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immersive education; XR technologies; virtual reality; augmented reality, GenAI, learning analytics
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Use of GenAI (Generative Artificial Intelligence) for Teaching, Learning, and Assessment in Primary and Secondary Education
This research line examines the educational potential of GenAI (generative artificial intelligence) in the context of primary and secondary education. It investigates how GenAI-based tools can enhance teaching, learning and assessment processes by fostering innovation, personalization and critical engagement with technology.
Examples:
• Teachers: The use of GenAI to support instructional design, enrich classroom practices and inform formative and summative assessment strategies.
• Students: The use of GenAI to facilitate learning, promote the creation of meaningful learning artefacts and develop metacognitive awareness and self-regulated learning.
Through this line of inquiry, the research aims to contribute to a deeper understanding of how GenAI can be integrated responsibly and effectively into educational practice.
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Investigadors independents
SINTE (UAB)
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Generative Artificial Intelligence (GenAI); Teaching, learning, and assessment; Primary and Secondary Education
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Intelligent Technologies for Supporting Collaboration and Innovation in Digital Higher Education
This research explores how artificial intelligence and educational technologies can enhance collaborative learning and pedagogical innovation in higher education. It investigates AI-driven tools to support communication, feedback and learner modelling, aiming to design more adaptive, inclusive, and effective digital learning environments.
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ajony@uoc.edu
eserradell@uoc.edu
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MeL |
artificial Intelligence, collaborative learning; educational innovation
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Ethical issues in ICT
Social, educational and ethical implications of emerging ICT.
STEM Education (science, technology, engineering, and mathematics) for the promotion of gender inclusion and equity in the information society.
Sustainable and responsible research and innovation in ICT.
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aornellas@uoc.edu
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NODES |
ethics & ICT; STEM education; gender perspective
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Critical Perspectives on Digital Coloniality and Algorithmic Bias in Education
This research line critically investigates the phenomenon of digital coloniality, examining how algorithmic and artificial intelligence (AI) systems replicate and automate historical structures of power and cultural hegemony within digital learning environments. The focus is on analysing the mechanisms through which these systems codify existing biases, leading to the epistemic marginalization of non-Western cultures, local knowledge systems and diverse epistemologies. Ultimately, this line seeks to understand the impact of algorithmic governance on educational equity and autonomy, questioning the perceived neutrality of digital tools and advocating for frameworks that promote data sovereignty and epistemic justice in online education.
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aornellas@uoc.edu
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NODES |
data coloniality, epistemic justice, algorithmic bias
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