Track 05. Learning Analytics – Reconnecting Data, Theory, and Action

Learning Analytics has been part of the educational research landscape for more than a decade. During this time, the field has grown in scope, methods, and areas of application. Data is easier to collect, analytical techniques are more accessible, and learning analytics tools are increasingly present in educational institutions. However, wider adoption has not always gone hand in hand with clearer educational purpose.
A recurring issue in recent years has been the growing distance between analytical work and learning itself. While technical progress is necessary, Learning Analytics risks becoming disconnected from learning theory, instructional decisions, and educational practice if analysis is treated as an end rather than as a means. Models, indicators, and dashboards only become relevant when they help learners, teachers, and institutions understand learning processes and act on that understanding.
This 14th edition of the Learning Analytics track invites contributions that address this tension directly. Building on the trajectory of previous editions, this track seeks work that places learning and teaching processes at the core of the learning analytics process. We are particularly interested in studies that make explicit connections between data, theory, interpretation, and action, and that reflect on how learning analytics is used, understood, and acted upon in real contexts.
As in previous editions, this track remains open to different perspectives and methods. We welcome theoretical contributions, empirical studies, methodological work, and reflective analyses, as long as their relevance to learning and teaching is clearly articulated and grounded.

Topics

Submissions may address, but are not limited to, the following topics:

• Educational research and Learning Analytics
• Learning Analytics and instructional design
• Competence-based Learning Analytics
• Learning Analytics and self-regulated learning
• Learning Analytics in collaborative and team-based learning
• Multimodal Learning Analytics
• Learning Analytics for Personal Learning Environments (PLEs)
• Academic and institution-focused Learning Analytics
• Interoperability and standards for Learning Analytics
• New approaches and methods in Learning Analytics, when clearly connected to learning processes
• Replication, cross-validation, and longitudinal studies in Learning Analytics
• Success stories and case studies reporting the use of Learning Analytics in practice
• Ethical aspects of Learning Analytics, including data protection, responsibility, and governance

In line with current discussions within the Learning Analytics community, this edition also encourages contributions that explore directions that are becoming increasingly relevant for the field, including:

• Human-centred and participatory approaches to the design of Learning Analytics
• Explainable and interpretable models that support understanding rather than prediction alone
• Learning Analytics for feedback, reflection, and decision-making by different stakeholders
• Closing the loop between data analysis and educational action
• Learning Analytics in AI-supported and hybrid learning environments, with attention to how analytics is used
• Equity, fairness, and learner well being in Learning Analytics practices

Track Scientific Committee

Agustín Carlos Caminero-Herráez, Universidad Nacional de Educación a Distancia, Spain
Ainhoa Izaro Álvarez Arana, Universidad del País Vasco / Euskal Herriko Unibertsitatea, Spain
Alejandra Martínez-Monés, Universidad de Valladolid, Spain
Ana Isabel Jiménez-Zarco, Universitat Oberta de Catalunya, Spain
Antonio Balderas Alberico, Universidad de Cádiz, Spain
Antonio Fumero-Reverón, Universidad Politécnica de Madrid, Spain
Antonio Robles-Gómez, Universidad Nacional de Educación a Distancia, Spain
Camino Fernández-Llamas, Universidad de León, Spain
Carlos Cuenca-Enrique, Universidad Politécnica de Madrid, Spain
David Griffiths, Universidad Internacional de la Rioja, Spain
Daniel Amo-Filvà, Universidad de la Salle, Spain
Emiliano Acquila-Natale, Universidad Politécnica de Madrid, Spain
Gustavo Ribeiro Alves, Instituto Politécnico do Porto, Portugal
Ionuț Dorin Stanciu, Universitatea Tehnică din Cluj-Napoca, Romania
Juan Antonio Martínez-Carrascal, Universidad Politécnica de Madrid, Spain
Juan Cruz-Benito, IBM Quantum Research, USA
Julián Chaparro-Peláez, Universidad Politécnica de Madrid, Spain
Laura Del-Río-Carazo, Universidad Politécnica de Madrid, Spain
Manuel Caeiro-Rodríguez, Universidade de Vigo, Spain
Manuel Freire-Morán, Universidad Complutense de Madrid, Spain
María Arcelina Marques, Instituto Politécnico do Porto, Portugal
Martín Liz-Domínguez, Universidade de Santiago de Compostela, Spain
Mikel Larrañaga, Universidad del País Vasco / Euskal Herriko Unibertsitatea, Spain
Milos Milovanovic, Univerzitet u Beogradu, Serbia
Miroslav Minovic, Univerzitet u Beogradu, Serbia
Mohammed Saqr, University of Eastern Finland, Finland
Nic Nistor, Ludwig-Maximilians-Universität München, Germany
Pedro José Muñoz-Merino, Universidad Carlos III, Spain
Pedro Manuel Moreno-Marcos, Universidad Carlos III, Spain
Rebeca Cerezo-Menéndez, Universidad de Oviedo, Spain
Ruth Cobos, Universidad Autónoma de Madrid, Spain
Salvador Ros-Muñoz, Universidad Nacional de Educación a Distancia, Spain
Santiago Iglesias-Pradas, Universidad Politécnica de Madrid, Spain
Sonsoles López-Pernas, University of Eastern Finland, Finland
Teresa Sancho, Universitat Oberta de Catalunya, Spain

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