TALENT (Teaching And Learning ENhanced by Technologies) will work mainly on three scientific axes in the field of Computer Environments for Human Learning:

Axis 1: HLEs to support active learning

Research activities in this area focus on the design and implementation of digital environments to enhance learning, but also on their evaluation in authentic learning situations. Our research focuses on how to support active pedagogical methods, which aim to maximize learners’ engagement in the learning process. In particular, our studies aim to promote deeper learning through the use of visualizations and reflection tools, methods such as peer teaching and confrontation, or exploratory approaches based on the development of practical activities.

Axis 2: Learning analysis for personalized and self-managed learning

The main objective of this research axis is to study how learning data can be exploited to support teaching and learning processes. Innovative methods and mechanisms are explored to design useful technological solutions for teachers and students, where big data methods and techniques are used to provide effective tools and systems. The overall goal is to:

• track the user experience in digital educational environments,
• apply data mining techniques (e.g., process/pattern mining) to identify successful learning patterns based on learner behaviors, and
• develop intelligent capabilities to guide learners through tasks based on knowledge inferred from successful behavioral patterns.

Axis 3: Digital skills and development for the future

This axis investigates the skills that teachers, students, and institutions should develop to adapt to future educational challenges. The type of research questions posed in this area are: how to support these competencies and how to transform educational institutions to achieve them.