Scientific axis of TALENT
TALENT will mainly work on 3 scientific axis within the area of Technology-Enhanced Learning:
Axis 1: TEL environments for supporting Active Learning
The research activities in this area focus on the design and implementation of digital environments for enhancing learning, but also on their evaluation in authentic learning situations. Our research investigates how to support active pedagogical methods, whose objective is to maximize the engagement of learners in the learning process. In particular, our studies aim to promote in-depth learning through the use of visualisations and reflective tools, methods such as peer instruction and confrontation of views, or exploratory approaches based on the development of practical activities.
Axis 2: Learning analytics for personalised and self-regulated learning
The main aim of this research line is to study how learning data can be exploited for supporting teaching and learning processes. Innovative methods and mechanisms are explored to design technological solutions meaningful for both teachers and students, where big data methods and techniques are used to provide effective tools and systems. The overall objective here is to
- track the user experience within digital educational environments,
- apply data mining techniques (e.g. process/pattern mining) to identify successful learning patterns based on learners’ behaviors, and
- develop intelligent capacities to guide learners in their tasks based on the knowledge inferred from successful behavioural patterns.
Axis 3: Digital competences and development for the future
This axis investigates the competences that teachers, students and institutions should develop for adapting to future challenges in education. How these competences should be supported and how education institutions should be transformed to do so are the type of research questions posed in this area.