We develop a large number of software tools and hosting infrastructures to support the research developed at the Department. We will be detailing in this section the different tools available. You can take a look for the moment at the offer available within the UPF Knowledge Portal, the innovations created in the context of EU projects in the Innovation Radar and the software sections of some of our research groups:


 Artificial Intelligence

 Nonlinear Time Series Analysis

 Web Research 


 Music Technology

 Interactive  Technologies

 Barcelona MedTech

 Natural Language  Processing

 Nonlinear Time Series  Analysis


Wireless Networking

Educational Technologies




Back Educational Data Science

Educational Data Science

Educational Data Science

During recent years, analytics or data mining techniques have been used to extract actionable information from large data quantities in an increasing variety of scientific fields. In the context of education, the use of technology to mediate activities in learning environments allows the collection of large data sets about student interactions. The area of learning analytics and educational data science have emerged to explore how this data can be used to increase the understanding and quality of learning experiences. The field has undergone a fast expansion phase and the use of data is now being considered in aspects such as for example student retention. Recent detailed analysis of the use of data in learning environments show an increasingly complex landscape influenced by multiple disciplines to deploy effective initiatives. Existing models however do not pay the deserved attention to the connection between analytics and learning design. The integration of learning analytics with learning design has been identified as important.


However, a tight integration of data analytics in learning designs has not yet been exploited to its full potential. The vision is the overall research program of the PI aims at articulating the variety and connections at various levels (community, design and implementation layers, see figure) between data obtained from students’ and teachers’ actions and the creation and implementation stages of “learning designs”.


Learning Design is the field studying how teachers can model potentially effective learning activities using computational representations interpretable by software systems. Computational representations of learning designs also enables the automatic analysis, reuse and sharing of the modelled learning activities. Previous research by the PI has been focused on Learning Design, with the Integrated Learning Design Environment (ILDE, http://ilde.upf.edu/about) as a remarkable achievement in terms of developed infrastructure to enable the modelling and sharing of learning designs. ILDE is a Community Environment that integrates a number of learning design conceptualization, authoring and implementation tools.


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