Most of my research lies within the area of learning analytics and educational data mining, where I often collect contextualized data from interactive learning environments and analyze it in order to provide feedback about how to improve learning and the environment where it occurs.
During my PhD, my research focused on three areas: 1) the implementation of algorithms for behavioral modeling, such as to detect cheating, off-task behaviors or gamification interest 2) the development of visual analytics dashboards for MOOC environments 3) applied machine learning for the prediction of learning outcomes.
Currently, my personal work is being focused on 1) conducting large-scale MOOC analytics finding global, regional and cultural trends in vast amounts of data, and 2) applying learning analytics in games to evaluate cognitive and non-cognitive competences through stealth assessment and to provide support to teachers.
Through students and collaborations, I also work in other areas equally exciting including many other topics within the broad area of technology-enhanced learning and applied data science and technology in diverse contexts like social networks or online advertising.
One of the things I enjoy the most as part of the academic career is supervising students and see them grow into independent researchers over the years.
I'm currently part of the CyberDataLab at the University of Murcia. We are constantly offering research opportunities for last year brilliant BEng students and Master students, as well as PhD fellowships. I'm also open to remote supervision and collaborations if you already work in a different institution. Just contact me!