Radical Solutions and Learning Analytics

Prof. Dr. Daniel Burgos works as a Full Professor of Technologies for Education & Communication and Vice-rector for International Research (UNIR Research), at Universidad Internacional de La Rioja (UNIR). In addition, he holds the UNESCO Chair on eLearning and the ICDE Chair in Open Educational Resources. He works also as Director of the Research Institute for Innovation & Technology in Education (UNIR iTED).His interests are mainly focused on Educational Technology & Innovation: Adaptive/Personalised and Informal eLearning, Learning Analytics, Social Networks, eGames, and eLearning Specifications. He has published over 130 scientific papers, 15 books and 15 special issues on indexed journals. He is or has been involved in +55 European and Worldwide R&D projects, with a practical implementation approach.He also works as a Professor at An-Najah National University (Palestine), an Assistant Professor at Universidad Nacional de Colombia (UNAL, Colombia), and a Visiting Professor at Coventry University (United Kingdom) and Universidad de las Fuerzas Armadas (ESPE, Ecuador). He has been chair (2016, 2018) and vice-chair (2015, 2017) of the international jury for the UNESCO King Hamad Bin Isa Al Khalifa Prize for the Use of ICTs in Education. He is a consultant for United Nations Economic Commission for Europe (UNECE), European Commission, European Parliament, Russian Academy of Science and ministries of Education in over a dozen countries. He is an IEEE Senior Member. He holds degrees in Communication (PhD), Computer Science (Dr. Ing), Education (PhD), Anthropology (PhD), Business Administration (DBA) and Artificial Intelligence (MIT, postgraduate).

• 1 Learning Analytics as a Breakthrough in Educational Improvement.- 2 LA to Improve the Learner's Performance.- 3 LA to Improve the Teacher's Performance.- 4 Dashboards for a Better Application of LA.- 5 Mobile LA in Digital Devices.- 6 Physical Sensors and LA in the Classroom.- 7 Remote Labs and Big Data.- 8 Understanding Big Data for Educational Management.- 9 Interpretation of Live Data and Decision Making in Streamed Lessons and Real-Time User Tracking.- 10 Prediction of Users' Behaviour.- 11 Prevention of Students and Faculty Attrition.- 12 Personalised Mentoring Through Quantitative & Qualitative Data.- 13 User Vectorisation Through Deep Learning and Neural Networks.- 14 Fighting Student's Drop-Out Through Historical Data.- 15 Visual Analytics for a Better Impact of Deep Data.