Enhanced Affective Factors Management for HEI Students Dropout Prevention

  • Emmanuelle Gutiérrez y Restrepo
  • Fernando Ferreira
  • Jesús G. Boticario
  • Elsa Marcelino-Jesus
  • Joao SarraipaEmail author
  • Ricardo Jardim-Goncalves
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9753)


Among the problems affecting Higher Education Institutions (HEI) in Latin America and the Caribbean there is the dropout, which relates to a more general issue consisting in dealing with the diversity of students. Here provided solutions are to detect and deal with student’s particular capacities and needs. To cope with this situation the ACACIA project has defined a framework that develops both CADEP centers and technological infrastructure. The former consists of an organizational unit focus on Empowering, Innovating, Educating, Supporting, Monitoring and leveraging institutions in dealing with such diversity. The latter is based on building the required infrastructure to tackle those issues and covering both face-to-face and eLearning educational settings. This comprises non-intrusive affect detection methods along with ambient intelligent solutions, which provide context-aware affective feedback to each student. Preliminary experimentation results open interesting avenues to be further progressed thus taking advantage of current developments on affect computing technologies.


Emerging technologies for collaboration and learning Recommender systems for technology-enhanced learning 



The authors acknowledge the European Commission for its support and partial funding and the partners of the research projects from ERASMUS+: Higher Education – International Capacity Building - ACACIA – Project reference number – 561754-EPP-1-2015-1-CO-EPKA2-CBHE-JP, (; and Horizon2020 - AquaSmart – Aquaculture Smart and Open Data Analytics as a Service, project number - 644715, ( This work has also been partly supported by the Spanish Ministry of Economy and Competitiveness through projects MAMIPEC (TIN2011-29221-C03-01) and BIG-AFF (TIN2014-59641-C2-2-P.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Emmanuelle Gutiérrez y Restrepo
    • 1
    • 2
  • Fernando Ferreira
    • 3
  • Jesús G. Boticario
    • 1
  • Elsa Marcelino-Jesus
    • 3
  • Joao Sarraipa
    • 3
    Email author
  • Ricardo Jardim-Goncalves
    • 3
  1. 1.aDeNu Research Group, Artificial Intelligence Department, Computer Science SchoolUNEDMadridSpain
  2. 2.SIDAR FoundationMadridSpain
  3. 3.CTS, UNINOVA, DEE, Faculdade de Ciências e TecnologiaUniversidade NOVA de LisboaCaparicaPortugal

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