@article{923085,
      recid = {923085},
      author = {Baneres, David, and Rodríguez, M. Elena, and  Guerrero-Roldán, Ana Elena,},
      title = {Engineering data-driven adaptive trust-based e-assessment  systems : challenges and infrastructure solutions /},
      pages = {1 online resource (xxiii, 327 pages) :},
      note = {Includes index.},
      abstract = {This book shares original innovations, research, and  lessons learned regarding teaching and technological  perspectives on trust-based learning systems. Both  perspectives are crucial to enhancing the e-Assessment  process. In the course of the book, diverse areas of the  computer sciences (machine learning, biometric recognition,  cloud computing, and learning analytics, amongst others)  are addressed. In addition, current trends, privacy,  ethical issues, technological solutions, and adaptive  educational models are described to provide readers with a  global view on the state of the art, the latest challenges,  and potential solutions in e-Assessment. As such, the book  offers a valuable reference guide for industry, educational  institutions, researchers, developers, and practitioners  seeking to promote e-Assessment processes.},
      url = {http://library.usi.edu/record/923085},
      doi = {https://doi.org/10.1007/978-3-030-29326-0,  https://doi.org/10.1007/978-3-030-29},
}