Personal Data Broker: A Solution to Assure Data Privacy in EdTech

  • Daniel AmoEmail author
  • David Fonseca
  • Marc Alier
  • Francisco José García-Peñalvo
  • María José Casañ
  • María Alsina
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11590)


Educational technologies (Edtech) collect private and personal data from students. This is a growing trend in both new and already available Edtech. There are different stakeholders in the analysis of the collected students’ data. Teachers use educational analytics to enhance the learning environment, principals use academic analytics for decision making in the leadership of the educational institution and Edtech providers uses students’ data interactions to improve their services and tools. There are some issues in this new context. Edtech have been feeding their analytical algorithms from student’s data, both private and personal, even from minors. This draws a critical problem about data privacy fragility in Edtech. Moreover, this is a sensitive issue that generates fears and angst in the use of educational data analytics in Edtech, such as learning management systems (LMS). Current laws, regulations, policies, principles and good practices are not enough to prevent private data leakage, security breaches, misuses or trading. For instance, data privacy agreements in LMS are deterrent but not an ultimate solution due do not act in real time. There is a need for automated real-time law enforcement to avoid the fragility of data privacy. In this work, we take a step further in the automation of data privacy agreement in LMS. We expose which technology and architecture are suitable for data privacy agreement automation, a partial implementation of the design in Moodle and ongoing work.


Smart contracts Learning Analytics Moodle Data privacy Digital identity Blockchain Educational data mining Academic analytics 



To the support of the Secretaria d’Universitats i Recerca of the Department of Business and Knowledge of the Generalitat de Catalunya for the help regarding 2017 SGR 934.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Daniel Amo
    • 1
    Email author
  • David Fonseca
    • 1
  • Marc Alier
    • 2
  • Francisco José García-Peñalvo
    • 3
  • María José Casañ
    • 2
  • María Alsina
    • 1
  1. 1.La Salle, Universitat Ramón LlullBarcelonaSpain
  2. 2.Universitat Politècnica de CatalunyaBarcelonaSpain
  3. 3.Universidad de SalamancaSalamancaSpain

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