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

Daniel Amo, David Fonseca, Marc Alier, Francisco José García-Peñalvo, María José Casañ, María Alsina

Research output: Book chapterConference contributionpeer-review

14 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationLearning and Collaboration Technologies. Designing Learning Experiences - 6th International Conference, LCT 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings
EditorsPanayiotis Zaphiris, Andri Ioannou
PublisherSpringer Verlag
Pages3-14
Number of pages12
ISBN (Print)9783030218133
DOIs
Publication statusPublished - 2019
Event6th International Conference on Learning and Collaboration Technologies, LCT 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019 - Orlando, United States
Duration: 26 Jul 201931 Jul 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11590 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Conference on Learning and Collaboration Technologies, LCT 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019
Country/TerritoryUnited States
CityOrlando
Period26/07/1931/07/19

Keywords

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

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