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Mapping a Privacy Framework to a Reference Model of Learning Analytics

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Presentation of the article at Workshop of Learning Analytics & Knowledge 2016 in April 25, 2016.

Note: full paper is available on http://www.laceproject.eu/wp-content/uploads/2015/12/ep4la2016_paper_4.pdf

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Mapping a Privacy Framework to a Reference Model of Learning Analytics

  1. 1. Mapping a Privacy Framework to a Reference Model of Learning Analytics Yong-Sang Cho, Tore Hoel and Weiqin Chen Korea Education & Research Information Service Yong-Sang Cho, Ph.D zzosang@keris.or.kr FB: /zzosang Twitter: @zzosang LAK 2016 Workshop April 25, 2016
  2. 2. “This paper is a first exploration of how the privacy framework found in the ISO/IEC 29100 standard could be applied to learning analytics. In this case study a mapping is provided between the published ISO/IEC standard and the learning analytics framework under development as a reference model for learning analytics, ISO/IEC 20748. This mapping and the identified privacy requirements and principles will prove useful in designing learning analytics system as well as performing risk management to avoid privacy breaches.” Abstract
  3. 3. Overview ISO/IEC 29100 ISO/IEC 29100 is an international standard providing a high-level framework for the protection of Personally Identifiable Information (PII) within information and communication technology (ICT) systems. This standard describes organizational technical, and procedural aspects in overall privacy framework. • specifying a common privacy terminology; • defining the actors and their roles in processing PII; • describing privacy safeguarding requirements; and • referencing known privacy principles.
  4. 4. Basic Elements of Privacy Framework • actors and roles; • Interactions; • recognizing PII; • privacy safeguarding requirements; • privacy policies; and • privacy controls.
  5. 5. Basic Elements of Privacy Framework • actors and roles; • Interactions; • recognizing PII; • privacy safeguarding requirements; • privacy policies; and • privacy controls. a) PII Principals b) PII Controller c) PII Processor d) Third party
  6. 6. Basic Elements of Privacy Framework • actors and roles; • Interactions; • recognizing PII; • privacy safeguarding requirements; • privacy policies; and • privacy controls. Provide PII between actors
  7. 7. Basic Elements of Privacy Framework • actors and roles; • Interactions; • recognizing PII; • privacy safeguarding requirements; • privacy policies; and • privacy controls. a) Identifier b) Other distinguishing characteristics c) Any information linked to a PII principal d) Pseudonymous data e) Metadata f) Unsolicited PII g) Sensitive PII
  8. 8. Basic Elements of Privacy Framework • actors and roles; • Interactions; • recognizing PII; • privacy safeguarding requirements; Risk Management • privacy policies; and • privacy controls.
  9. 9. Basic Elements of Privacy Framework • actors and roles; • Interactions; • recognizing PII; • privacy safeguarding requirements; • privacy policies; and • privacy controls. a) Provide framework b) Satisfy privacy safeguarding requirements
  10. 10. Basic Elements of Privacy Framework • actors and roles; • Interactions; • recognizing PII; • privacy safeguarding requirements; • privacy policies; and • privacy controls. to meet the privacy safeguarding requirements identified by the privacy risk assessment and treatment process
  11. 11. Privacy Principles
  12. 12. Privacy Principles 1. Consent and choice 2. Purpose legitimacy and specification 3. Collection limitation 4. Data minimization 5. Use, retention and disclosure limitation 6. Accuracy and quality 7. Openness, transparency and notice 8. Individual participation and access 9. Accountability 10. Information security 11. Privacy compliance
  13. 13. ISO/IEC 29748-1 LAI - Reference Model
  14. 14. Adoption of Privacy Framework to Learning Analytics
  15. 15. Questions? Korea Education & Research Information Service Yong-Sang CHO, Ph.D zzosang@gmail.com FB: /zzosang Twitter: @zzosang

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