View in EDS

LEA in Private: A Privacy and Data Protection Framework for a Learning Analytics Toolbox

Saved in:
Bibliographic Details
Title: LEA in Private: A Privacy and Data Protection Framework for a Learning Analytics Toolbox
Language: English
Authors: Steiner, Christina M., Kickmeier-Rust, Michael D., Albert, Dietrich
Source: Journal of Learning Analytics. 2016 3(1):66-90.
Availability: Society for Learning Analytics Research. 121 Pointe Marsan, Beaumont, AB T4X 0A2, Canada. Tel: +61-429-920-838; e-mail: info@solaresearch.org; Web site: http://learning-analytics.info/journals/index.php/JLA/
Peer Reviewed: Y
Page Count: 25
Publication Date: 2016
Document Type: Journal Articles
Reports - Descriptive
Descriptors: Privacy, Guidelines, Ethics, Information Security, Correlation, Data Analysis, Laws, Research and Development, Program Descriptions, Informed Consent, Foreign Countries, Civil Rights, Information Management, Classification, Ownership, Trust (Psychology), Best Practices
Geographic Terms: Europe
ISSN: 1929-7750
Abstract: To find a balance between learning analytics research and individual privacy, learning analytics initiatives need to appropriately address ethical, privacy, and data protection issues. A range of general guidelines, model codes, and principles for handling ethical issues and for appropriate data and privacy protection are available, which may serve the consideration of these topics in a learning analytics context. The importance and significance of data security and protection are also reflected in national and international laws and directives, where data protection is usually considered as a fundamental right. Existing guidelines, approaches, and regulations served as a basis for elaborating a comprehensive privacy and data protection framework for the LEA's BOX project. It comprises a set of eight principles to derive implications for ensuring ethical treatment of personal data in a learning analytics platform and its services. The privacy and data protection policy set out in the framework is translated into the learning analytics technologies and tools that were developed in the project and may be used as best practice for other learning analytics projects.
Abstractor: As Provided
Number of References: 55
Entry Date: 2017
Accession Number: EJ1126798
Database: ERIC
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://eric.ed.gov/contentdelivery/servlet/ERICServlet?accno=EJ1126798
    Name: ERIC Full Text
    Category: fullText
    Text: Full Text from ERIC
Header DbId: eric
DbLabel: ERIC
An: EJ1126798
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: LEA in Private: A Privacy and Data Protection Framework for a Learning Analytics Toolbox
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Steiner%2C+Christina+M%2E%22">Steiner, Christina M.</searchLink><br /><searchLink fieldCode="AR" term="%22Kickmeier-Rust%2C+Michael+D%2E%22">Kickmeier-Rust, Michael D.</searchLink><br /><searchLink fieldCode="AR" term="%22Albert%2C+Dietrich%22">Albert, Dietrich</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Journal+of+Learning+Analytics%22"><i>Journal of Learning Analytics</i></searchLink>. 2016 3(1):66-90.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Society for Learning Analytics Research. 121 Pointe Marsan, Beaumont, AB T4X 0A2, Canada. Tel: +61-429-920-838; e-mail: info@solaresearch.org; Web site: http://learning-analytics.info/journals/index.php/JLA/
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 25
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2016
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Descriptive
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Privacy%22">Privacy</searchLink><br /><searchLink fieldCode="DE" term="%22Guidelines%22">Guidelines</searchLink><br /><searchLink fieldCode="DE" term="%22Ethics%22">Ethics</searchLink><br /><searchLink fieldCode="DE" term="%22Information+Security%22">Information Security</searchLink><br /><searchLink fieldCode="DE" term="%22Correlation%22">Correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Data+Analysis%22">Data Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Laws%22">Laws</searchLink><br /><searchLink fieldCode="DE" term="%22Research+and+Development%22">Research and Development</searchLink><br /><searchLink fieldCode="DE" term="%22Program+Descriptions%22">Program Descriptions</searchLink><br /><searchLink fieldCode="DE" term="%22Informed+Consent%22">Informed Consent</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Civil+Rights%22">Civil Rights</searchLink><br /><searchLink fieldCode="DE" term="%22Information+Management%22">Information Management</searchLink><br /><searchLink fieldCode="DE" term="%22Classification%22">Classification</searchLink><br /><searchLink fieldCode="DE" term="%22Ownership%22">Ownership</searchLink><br /><searchLink fieldCode="DE" term="%22Trust+%28Psychology%29%22">Trust (Psychology)</searchLink><br /><searchLink fieldCode="DE" term="%22Best+Practices%22">Best Practices</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Europe%22">Europe</searchLink>
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1929-7750
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: To find a balance between learning analytics research and individual privacy, learning analytics initiatives need to appropriately address ethical, privacy, and data protection issues. A range of general guidelines, model codes, and principles for handling ethical issues and for appropriate data and privacy protection are available, which may serve the consideration of these topics in a learning analytics context. The importance and significance of data security and protection are also reflected in national and international laws and directives, where data protection is usually considered as a fundamental right. Existing guidelines, approaches, and regulations served as a basis for elaborating a comprehensive privacy and data protection framework for the LEA's BOX project. It comprises a set of eight principles to derive implications for ensuring ethical treatment of personal data in a learning analytics platform and its services. The privacy and data protection policy set out in the framework is translated into the learning analytics technologies and tools that were developed in the project and may be used as best practice for other learning analytics projects.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: Ref
  Label: Number of References
  Group: RefInfo
  Data: 55
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2017
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1126798
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1126798
RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 25
        StartPage: 66
    Subjects:
      – SubjectFull: Privacy
        Type: general
      – SubjectFull: Guidelines
        Type: general
      – SubjectFull: Ethics
        Type: general
      – SubjectFull: Information Security
        Type: general
      – SubjectFull: Correlation
        Type: general
      – SubjectFull: Data Analysis
        Type: general
      – SubjectFull: Laws
        Type: general
      – SubjectFull: Research and Development
        Type: general
      – SubjectFull: Program Descriptions
        Type: general
      – SubjectFull: Informed Consent
        Type: general
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: Civil Rights
        Type: general
      – SubjectFull: Information Management
        Type: general
      – SubjectFull: Classification
        Type: general
      – SubjectFull: Ownership
        Type: general
      – SubjectFull: Trust (Psychology)
        Type: general
      – SubjectFull: Best Practices
        Type: general
      – SubjectFull: Europe
        Type: general
    Titles:
      – TitleFull: LEA in Private: A Privacy and Data Protection Framework for a Learning Analytics Toolbox
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Steiner, Christina M.
      – PersonEntity:
          Name:
            NameFull: Kickmeier-Rust, Michael D.
      – PersonEntity:
          Name:
            NameFull: Albert, Dietrich
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2016
          Identifiers:
            – Type: issn-electronic
              Value: 1929-7750
          Numbering:
            – Type: volume
              Value: 3
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: Journal of Learning Analytics
              Type: main
ResultId 1