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

Autor/inn/en	Steiner, Christina M.; Kickmeier-Rust, Michael D.; Albert, Dietrich
Titel	LEA in Private: A Privacy and Data Protection Framework for a Learning Analytics Toolbox
Quelle	In: Journal of Learning Analytics, 3 (2016) 1, S.66-90 (25 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1929-7750
Schlagwörter	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; Europe + Suchen Sie Ihr Suchwort? Privatsphäre; Richtlinien; Ethik; Korrelation; Auswertung; Law; Recht; Forschung und Entwicklung; Ausland; Bürgerrechte; Grundrechte; Zivilrecht; Procurement of information; Informationsbeschaffung; Classification system; Klassifikation; Klassifikationssystem; Eigentum; Europa
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. (As Provided).
Anmerkungen	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/
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01