Literaturnachweis - Detailanzeige
Autor/inn/en | Yacobson, Elad; Fuhrman, Orly; Hershkowitz, Sara; Alexandron, Giora |
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Titel | De-Identification Is Insufficient to Protect Student Privacy, or--What Can a Field Trip Reveal? |
Quelle | In: Journal of Learning Analytics, 8 (2021) 2, S.83-92 (10 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
Zusatzinformation | ORCID (Yacobson, Elad) ORCID (Fuhrman, Orly) ORCID (Alexandron, Giora) |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
ISSN | 1929-7750 |
Schlagwörter | Identification; Privacy; Field Trips; Learning Analytics; Student Records; Data Collection; Foreign Countries; Elementary School Students; Secondary School Students; Israel |
Abstract | Learning analytics have the potential to improve teaching and learning in K-12 education, but as student data is increasingly being collected and transferred for the purpose of analysis, it is important to take measures that will protect student privacy. A common approach to achieve this goal is the de-identification of the data, meaning the removal of personal details that can reveal student identity. However, as we demonstrate, de-identification alone is not a complete solution. We show how we can discover sensitive information about students by linking de-identified datasets with publicly available school data, using unsupervised machine learning techniques. This underlines that de-identification alone is insufficient if we wish to further learning analytics in K-12 without compromising student privacy. (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: https://learning-analytics.info/index.php/JLA/index |
Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2024/1/01 |