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ERIC Number: EJ1316062
Record Type: Journal
Publication Date: 2021-Dec
Pages: 15
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1560-4292
EISSN: N/A
Available Date: N/A
Supporting Privacy, Trust, and Personalization in Online Learning
International Journal of Artificial Intelligence in Education, v31 n4 p769-783 Dec 2021
Privacy is a rather murky concept, but the absence of privacy is clearly felt in today's digital world. With the significant increase in surveillance power of software and hardware, storage capacity, computing power as well as advancement in data science technologies, the threat to privacy is ever increasing. Within the digital realm, privacy has been studied in different platforms, contexts, and environments. In this capacity, Professor Jim Greer is one of the pioneering thought leaders to study privacy in online learning environment. Additionally, strongly related to privacy, trust and personalization are two important components of online learning. This article reflects on Greer's contributions to grapple with the following questions: (1) To what extent are privacy, trust, and personalization desired in online learning? (2) How can privacy, trust, and personalization be supported in online learning? In this vein, we study three theories (i.e., limitation theory, control theory, and contextual integrity theory) and different mechanisms (e.g., privacy preferences, identity management, contextual information flow) for privacy. Additionally, this article discusses the ways to achieve trust and personalization without compromising privacy.
Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link-springer-com.bibliotheek.ehb.be/
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: N/A