Contextualizing privacy with wearable data in higher education
Bibliographic Data
| ID | 21297779 |
|---|---|
| Authors | Mariah Hagadone‐Bedir (0000-0002-7112-6183, Educational Studies The Ohio State University Columbus Ohio USA, corresponding author), Rick Voithofer (0000-0002-5974-0367, Educational Studies The Ohio State University Columbus Ohio USA), Jessica T Kulp (0009-0003-6266-6326, Educational Studies The Ohio State University Columbus Ohio USA) |
| Year | 2023 |
| Volume | 54 |
| Issue | 6 |
| Pages | 1619-1635 |
| Publication date | 2023-11-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | British Journal of Educational Technology (JOURNAL) |
| Journal identifiers | ISSN: 0007-1013 • E-ISSN: 1467-8535 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/bjet.13378 |
| OpenAlex | W4386163474 |
| Language | EN |
| Citations received | 3 |
| References cited | 31 |
This conceptual study uses dynamic systems theory (DST) and phenomenology as lenses to examine data privacy implications surrounding wearable devices that incorporate stakeholder, contextual and technical factors. Wearable devices can impact people's behaviour and sense of self, and DST and phenomenology provide complementary approaches for emphasizing the subjective experiences of individuals that occur with the use of wearable data. Privacy is approached through phenomenology as an individual's lived bodily experience and DST emphasizes the self‐regulation and feedback loops of individuals and their uses of wearable data. The data collection, analysis and communication of wearable data to support learning systems alongside privacy implications for each are examined. The IoT, cloud computing, metadata and algorithms are discussed as they relate to wearable data, pointing out privacy risks and strategies to minimize harm. Practitioner notes
Data science · Data sharing · Epistemology · Human–computer interaction · Information privacy · Internet privacy · Metadata · Phenomenology (philosophy) · Wearable computer · Wearable technology · World Wide Web · Computer Science · IoT and Edge/Fog Computing · Mobile Crowdsensing and Crowdsourcing · Privacy-Preserving Technologies in Data
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Writing the Conceptual Article
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| Unique citing works | 3 |
|---|---|
| Citations per year | 1,5 |
| Citation span | 2024 - 2026 (3) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 3 |