Abstract
The current study investigated the role of trust in students' attitudes towards personal data sharing in the context of e-assessment, and whether this is different for students with special educational needs and disabilities (SEND). SEND students were included as a special target group because they may feel more dependent on e-assessment technologies, and thus, more easily consent to personal data sharing. A mixed methods research design was adopted combining an online survey and a focus group interview to collect quantitative and qualitative data. The findings suggest that a considerable number of students trust e-assessment technology that does not require the physical presence of a supervisor. Students who trust are more likely to perceive e-assessment technology as having no disadvantages, and are more willing to share their personal data for e-assessment purposes. The responses of SEND and non-SEND students do not differ significantly in terms of trust. However, the results diverge regarding the relation between trust and perception of e-assessment technology as having no disadvantages. Practical implications for informed consent are discussed.
| Original language | English |
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| Title of host publication | UMAP '20 |
| Subtitle of host publication | Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization |
| Place of Publication | New York, USA |
| Publisher | Association for Computing Machinery (ACM) |
| Pages | 328-332 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781450368612 |
| DOIs | |
| Publication status | Published - Jul 2020 |
| Event | 28th ACM Conference on User Modeling, Adaptation and Personalization - Genoa, Italy Duration: 14 Jul 2020 → 17 Jul 2020 https://dl.acm.org/doi/proceedings/10.1145/3340631 |
Conference
| Conference | 28th ACM Conference on User Modeling, Adaptation and Personalization |
|---|---|
| Abbreviated title | UMAP’20 |
| Country/Territory | Italy |
| City | Genoa |
| Period | 14/07/20 → 17/07/20 |
| Internet address |
Keywords
- Decision-making
- Informed consent
- Personal data
- Sensitive data
- Trust
- e-Assessment
- trust
- informed consent
- decision-making
- e-assessment
- sensitive data
- personal data