The Role of Trust in Personal Data Sharing in the Context of e-Assessment and the Moderating Effect of Special Educational Needs

Ekaterina Muravyeva, José Janssen, Kim Dirkx, Marcus Specht

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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 languageEnglish
Title of host publicationUMAP 2020 - Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization
PublisherAssociation for Computing Machinery (ACM)
Pages328-332
Number of pages5
ISBN (Electronic)9781450368612
DOIs
Publication statusPublished - 2020
Event28th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2020 - Genoa, Italy
Duration: 14 Jul 202017 Jul 2020

Publication series

NameUMAP 2020 - Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization

Conference

Conference28th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2020
Country/TerritoryItaly
CityGenoa
Period14/07/2017/07/20

Keywords

  • decision-making
  • e-assessment
  • informed consent
  • personal data
  • sensitive data
  • trust

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