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

E.V. Muravyeva*, J.P.W. Janssen, K.J.H. Dirkx, M.M. Specht

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-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 '20
Subtitle of host publicationProceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization
Place of PublicationNew York, USA
PublisherAssociation for Computing Machinery (ACM)
Pages328-332
Number of pages5
ISBN (Electronic)978-1-4503-6861-2/20/07
DOIs
Publication statusPublished - Jul 2020
Event28th ACM Conference on User Modeling, Adaptation and Personalization - Genoa, Italy
Duration: 14 Jul 202017 Jul 2020
https://dl.acm.org/doi/proceedings/10.1145/3340631

Conference

Conference28th ACM Conference on User Modeling, Adaptation and Personalization
Abbreviated titleUMAP’20
CountryItaly
CityGenoa
Period14/07/2017/07/20
Internet address

Keywords

  • Trust
  • Decision-making
  • Informed consent
  • Personal data
  • Sensitive data
  • e-Assessment

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