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Okada, Alexandra and Whitelock, Denise
(2018).
Abstract
This work presents a novel approach RRI supported by data science to measure and evaluate trust during the development of the innovative technology “TeSLA“.
The EU‐funded Adaptive Trust‐based e‐Assessment System for Learning (TeSLA) (http://tesla-project.eu) was developed to check student authentication and authorship through a combination of various instruments, such as: facial recognition, voice recognition, keystroke analysis, anti‐plagiarism and forensic analysis.
Through mixed methods, three case-studies analysed small, medium and large data sets co-produced at the beginning, during and at the end of the TeSLA project in seven Institutions from 6 European countries.
The set of studies revealed that the RRI with data science approach was vital to examine the perceptions and needs of distinctive users as well to evaluate and increase trust of the European TeSLA system.
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- Item ORO ID
- 58244
- Item Type
- Conference or Workshop Item
- Project Funding Details
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Funded Project Name Project ID Funding Body TeSLA 688520 European Commission - Academic Unit or School
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Faculty of Wellbeing, Education and Language Studies (WELS) > Education, Childhood, Youth and Sport > Education
Faculty of Wellbeing, Education and Language Studies (WELS) > Education, Childhood, Youth and Sport
Faculty of Wellbeing, Education and Language Studies (WELS)
Institute of Educational Technology (IET) - Research Group
- OpenTEL
- Copyright Holders
- © 2018 The Authors
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- Depositing User
- Alexandra Okada