文章基本信息

标题：Can e-Authentication Raise the Confidence of Both Students and Teachers in Qualifications Granted Through the e-Assessment Process?
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作者：Denise Whitelock ; Chris Edwards ; Alexandra Okada 等
期刊名称：Journal of Learning for Development
电子版ISSN：2311-1550
出版年度：2020
卷号：7
期号：1
页码：46-60
出版社：Commonwealth of Learning
摘要：The EU-funded TeSLA project - Adaptive Trust-based e-Assessment System for Learning (http://tesla-project.eu) has developed a suite of instruments for e-Authentication. These include face recognition, voice recognition, keystroke dynamics, forensic analysis and plagiarism detection were designed for integration within a university's virtual learning environment. These tools were trialed across the seven partner institutions: 4,058 participating students, including 330 Students with special educational needs and disabilities (SEND); 54 teaching staff. This paper describes the findings of this large-scale study where over 50% of students gave a positive response to the use of these tools. In addition, over 70% agreed that these tools were 'to ensure that my examination results are trusted' and 'to prove that my essay is my own original work'. Teaching staff also reported positive experiences of TeSLA: the figure reaching 100% in one institution. We show there is evidence that a suite of e-authentication tools such as TeSLA can potentially be acceptable to students and staff and be used to increase trust in online assessment. Also, that whilst not yet perfected for SEND students it can still enrich their experience of assessment. We find that care is needed when introducing such technologies to ensure the building of the layers of trust required for their successful adoption.
关键词：assessment; cheating; plagiarism; e;authentication