The 2018 International Technology Enhanced Assessment Conference (TEA2018) took place December 10-11 2018 in Amsterdam, The Netherlands (http://www.teaconference.org/). This is a unique event, which provides researchers, teachers and policymakers a possibility to share problems, challenges and advances in the field of e-Assessment.
Researchers from the Technical University of Sofia (TUS) and IDIAP Research Institute from Switzerland, both partners in the TeSLA project, developed a joint research study “Enhancing Trust in eAssessment – the TeSLA System Solution” and the paper was included in the conference program.
The paper was presented by Mariana Durcheva from TUS in session 4b and it attracted the attention of many participants in the forum interested in how to enhance trust in eAssessment and the solution which the TeSLA System provides.
The presented joint work was focused on the investigation and analysis of trust issues related to the TeSLA system as observed during the large-scale pilot conducted at the Technical University of Sofia. The main research questions posed in this work were: what are the factors determining trust in eAssessment; how can trust in eAssessment be achieved; how could the TeSLA system enhance trust in eAssessment?
The paper provided analysis of questionnaires and surveys concerning trust, filled in by pilot participants at TUS and presented the trust model implemented in the TeSLA system. Besides the instruments for biometric authentication, it involves instruments for cheating attacks detection and prevention as well, i.e. face-recognition anti-spoofing (FRA) and voice-recognition anti-spoofing (VRA) instruments. They provide for avoiding possible authentication frauds performed by students during the conduction of assessment activities. The anti-spoofing instruments (FRA and VRA) included in the TeSLA system address concerns of TeSLA pilot users, expressed in the questionnaires and surveys, about the trustworthiness of the core biometric instruments (face recognition and voice recognition respectively). The use of such instruments can help for enhancing the eAssessment trust model by preventing cheating and fraudulent behavior in online assessment scenarios.
Besides trustworthy authentication of learners the TeSLA system provides authorship analysis of written submissions including plagiarism detection. Research results concerning this aspect for trust enhancement provided by TeSLA as “An embedded approach to plagiarism detection using the TeSLA e-authentication system” authored by a research team of TeSLA partners from the Open University UK (OUUK), the Open University of Netherlands (OUNL) and The Open University of Catalunia (UOC) was presented by Dr. Alexandra Okada from OUUK.
It discusses whether the embedded nature of the TeSLA system could be used to improve constructive alignment between teaching and assessment within modules. The TeSLA system is constructed in a way that enables it to be embedded within an institutional VLE and invoked seamlessly. In addition to providing the e-authentication of students, this provides opportunities for improving the constructive alignment of learning outcomes describing the development of good academic practice and the avoidance of plagiaristic approaches in their learning and assessment: and thus the overall student experience.
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