Polytechnic University of Valencia Congress, First International Conference on Higher Education Advances

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Optimising Peer Marking with Explicit Training: from Superficial to Deep Learning
Sabrina Caldwell, Tom Gedeon

Last modified: 10-06-2015

Abstract


We describe our use of formative assessment tasks measuring superficial learning as explicit training for peer assessment of a major summative assessment task (report writing) which requires deep learning. Formative assessment trained peer markers performing a surface learning task can produce peer marks consistent with our expert marker. This could have use in large online courses such as MOOCs. COMP1710 at our University is a first year Web Development and Design course done by about 100 students each year, by many Computing students in their first semester of their first year, or at any time prior to graduation as there is not a strong prerequisites tail, while the course is required for professional society accreditation of their Computing degree. The course also attracts some 25% of the cohort from other academic areas of the University. We found that the weaker students only capable of superficial learning were able to reliably assess the reports of the better students capable of the deeper learning required to produce the reports. This significantly increases the usefulness of peer marking.

DOI: http://dx.doi.org/10.4995/HEAd15.2015.441


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