Abstract
Peer Assessment is a powerful tool to enhance students high level meta-cognitive skills. In this paper we deal with a simulation framework (K-OpenAnswer) allowing to support peer assessment sessions, in which peers answer a question and assess some of their peers’ answers, with the enrichment of “teacher mediation”. Teacher mediation consists in the possibility for the teacher to add information into the network of data built by the peer assessment, by grading some answers. This can be useful to enhance the automated grading functionality of an educational system supporting peer assessment. We present a software system allowing to apply the K-OpenAnswer simulation framework on simulated Massive Open On-line Courses (MOOCs). The system allows to guide the dynamic of the student models and grades evolution, according to the teacher’s intervention. It also allows to appreciate such dynamic and make observations about it. The aim of this paper is to show the functionalities that the teacher can use, and their usefulness on simulated MOOCs, planning the use of the same functionalities in the case of real MOOCs.
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Sciarrone, F., Temperini, M. (2019). Simulating Peer Assessment in Massive Open On-line Courses. In: Visvizi, A., Lytras, M. (eds) Research & Innovation Forum 2019. RIIFORUM 2019. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-30809-4_1
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DOI: https://doi.org/10.1007/978-3-030-30809-4_1
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