Open Access
ARTICLE
A Sentinel-Based Peer Assessment Mechanism for Collaborative Learning
Cong Wang1, Mingming Zhao2, Qinyue Wang2, 3, Min Li2, *
1 Sichuan Police College, Luzhou, 646000, China.
2 Sichuan Normal University, Chengdu, 610068, China.
3 University of Tasmania, Sandy Bay, TAS, 7001, Australia.
* Corresponding Author: Min Li. Email: .
Computers, Materials & Continua 2020, 65(3), 2309-2319. https://doi.org/10.32604/cmc.2020.09958
Received 31 January 2020; Accepted 07 July 2020; Issue published 16 September 2020
Abstract
This paper introduces a novel mechanism to improve the performance of peer
assessment for collaborative learning. Firstly, a small set of assignments which have being
pre-scored by the teacher impartially, are introduced as “sentinels”. The reliability of a
reviewer can be estimated by the deviation between the sentinels’ scores judged by the
reviewers and the impartial scores. Through filtering the inferior reviewers by the reliability,
each score can then be subjected into mean value correction and standard deviation correction
processes sequentially. Then the optimized mutual score which mitigated the influence of the
subjective differences of the reviewers are obtained. We perform our experiments on 200
learners. They are asked to submit their assignments and review each other. In the
experiments, the sentinel-based mechanism is compared with several other baseline
algorithms. It proves that the proposed mechanism can effectively improve the accuracy of
peer assessment, and promote the development of collaborative learning.
Keywords
Cite This Article
C. Wang, M. Zhao, Q. Wang and M. Li, "A sentinel-based peer assessment mechanism for collaborative learning,"
Computers, Materials & Continua, vol. 65, no.3, pp. 2309–2319, 2020. https://doi.org/10.32604/cmc.2020.09958