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...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.展开更多
This paper mainly focuses on advantages and challenges of student peer assessment,which is an effective approach for students to increase the confidence and curriculum engagement as well as formative assessment.
基金sponsored by the National Natural Science Foundation of China(61602331)the Opening Foundation for the Key Laboratory of Sichuan Province(NDSMS201606).
文摘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.
文摘This paper mainly focuses on advantages and challenges of student peer assessment,which is an effective approach for students to increase the confidence and curriculum engagement as well as formative assessment.
