@inproceedings{7ad7f21b358944d08c1e7245d57e943b,
title = "A peer grading tool for MOOCs on programming",
abstract = "In massive open online courses (MOOCs), peer grading will play an important role to promote MOOCs development. In this paper, we develop a peer grading tool for programming courses on MOOCs. It is capable of dealing with large and diverse student population, and providing them with targeted subjective assessment. This tool firstly partition the submissions into small chunks to reduce the task of reviewers and give us flexibility to scale the code review process. Next we use code normalization and chunks clustering to assign similar chunks to the same student for increasing reviewer efficiency. Besides, the tool use a random allocation strategy and workload classification to assure reviewers workload balance while every student can get diverse feedback. Finally our evaluation experiments on a number of students in school indicate that the tool has achieved a significant improvement over the peer grading on MOOCs.",
keywords = "Code normalization, Peer grading. MOOCs, Review balance",
author = "Zhaodong Wei and Wenjun Wu",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2015.; International Conference of Young Computer Scientists, Engineers and Educators, ICYCSEE 2015 ; Conference date: 10-01-2015 Through 12-01-2015",
year = "2015",
doi = "10.1007/978-3-662-46248-5\_46",
language = "英语",
isbn = "9783662462478",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "378--385",
editor = "Hongzhi Wang and Wanxiang Che and Haoliang Qi and Leilei Kong and Zhongyuan Han and Zhaowen Qiu and Junyu Lin and Zeguang Lu",
booktitle = "Intelligent Computation in Big Data Era - International Conference of Young Computer Scientists, Engineers and Educators, ICYCSEE 2015, Proceedings",
address = "德国",
}