A multi-peer assessment platform for programming language learning: considering group non-consensus and personal radicalness

被引：17

作者：

Wang, Yanqing ^{[1
]}

Liang, Yaowen ^{[1
]}

Liu, Luning ^{[1
]}

Liu, Ying ^{[2
]}

机构：

[1] Harbin Inst Technol, Sch Management, Harbin, Peoples R China

[2] Calif State Univ Long Beach, Dept Informat Syst, Coll Business Adm, Long Beach, CA 90840 USA

来源：

INTERACTIVE LEARNING ENVIRONMENTS | 2016年 / 24卷 / 08期

基金：

黑龙江省自然科学基金; 中国国家自然科学基金;

关键词：

interactive learning environments; peer code review; multi-peer assessment; programming languages learning; learning communities; cooperative learning; FEEDBACK; STUDENTS;

D O I：

10.1080/10494820.2015.1073748

中图分类号：

G40 [教育学];

学科分类号：

040101 ; 120403 ;

摘要：

Multi-peer assessment has often been used by teachers to reduce personal bias and make the assessment more reliable. This study reviews the design and development of multi-peer assessment systems that detect and solve two common issues in such systems: non-consensus among group members and personal radicalness in some assessments. A multi-peer assessment model is proposed to address these issues. The model captures roles, activities, and data structures in a typical multi-peer assessment setting that can be generalized to other scenarios. We implemented the model in a multi-peer code review system and conducted several empirical experiments in programming language classes. The studies showed that the model can significantly improve student learning outcomes than in a single-peer assessment. Also,we used statistical measures to detect non-consensus and radicalness issues that often occur in the model. The results reveal many insights and provide valuable guidance for teachers to implement a multi-peer assessment system.

引用

页码：2011 / 2031

页数：21