Students’ engagement with a collaborative wiki tool predicts enhanced written exam performance

Author:

Stafford Tom,Elgueta Herman,Cameron Harriet

Abstract

We introduced voluntary wiki-based exercises to a long-running cognitive psychology course, part of the core curriculum for an undergraduate degree in psychology. Over 2 yearly cohorts, students who used the wiki more also scored higher on the final written exam. Using regression analysis, it is possible to account for students’ tendency to score well on other psychology exams, thus statistically removing some obvious candidate third factors, such as general talent or enthusiasm for psychology, which might drive this correlation. Such an analysis shows that both high- and low-grading students who used the wiki got higher scores on the final exam, with engaged wiki users scoring an average of an extra 5 percentage points. We offer an interpretation of the mechanisms of action in terms of the psychological literature on learning and memory.Keywords: learning technology; writing; wiki; collaborative learning; interactive learning environments; higher education(Published: 5 August 2014)Citation: Research in Learning Technology 2014, 22: 22797 - http://dx.doi.org/10.3402/rlt.v22.22797

Publisher

Association for Learning Technology

Subject

Computer Science Applications,Education

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Increasing Engagement in e-Learning Systems;Intelligent Systems Reference Library;2022

2. To Ameliorate Classification Accuracy Using Ensemble Vote Approach and Base Classifiers;Advances in Intelligent Systems and Computing;2018-09-02

3. Predicting Academic Performance Based on Learner Traces in a Social Learning Environment;IEEE Access;2018

4. Students’ collaborative patterns in a wiki-authoring project;Journal of Applied Research in Higher Education;2017-02-06

5. Using Ranking and Multiple Linear Regression to Explore the Impact of Social Media Engagement on Student Performance;2016 IEEE 16th International Conference on Advanced Learning Technologies (ICALT);2016-07

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3