DocumentCode
737223
Title
Learnersourced Recommendations for Remediation
Author
Li, Shang-Wen Daniel ; Mitros, Piotr
fYear
2015
fDate
6-9 July 2015
Firstpage
411
Lastpage
412
Abstract
Rapid remediation of student misconceptions and knowledge gaps is one of the most effective ways to help students learn. We present a system for recommending additional resources, such as videos, reading materials, and web pages for students working through on-line course materials. This can provide remediations of knowledge gaps involving complex concepts. The system relies on learners suggesting resources which helped them, leveraging economies of scale as found in MOOCs and similar at-scale settings in order to build a rich body of remediations. The system allows for remediation of much deeper knowledge gaps than in prior work on remediation in MOOCs. We validated the system through a deployment in an introductory computer science MOOC. We found it lead to more in-depth remediation than prior strategies.
Keywords
Artificial intelligence; Computer science; Crowdsourcing; Debugging; Education; Psychology; Web pages;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Learning Technologies (ICALT), 2015 IEEE 15th International Conference on
Conference_Location
Hualien, Taiwan
Type
conf
DOI
10.1109/ICALT.2015.72
Filename
7265366
Link To Document