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 :
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