The reviewed record of science sign in
Pith

arxiv: 1703.06169 · v1 · pith:S7DZLURC · submitted 2017-03-17 · cs.CY · cs.HC

Improving Assessment on MOOCs Through Peer Identification and Aligned Incentives

Reviewed by Pith T0 review T1 audit T2 compute T3 formal T4 kernel pith:S7DZLURCrecord.jsonopen to challenge →

classification cs.CY cs.HC
keywords peerassessmentfeedbackmoocsincentivesopenqualityaligned
0
0 comments X
read the original abstract

Massive Open Online Courses (MOOCs) use peer assessment to grade open ended questions at scale, allowing students to provide feedback. Relative to teacher based grading, peer assessment on MOOCs traditionally delivers lower quality feedback and fewer learner interactions. We present the identified peer review (IPR) framework, which provides non-blind peer assessment and incentives driving high quality feedback. We show that, compared to traditional peer assessment methods, IPR leads to significantly longer and more useful feedback as well as more discussion between peers.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.