Web-Based Student Peer Review: A Research Summary
Abstract
Interest in web-based peer-review systems dates back nearly 20 years. Systems were built to let students give feedback to other students, mainly to help them improve their writing. But students are not necessarily effective peer reviewers. Left to their own, devices, they will submit cursory reviews, which are not very helpful to their peers. Techniques have been developed to improve the quality of reviews. Calibration is one such technique. Students are asked to assess samples of writing that have previously been assessed by experts or by other students. Some MOOCs have employed a "Crowdsourcing" approach to vetting reviews. A new area of research is automated meta-reviewing, where natural-language processing techniques are used to give students formative feedback on reviews they are about to submit. There is also a debate over whether students should rate eers on an absolute scale, or rank their work compared to the work of other students. This presentation summarizes findings from a broad range of research in Web-based peer review.
Location
Room 1220
Recommended Citation
Gehringer, Edward F., "Web-Based Student Peer Review: A Research Summary" (2014). SoTL Commons Conference. 105.
https://digitalcommons.georgiasouthern.edu/sotlcommons/SoTL/2014/105
Web-Based Student Peer Review: A Research Summary
Room 1220
Interest in web-based peer-review systems dates back nearly 20 years. Systems were built to let students give feedback to other students, mainly to help them improve their writing. But students are not necessarily effective peer reviewers. Left to their own, devices, they will submit cursory reviews, which are not very helpful to their peers. Techniques have been developed to improve the quality of reviews. Calibration is one such technique. Students are asked to assess samples of writing that have previously been assessed by experts or by other students. Some MOOCs have employed a "Crowdsourcing" approach to vetting reviews. A new area of research is automated meta-reviewing, where natural-language processing techniques are used to give students formative feedback on reviews they are about to submit. There is also a debate over whether students should rate eers on an absolute scale, or rank their work compared to the work of other students. This presentation summarizes findings from a broad range of research in Web-based peer review.
