Salt Lake City, Utah
June 23, 2018
June 23, 2018
July 27, 2018
Computers in Education
Peer assessment has at least a 50-year history in academia, and online applications peer assessment have been available for more than 20 years. Until recently, online applications simply transmitted classmates’ feedback to each other. But in the past decade, facilities have been incorporated to automatically recognize good reviews. This helps authors know which suggestions to follow and helps reviewers improve their reviews. It can also aid in assigning peer grades. Several types of data can be used to determine review quality. These metrics can be combined using machine-learning and neural-network models to produce better estimates of review quality, and hence better estimates of the quality of reviewed work. This paper discusses past work in automatically assessing reviews, and summarizes our current efforts to build on that work.
Gehringer, E. F., & Pramudianto, F., & Medhekar, A., & Rajasekar, C., & Xiao, Z. (2018, June), Board 62: Applications of Artificial Intelligence in Peer Assessment Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. https://peer.asee.org/30073
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