Abstract
Over the last 20 years, online peer review and assessment have become widely used and well-researched practices in education. Their use increased, especially with the proliferation of nonconventional large-scale and online modes of teaching and learning, such as Massive Open Online Courses (MOOCs). A well-designed peer-review system is expected to produce valid and reliable assessments of the artifacts created by participants. These systems notably vary in designs, particularly in the structure of the peer-review networks, i.e., how participants are linked to each other as creators and reviewers. To date, little research has been done on how different network structures impact a system's ability to accurately assess the quality of the evaluated artifacts. We begin to address this gap, using a simulation approach to demonstrate that two network characteristics-dispersion and reciprocity-may indeed affect assessment fidelity in peer-review systems in conjunction with other design choices, such as evaluation scale and aggregation method. We also outline directions for further investigations of peer-review systems design.
Original language | English (US) |
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Article number | 8982044 |
Pages (from-to) | 580-592 |
Number of pages | 13 |
Journal | IEEE Transactions on Learning Technologies |
Volume | 13 |
Issue number | 3 |
DOIs | |
State | Published - Jul 1 2020 |
Keywords
- Assessment
- clustering
- dispersion
- evaluation systems
- information quality
- knowledge artifacts
- network structures
- peer assessment
- peer review
- reciprocity.
ASJC Scopus subject areas
- Education
- Engineering(all)
- Computer Science Applications