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Malik, Ali; Wu, Mike; Vasavada, Vrinda; Song, Jinpeng; Coots, Madison; Mitchell, John; Goodman, Noah; Piech, Chris – International Educational Data Mining Society, 2021
Access to high-quality education at scale is limited by the difficulty of providing student feedback on open-ended assignments in structured domains like programming, graphics, and short response questions. This problem has proven to be exceptionally difficult: for humans, it requires large amounts of manual work, and for computers, until…
Descriptors: Grading, Accuracy, Computer Assisted Testing, Automation
Peer reviewed Peer reviewed
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Han, Yong; Wu, Wenjun; Ji, Suozhao; Zhang, Lijun; Zhang, Hui – International Educational Data Mining Society, 2019
Peer-grading is commonly adopted by instructors as an effective assessment method for MOOCs (Massive Open Online Courses) and SPOCs (Small Private online course). For solving the problems brought by varied skill levels and attitudes of online students, statistical models have been proposed to improve the fairness and accuracy of peer-grading.…
Descriptors: Peer Evaluation, Grading, Online Courses, Computer Assisted Testing
Peer reviewed Peer reviewed
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Pelánek, Radek; Rihák, Ji?rí – International Educational Data Mining Society, 2016
In online educational systems we can easily collect and analyze extensive data about student learning. Current practice, however, focuses only on some aspects of these data, particularly on correctness of students answers. When a student answers incorrectly, the submitted wrong answer can give us valuable information. We provide an overview of…
Descriptors: Foreign Countries, Online Systems, Geography, Anatomy