A factorization approach to evaluate open-response assignments in MOOCs using preference learning on peer assessments
We approach the problem of assessing open-text questions in MOOCs by peer-assessment. Our method avoids the intrinsic subjectivity of the numeric grades given by graders. Experiments where made with real-world data collected from 3 Universities in Spain. Our method performs well when comparing discrepancies among instructors grades.
factorization moocs preference learning peer grading ordinal and cardinal approaches