We propose an assessor reallocation algorithm that aims to objectively reduce the marking biases of the individual markers based on their earlier marking statistics. The underlying mathematical structure along with a number of pertinent statistical properties and relationships has been analyzed for the model to assure the validity of the proposed methodology. Experiments on simulated data and on the real cases have also been conducted to illustrate the effectiveness on the reduction of the accumulated marking biases over multiple assessment items involving multiple assessors
This paper explores the implications of bias cancellation on the estimate of average treatment effec...
The presence of biased items may seriously affect methods used to link metrics in item response theo...
Bias Mitigation Algorithms and machine learning models are increasingly used in educational setting...
Assessment consistency is not easy to maintain across many assessors for a unit of a large student p...
A fundamental subject delivered at the tertiary level could have a cohort of several hundreds of stu...
A fundamental subject delivered at the tertiary level could have a cohort of several hundreds of stu...
The minimum bias classification ratemaking proce-dure, introduced by Robert Bailey and LeRoy Simon i...
It has been experienced and reported by academic institutions around the globe that marking of most ...
This tutorial presents recent advances on the assessment and mitigation of data and algorithmic bias...
Reliability and validity are ever-present themes in the evaluation of assessment. Previous research ...
This tutorial presents recent advances on the assessment and mitigation of data and algorithmic bias...
Rank aggregation is the process of aggregating multiple rankings provided by multiple assessors, of ...
Marker bias has been a serious factor contributing to discrepancy in assessments. In this study we a...
Frequently, a set of objects has to be evaluated by a panel of assessors, but not every object is as...
AVAA TIEDOSTO, KUN ARTIKKELI ON JULKAISTU. EMBARGO 12 KUUKAUTTAIn the practice of multi-criteria dec...
This paper explores the implications of bias cancellation on the estimate of average treatment effec...
The presence of biased items may seriously affect methods used to link metrics in item response theo...
Bias Mitigation Algorithms and machine learning models are increasingly used in educational setting...
Assessment consistency is not easy to maintain across many assessors for a unit of a large student p...
A fundamental subject delivered at the tertiary level could have a cohort of several hundreds of stu...
A fundamental subject delivered at the tertiary level could have a cohort of several hundreds of stu...
The minimum bias classification ratemaking proce-dure, introduced by Robert Bailey and LeRoy Simon i...
It has been experienced and reported by academic institutions around the globe that marking of most ...
This tutorial presents recent advances on the assessment and mitigation of data and algorithmic bias...
Reliability and validity are ever-present themes in the evaluation of assessment. Previous research ...
This tutorial presents recent advances on the assessment and mitigation of data and algorithmic bias...
Rank aggregation is the process of aggregating multiple rankings provided by multiple assessors, of ...
Marker bias has been a serious factor contributing to discrepancy in assessments. In this study we a...
Frequently, a set of objects has to be evaluated by a panel of assessors, but not every object is as...
AVAA TIEDOSTO, KUN ARTIKKELI ON JULKAISTU. EMBARGO 12 KUUKAUTTAIn the practice of multi-criteria dec...
This paper explores the implications of bias cancellation on the estimate of average treatment effec...
The presence of biased items may seriously affect methods used to link metrics in item response theo...
Bias Mitigation Algorithms and machine learning models are increasingly used in educational setting...