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Research Thesis Topic

Reducing Assessor Specific Bias in Assessments Marking in Multi-Assessor Scenarios Utilising Group Normalising Technique


Topic ID
112

Thesis Topic/Title
Reducing Assessor Specific Bias in Assessments Marking in Multi-Assessor Scenarios Utilising Group Normalising Technique

Description

In this study we intend to investigate, develop and test a new innovative and adaptive bias reduction technique in multi-assessor marking scenarios. We intend to develop innovative and adaptable group normalisation based algorithms and identify requirement specifications to build software to handle the assessor bias in an automated manner considering the marking behaviour of individual assessors. The project will conduct test marking on assessments to identify the bias trends among assessors. The results will be included in the adjustments of the marking bias along with assessor specific trend data.


Principal Supervisor


Research Affiliations
  • School of Management and Enterprise

Field of Research
  • Education Systems
  • Information Systems
  • Other Education


Application Open Date
28/02/2017

Application Close Date
31/12/2020

USQ Scholarship Applications

Pre-approved for Ethics
Yes


Admission Requirements

Please review the admission requirements for the academic program associated with this Thesis Topic




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