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
Associate Supervisors
Research Affiliations
- School of Management and Enterprise
Field of Research
- Education Systems
- Information Systems
- Other Education
Available Academic Programs
- Doctor of Philosophy (DPHD)
- Doctor of Philosophy (DPHD)
- Master of Research (MRES)
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