Abstract
In this study, the problem of biasness and unfairness in course allocation mechanism is addressed. Institutions face problem when allocating courses to the faculty members that are according to their expertise and this becomes more complex when two or more than two individuals are having expertise in same area. The work done previously in this area is extended by suggesting the mechanism that reduce the human biasness and encourages the fairness to the extent possible. Mechanism suggested uses well known process mining algorithm, the Alpha. It generates process model based on software generated event logs and comparison of original process model with process mining generated process model reveals the deviations in process model which in turn helps to detect deviations in it and is founding stone for suggestive conclusion for further improvement and modification in the software process model and the software system itself. Conclusively the suggested mechanism helps to reduce human biasness in course allocation and encourages to allow fair allocation of the resources to the right person.
Muhammad Imran, Riaz-ul- Amin, Abdul Sattar Malik, Bakhtiar Kasi, Mumraiz Kasi. (2017) Constraints Resolution in Semi-Automated Course Allocation Process for Educational Institute, Journal of Applied and Emerging Sciences, Volume 7, Issue 1.
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