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Unveiling Mapping Algorithm for a Computerized Academic Workload Sharing Model in Higher Institutions
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 187 - Number 89 |
| Year of Publication: 2026 |
| Authors: J.A. Adebisi, C.A. Chukwulobe, K.A. Abdulsalam |
10.5120/ijca2026926546
|
J.A. Adebisi, C.A. Chukwulobe, K.A. Abdulsalam . Unveiling Mapping Algorithm for a Computerized Academic Workload Sharing Model in Higher Institutions. International Journal of Computer Applications. 187, 89 ( Mar 2026), 16-23. DOI=10.5120/ijca2026926546
Abstract
In modern day academic settings, one of the most challenging activities in ivory towers is academic workload sharing. It is a critical activity in most universities and other higher institutions of learning. It is more crucial with the rising effect of staff turn-over in academics. This activity is usually committed to dedicated staff members of the faculty who is in charge of distribution, allocation and de-allocation under the instruction of the headship. It is more challenging as staff members tends to associate workload stress and burden to those in-charge hence the need for a computerised model of allocating workloads to academic staff in a seamless and efficient manner. The new mapping algorithm proposed in this work will eradicate most existing manual approaches, which is connected to slow pace of allocation, inconsistency, mismatch of areas of specializations among others. This work developed a model, designed a software engineering approach and implemented a prototype system in form of an application uses a typical the university settings in Nigeria as a case study. The developed software system uses a suitable mapping algorithm to share workloads in a more user friendly and smart methodology. Analysis of the workload allocation results revealed that the accuracy depends on the number of available academic staffs qualified for the individual workloads and subject areas assignment. The developed algorithm was implemented and tested using lecturers and module data from a standard curriculum in which, most of the activities recorded an accuracy of 100% in most cases with a few margins of less 2% using randomization techniques.
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