Developing an optimal academic workload distribution model: a case study of an academic department at a university of technology in South Africa
Olwal, Thomas (2023)
2023
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2023101927732
https://urn.fi/URN:NBN:fi:amk-2023101927732
Tiivistelmä
The recent surge in demand for higher education has witnessed an increased number of students and the evolution of newer courses in Higher Education Institutions (HEIs) globally. This phenomenon has further precipitated the development of more efficient mechanisms for educational quality assurance with more student and outcome oriented. Academic work is notoriously difficult to quantify, but the rationale for managing academic workload is pillared on accountability required of the HEIs by stakeholders. Studies show that existing workload models in practice are not optimal and cannot guarantee fair, equitable, transparent and consistent distribution of academic work. This study aims to determine a mathematically optimal aggregate academic workload distribution (AAWLD) model in a case study department at a university of technology in South Africa.
The aim was achieved by developing a low complex mathematical optimisation model numerically solved using Matrix Laboratory (MATLAB)TM software. Empirical data was collected using a developed on online survey questionnaire. Data from the empirical study from a population number (N = 161) and sample size (n = 63) as well as from the institutional academic workload norms were utilised to moderate the performance of the optimal AAWLD model. Further statistical tests were conducted using STATA and word cloud analyses tool to establish the statistically significant differences among the academic post levels with regard to their level of agreements on academic workload distribution preferences.
Results showed that the developed optimal AAWLD model yielded optimal values of the academic workload commitments in a fair, equitable, transparent and consistent manner. The results also showed that developing an optimal AAWLD model is a catalyst for an improved job productivity and satisfaction among academics in a UoT context.
The aim was achieved by developing a low complex mathematical optimisation model numerically solved using Matrix Laboratory (MATLAB)TM software. Empirical data was collected using a developed on online survey questionnaire. Data from the empirical study from a population number (N = 161) and sample size (n = 63) as well as from the institutional academic workload norms were utilised to moderate the performance of the optimal AAWLD model. Further statistical tests were conducted using STATA and word cloud analyses tool to establish the statistically significant differences among the academic post levels with regard to their level of agreements on academic workload distribution preferences.
Results showed that the developed optimal AAWLD model yielded optimal values of the academic workload commitments in a fair, equitable, transparent and consistent manner. The results also showed that developing an optimal AAWLD model is a catalyst for an improved job productivity and satisfaction among academics in a UoT context.