Teaching, Research, Service: The Concept of Faculty Workload

Mancing, Howard

doi:10.1632/adfl.22.3.44

Cited by 4 publications

(1 citation statement)

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“…An attempt to find a fair and equitable workload model was carried out by Blitzer [2] in South Africa with an attempt to find a fair and equitable workload distribution, while at the same time ensuring general faculty satisfaction. The foundation for the attempt was based on the survey carried out by Soliman [29] where two frameworks for faculty workload were explored. The first was an economic costs and earnings based framework, where workload for an activity was equated to its financial output.…”

Section: Time-based Workload Modelsmentioning

confidence: 99%

Algorithms and data structures for automated teaching workload allocation

Sood¹

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Fair allocation of teaching workload to academic staff is one of the most important administrative duties of an educational institution. However, it is often managed manually with limited data and, often with an arbitrary set of constraints due its complexity, thereby resulting in sub optimal allocations. The objective of this research is to develop efficient methods to automatic the realization of a fair and transparent workload allocation system. A detailed exploration of past attempts, aimed at improving the workload allocation at tertiary institutions, was undertaken to gain a deeper understanding of the various approaches and challenges associated with the process. In particular, it was observed that various approaches were adopted to quantify a variety of components of the workload during the allocation process covering teaching, research and administrative duties. This motivated the development of an efficient time-based workload model called the Workload Unit (WLU) Model as the quantitative framework for measuring and comparing different faculty workloads. This involved the utilization of a combination of weightages corresponding to nature of teaching duties, the number and appointment of faculty as well as their availability for undertaking teaching duties, and attributes (such as class size, level of course, preparation requirements, etc.) of the courses to be offered. In addition, the proposed workload model takes into account the research activeness and administrative duties carried out by each faculty. The resulting workload is separated into two components, namely formal and informal teaching for the purpose of systematic workload allocation. Next, an efficient workload allocation method for formal teaching comprising of lectures, tutorials and labs was proposed by taking into consideration of faculty preference and performance, School policies and priorities and availability of teaching expertise. A novel combined cost function was proposed to determine the feasibility of individual allocations called the Feasibility Index (FI). A greedy approach, with activity-type and course-priority heuristics, is implemented to optimize the quality of the allocations. The proposed approach was validated against the workload allocations made at one of the schools of a University consisting of 100 teaching faculty, 120 courses and 1500 students. The resulting allocations improved workload distribution and quality of assignments over existing manual processes,

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Section: Time-based Workload Modelsmentioning

confidence: 99%