Work recognition model for a higher education unit
AbstractHigher Education frameworks have a strong focus on increasing students’ satisfaction. This vision increases expectations on academic performance that often derive from stringent output measures for staff. The combination of internal and external demands for workers, such as those derived fro...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2023-12-01
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| Series: | Cogent Education |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/2331186X.2023.2248912 |
| _version_ | 1797390189732036608 |
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| author | P Martinez-Vazquez |
| author_facet | P Martinez-Vazquez |
| author_sort | P Martinez-Vazquez |
| collection | DOAJ |
| description | AbstractHigher Education frameworks have a strong focus on increasing students’ satisfaction. This vision increases expectations on academic performance that often derive from stringent output measures for staff. The combination of internal and external demands for workers, such as those derived from their interaction with society, could create inadequate working conditions, which highlights the need to develop objective, rational, and robust mechanisms to distribute roles and responsibilities more fairly. This paper introduces a work recognition model for managing higher education units. It accounts for individual effort per discretised academic activity over a range of teaching, research, and administration duties. The model integrates standard academic activities into a mathematical framework characterised by continuous derivable functions that can be used to visualise fluctuations of workload across a complete academic year. The established framework enables optimisation of workloads through redistribution, moving away from diagnosing issues experienced by individuals subject to imbalanced or unfair workloads, to propose a practical solution. It is also possible to enhance the architecture of the proposed model to incorporate further activity or allowances and potentially increase robustness. In addition, the numerical model is relatively easy to implement in a variety of platforms. The proposed model was tested on a case study including 26 academics, mixing three-legged and teaching-focused contracts, showing how it decreases the relative differences of workload by a proportion of 4:1, after redistribution. |
| first_indexed | 2024-03-08T23:08:11Z |
| format | Article |
| id | doaj.art-1457dcbbc2cf4f02a89d30eb966c4158 |
| institution | Directory Open Access Journal |
| issn | 2331-186X |
| language | English |
| last_indexed | 2024-03-08T23:08:11Z |
| publishDate | 2023-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Cogent Education |
| spelling | doaj.art-1457dcbbc2cf4f02a89d30eb966c41582023-12-15T10:31:08ZengTaylor & Francis GroupCogent Education2331-186X2023-12-0110210.1080/2331186X.2023.2248912Work recognition model for a higher education unitP Martinez-Vazquez0School of Engineering, University of Birmingham, Birmingham, UKAbstractHigher Education frameworks have a strong focus on increasing students’ satisfaction. This vision increases expectations on academic performance that often derive from stringent output measures for staff. The combination of internal and external demands for workers, such as those derived from their interaction with society, could create inadequate working conditions, which highlights the need to develop objective, rational, and robust mechanisms to distribute roles and responsibilities more fairly. This paper introduces a work recognition model for managing higher education units. It accounts for individual effort per discretised academic activity over a range of teaching, research, and administration duties. The model integrates standard academic activities into a mathematical framework characterised by continuous derivable functions that can be used to visualise fluctuations of workload across a complete academic year. The established framework enables optimisation of workloads through redistribution, moving away from diagnosing issues experienced by individuals subject to imbalanced or unfair workloads, to propose a practical solution. It is also possible to enhance the architecture of the proposed model to incorporate further activity or allowances and potentially increase robustness. In addition, the numerical model is relatively easy to implement in a variety of platforms. The proposed model was tested on a case study including 26 academics, mixing three-legged and teaching-focused contracts, showing how it decreases the relative differences of workload by a proportion of 4:1, after redistribution.https://www.tandfonline.com/doi/10.1080/2331186X.2023.2248912project allocation modelstaff workloadnumerical algorithm |
| spellingShingle | P Martinez-Vazquez Work recognition model for a higher education unit Cogent Education project allocation model staff workload numerical algorithm |
| title | Work recognition model for a higher education unit |
| title_full | Work recognition model for a higher education unit |
| title_fullStr | Work recognition model for a higher education unit |
| title_full_unstemmed | Work recognition model for a higher education unit |
| title_short | Work recognition model for a higher education unit |
| title_sort | work recognition model for a higher education unit |
| topic | project allocation model staff workload numerical algorithm |
| url | https://www.tandfonline.com/doi/10.1080/2331186X.2023.2248912 |
| work_keys_str_mv | AT pmartinezvazquez workrecognitionmodelforahighereducationunit |