teaching workload
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Author(s):  
Abdul Rahim Razalli ◽  
Kamarulzaman Kamaruddin ◽  
Ong Eng Tek ◽  
Wong Kung Teck ◽  
Nurul Ain Mohd Daud

2021 ◽  
Vol 4 (2) ◽  
pp. p12
Author(s):  
Dr Warrick Long ◽  
Associate Professor Lisa Barnes ◽  
Professor Maria Northcote ◽  
Professor Anthony Williams

Continual reforms in the Australian Higher Education Sector result in ongoing significant changes to the experiences of the Australian academic. As a result, massification, internationalisation and corporatization form the landscape of academia in Australia. The Australian University Accounting Academic (AUAA) faces ongoing challenges and opportunities within this dynamic academic environment, and this study explores these challenges in relation to teaching themed issues that confront the AUAA. By using a questionnaire and interviews with AUAAs, three themes emerged, being curriculum, teaching workload, and the impact of online teaching. The “ASSET” support framework is developed from these conversations with the AUAA’s to help them become an “asset” to the university during these times of disruptive change instead of allowing the system to “gazump” them.


2020 ◽  
Vol 5 (1) ◽  
pp. 1-6
Author(s):  
Syadatul Saeda binti Mat Saleh ◽  
Najihan Awang Ali ◽  
Nurul Husna Jamian

Nowadays, it is more important to be as efficient as possible. Most of the teaching institutions, one of the essential tasks that is carried out every year or every semester are to allocate teaching workload. Teaching workload allocation refers to the teaching staff teaches which subject and group classes. The task is a time-consuming process. The best allocation will be one of the contributing factors to the teaching quality. In current practice to this department, the teaching load allocates manually through a trial-and-error manner using Microsoft Excel. This may lead to unfavourable results. In this study, we aim to propose an innovative approach to allocate teaching load to group courses using integer programming which able to optimize the teaching allocation while satisfying the teaching staff preferences and based on department policies as constraints. Primary data were gathered using google form among 12 lecturers with 8 courses and 45 group classes considered. A feasible solution will be solved using LINGO unlimited software and the model serves as the best tool to assist the head of the department to allocate teaching workload. It found that the model proposes as a suitable tool to be employed for teaching allocation.


Author(s):  
Hamimah Ujir ◽  
Shanti Faridah Salleh ◽  
Ade Syaheda Wani Marzuki ◽  
Hashimatul Fatma Hashim ◽  
Aidil Azli Alias

A standard equation on teaching workload calculation in the previous academic setting only includes the contact hours with students through lecture, tutorial, laboratory and in-person consultation (i.e. one-to-one final year project consultation). This paper discusses teaching workload factors according to the current higher-education setting. Devising a teaching workload equation that includes all teaching and learning strategies in the 21<sup>st</sup> century higher education learning setting is needed. This is indeed a challenging task for the academic administrators to scrutinize every single parameter that accounted for teaching and learning. In this work, we have discussed the parameters which are significant in teaching workload calculation. For instance, the conventional in-person contact with the students, type of delivery, type of assessment, the preparation of materials for flipped classroom as well as MOOC, to name a few. Teaching workload also affects quality teaching and from the academic perception, the higher workload means lower-quality teaching.


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