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Cognitive Workload Analysis

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Cognitive Workload Analysis

Abstract.

The cognitive workload is the method used to measure the mental efforts of an individual to accomplish a cognitive task. Before the NASA task load index which terms cognitive workload as human-centred was identified, the workload was initially referred to as the amount of work that needed to be performed. This paper discusses the GOMS approach which is a framework for workload analysis used to give detailed method on experimenting scenarios, monitoring and coming up with effective tools to reduce workload. The paper also goes ahead and outlines the three methods used to measure the amount of workload which includes behavioural indicators, physiological indicators and subjective evaluation. Workload drives are factors that lead to the cause of workload. The difficulty of performing tasks might be as a result of various factors, for instance, task schedule, which involves the time frame required to perform a particular task before the deadline. Various factors that lead to work overload are also highlighted in the paper. This paper will conclude by giving an outline of the benefits of using cognitive workload analysis.

 

 

 

 

 

 

 

 

Cognitive workload analysis

Cognitive workload analysis involves processing information and react to it according to the surrounding and later on be in a position to make a decision (Goldstein, 2018).  It is used to identify scenarios in where there are chances of overload, identify the main cause of the overload and come up with strategies on how to reduce workload. To help achieve this, the GOMS (Goals, operators, methods, selection) approach is applied to improve the instructions between human and computers and increase efficiency. It is a theory of cognitive skills used in human-computer assignments. The model is used to increase the usability of a system. The methods are further divided into operators which are of a lower level (Dam, 2019). To apply the GOMS technique, there is a need for determining the following. First, goals, which defines the issues to be achieved and the set methods to accomplish them. It is a task to be performed.  Second, operations, which involve the necessary steps that need to be taken to execute a goal. Next, the methods, which include the procedures used to accomplish the goal and lastly, selection, where the user chooses one or more methods that might be used to help goal in accomplishment. For a successful model to occur, various principles are applied. First, there is a need for doing away with the unnecessary operators from the method used. Provision of error-recovery methods can also help in task performance and finally, making sure that the operators involved during cognitive skills are specific to the method used.

A workload is a form of strain relationship between human and the tangible materials surrounding them which could lead to poor performance and low speed in accomplishing a task. The workload in human beings can be measured in three categories. First, we have the subjective evaluation which is commonly used comparing to the other methods as it is easy to use and the cost of administering it cheap. NASA task tool index is the main indicator used here because of its reliability and sensitivity during experiments regarding changes in workload. Second, we have the behavioural indictors in which performance is measured depending on the quality of work, errors that have emerged and the time taken. A decrease in performance as a result of multiple task load could have resulted from capacity workload hence the poor performance. Lastly, we have the physiological indicators which use electrical conductance of the brain where EEGs (Electroencephalograms) are extracted from electrodes attached to the skull (Kendrick, Harwood, Feeest & Falones, 2019). This method is not quite reliable as some functions from deep within the skull are not encountered for during registration.

The demand which outlines the goals and performance criteria is the major cause of workload in the human brain. This may be as a result of time pressure working for more hours, technology overload or expectations which are unrealistic. Additionally, lack of support or minimal support can also is a cause of workload where one feels frustrated and undervalued when they lack support from colleagues. When an employee is not able to identify the role and task they are supposed to perform, they may end up getting stressed leading to mental overload. Training in the work environment is essential to equip the workers with the best knowledge on how to handle the task and their roles should be clearly defined. Lastly, we have a poor relationship with others. We are aware that one is not always in a position to relate well with everyone but that does not call for bullying others in the workplace (Svenska, 2020). Positive behaviour and restricting workers from sharing work-related information only could help reduce poor relationship which can make one’s mind overloaded. The behaviour of an operator may also be influenced by other factors for example noise, heat, cold, danger and other more that lead to workload.

Conclusion

Benefits of using cognitive workload analysis are that it is an innovation, cost-friendly and helps come up with objectives that will measure the efficiency of the task. The different task requires different methods of handling them.  The task can lead to workload if proper planning and schedule are not taken care of leading to the low quality of task performance or even not being in a position to hit the deadline.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

References

Dam, K. (2019, August 6). What is GOMS? How could it help you to increase usability in the system? Retrieved from https://uxplanet.org/what-is-goms-how-could-it-help-you-to-increase-usability-in-the-system-732655ab777b

Goldstein, E. B. (2018). Judgement, Decision and reasoning. In Cognitive Psychology: Connecting Mind, Research, and Everyday Experience (4th ed.). Boston: Cengage Learning.

Kendrick, R. M., Harwood, A., Feest, B., & Falcone, B. (2019, September 11). Frontiers | Theories and Methods for Labeling Cognitive Workload: Classification and Transfer Learning | Human Neuroscience. Retrieved from https://www.frontiersin.org/articles/10.3389/fnhum.2019.00295/full

Svenska, S. P. (2020, April 30). Psychosocial workload factors – tyosuojelu England – Occupational safety and health. Retrieved from https://www.tyosuojelu.fi/web/en/working-conditions/psychosocial-workload/factors

 

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