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Task Difficulty and Time Constraint in Programmer Multitasking: An Analysis of Prospective Memory Performance and Cognitive Workload

Task Difficulty and Time Constraint in Programmer Multitasking: An Analysis of Prospective Memory Performance and Cognitive Workload

Premjit K. Sanjram, Meenakshi Gupta
Copyright: © 2013 |Volume: 4 |Issue: 1 |Pages: 23
ISSN: 1948-5018|EISSN: 1948-5026|EISBN13: 9781466631267|DOI: 10.4018/jgc.2013010103
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MLA

Sanjram, Premjit K., and Meenakshi Gupta. "Task Difficulty and Time Constraint in Programmer Multitasking: An Analysis of Prospective Memory Performance and Cognitive Workload." IJGC vol.4, no.1 2013: pp.35-57. http://doi.org/10.4018/jgc.2013010103

APA

Sanjram, P. K. & Gupta, M. (2013). Task Difficulty and Time Constraint in Programmer Multitasking: An Analysis of Prospective Memory Performance and Cognitive Workload. International Journal of Green Computing (IJGC), 4(1), 35-57. http://doi.org/10.4018/jgc.2013010103

Chicago

Sanjram, Premjit K., and Meenakshi Gupta. "Task Difficulty and Time Constraint in Programmer Multitasking: An Analysis of Prospective Memory Performance and Cognitive Workload," International Journal of Green Computing (IJGC) 4, no.1: 35-57. http://doi.org/10.4018/jgc.2013010103

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Abstract

The present study investigates how task difficulty and time constraint affect prospective memory (ProM) performance in programmer multitasking (N = 60). The results indicate that an increase in task difficulty and time constraint has a detrimental effect on ProM performance. Moreover, participants are able to successfully complete fewer difficult programs as compared to easier programs regardless of time constraint. Analysis shows that difficulty of the programming problems does not necessarily have a significant effect on cognitive workload (in short, workload) experienced by the programmers. Time constraint has a significant effect on workload experienced by the programmers. The results not only suggest a ProM performance decrement under high urgency (HU) as compared to low urgency (LU) but also show that time constraint has a significant effect on workload. Multiple regression analysis reveals that temporal demand is the most critical dimension of workload which explains 46% of the variation.

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