A longstanding folk belief suggests that 'busy' people possess the ability to get more done than others. Busyness, defined as the demands of everyday life, has been shown to generate cognitive load, which has been called 'cognitive busyness.' Although most cognitive theory would deny the possibility that cognitive load may enhance performance, some recent research may support the possibility. Cowan's 1988 information-processing model was used to study how measures of everyday busyness correlated with performance on cognitive tasks. The research question addressed whether any combination of such measures, in combination with working memory, could predict performance on such tasks. 92 participants, paid workers with Amazon Mechanical Turk, engaged in an online process, starting with completion of a validated self-report instrument to measure busyness. They then participated in 2 activities, structured as games and designed to measure working memory and cognitive performance. Multiple regressions, linear and nonlinear, were used to identify significant predictors of performance. Results of the analyses did not reveal any evidence for significant relationships between the variables. Additionally, 'volitional busyness' did not appear to enhance, or even affect, performance on a planning task. Further research exploring the effect of these variables on a working memory-based task may be worthwhile, if only to confirm the present findings. This project might benefit linguists tracking semantic change, showing how a term may adopt an entirely different meaning and suggesting further refinement in identifying such shifts over the years; psychologists exploring cognitive load and its effects; and social psychologists interested in making corrections to popular perceptions of the value of tradition gender-associated tasks.
| Identifer | oai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-4340 |
| Date | 01 January 2017 |
| Creators | Watson, Graham |
| Publisher | ScholarWorks |
| Source Sets | Walden University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Walden Dissertations and Doctoral Studies |
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