Data · dataset · 2024
Analysing Gender Differences in Multitasking: A Data Simulation Approach
Listed in Teesside University Research Data Repository
Understanding the data model. 1.
Description
Libraries and Setup: • The script starts by importing two essential Python libraries: numpy and matplotlib.pyplot. • numpy: Used for numerical operations and data generation. • matplotlib.pyplot: Used for creating visualizations. 2. Aspects of Multitasking: • The script defines three key aspects of multitasking: • Task Switching Speed: How quickly an individual can switch between tasks. • Attention Allocation: How effectively an individual can allocate their attention to multiple tasks. • Task Completion Time: The time it takes to complete tasks. 3.
Data Simulation: • The script generates simulated data for 50 individuals (both women and men) for each multitasking aspect. • For Task Switching Speed and Attention Allocation, the performance scores are simulated using a normal distribution with: • Mean of 0.8 and standard deviation of 0.1 for women. • Mean of 0.6 and standard deviation of 0.1 for men. • For Task Completion Time, the performance scores are simulated using a normal distribution with: • Mean of 10 and standard deviation of 2 for women. • Mean of 12 and standard deviation of 2 for men. • These simulated values are stored in dictionaries women_data and men_data. 4.
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Visualization: • The script creates histograms to compare the distribution of performance scores for women and men across each multitasking aspect. • Each histogram is plotted with: • bins=20 for better granularity. • alpha=0.5 to set the transparency of the bars. • color='red' for women and color='blue' for men. • Titles, labels, legends, and grids are added for clarity. Analytical Insights The simulated data and resulting histograms offer several insights into the comparative performance of women and men in multitasking: 1.
Task Switching Speed: • Women: The histogram is centered around a higher mean (0.8), suggesting that women generally have better task switching speed. • Men: The histogram is centered around a lower mean (0.6), indicating relatively slower task switching speed compared to women. • Interpretation: The distribution shows that women, on average, switch tasks more quickly than men. 2. Attention Allocation: • Women: The data follows a similar trend with a mean of 0.8, showing effective attention allocation. • Men: With a mean of 0.6, men display less efficiency in attention allocation. • Interpretation: Women tend to allocate their attention more effectively across multiple tasks. 3.
Task Completion Time: • Women: The mean task completion time is 10 units, with most data points clustered around this value. • Men: The mean is higher at 12 units, indicating longer task completion times. • Interpretation: Women, on average, complete tasks faster than men, reflecting higher efficiency in task completion.
Links
Where it is published
- DOI doi.org/10.17632/7p9k4yzp72.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Psychology & Behavioral Science · Social Science · Women's studies
- Inferred from text
- Simulation 75%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/7p9k4yzp72.1 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:field:440509 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords["Women's Studies"] |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:psychology-behavioral | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[method].local:method:simulation | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |