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# System prepended metadata

title: Assessment 3 - Grading

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# Assessment 3 - Dashboard Rubric

[toc]

## Metrics

### C1 - How many charts in Tableau
Does this correlates with the Analytical Questions?

### C2 - How many charts in the Dashboard

### C3 - Is the dashboard interactive?
Which type of interaction?
* Filter
* Drill Down
* Tooltip

### C4 - Does the dashboard answer the business question?
Based on the topic of the dashboard (impact of Covid on crude mortality rate in 2022) and the user input, here is a 4-level rubric table for evaluating "Does the dashboard answer the business question?":

| Level | Description | Feedback |
|-|-|-|  
| Accomplished | The dashboard clearly shows the impact of Covid on crude mortality rate (per 1000 population) in 2022, including trends over time and comparisons to previous years. Useful metrics like excess deaths are calculated and displayed effectively. | Excellent job capturing the impact of Covid on mortality in 2022 and presenting the data in a clear, insightful way. Consider adding more context on factors influencing trends. |
| Competent | The dashboard shows crude mortality rate data for 2022 and includes some analysis of Covid impact, such as comparisons to prior years. Metrics are relevant but could be presented more effectively. | Good attempt at answering the question. Ensure you are prominently displaying the key metric (crude mortality rate) and providing helpful context on factors driving trends. |   
| Progressing | The dashboard shows mortality data but does not effectively capture the impact of Covid. Some irrelevant metrics distract from the analysis. More work needed to answer question. | The mortality data is a good start, but does not sufficiently capture the impact of Covid in 2022. Refocus your analysis only on the most relevant metrics that help answer that specific question. |
| Beginning | The dashboard fails to show mortality rate data or draw any insights about the impact of Covid in 2022. It does not attempt to answer the business question. | The dashboard does not attempt to answer the stated question about the impact of Covid on crude mortality rate in 2022. Go back and refocus your metrics and analysis to address that specific question. |

To summarize, an effective dashboard should prominently display crude mortality rate data for 2022, ideally with historical comparisons to previous years. It should focus analysis on quantifying the impact of Covid on mortality in 2022 specifically, such as through excess death metrics. Factors influencing trends should be explored to provide context. Only the most relevant data and visualizations should be included to clearly answer the stated business question.

Citations:
[1] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5688382/
[2] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9977530/
[3] https://www.geckoboard.com/best-practice/dashboard-design/
[4] https://retool.com/templates/customer-feedback-dashboard
[5] https://www.rcampus.com/rubricshowc.cfm?code=JXA57A5&sp=yes
[6] https://www.toptal.com/designers/data-visualization/dashboard-design-best-practices
[7] https://www.sisense.com/blog/4-design-principles-creating-better-dashboards/
[8] https://mopinion.com/building-your-user-feedback-dashboard-the-easy-way/
[9] https://www.smartsheet.com/rubric-templates
[10] https://www.yellowfinbi.com/blog/critical-elements-of-effective-bi-dashboards
[11] https://help.tableau.com/current/pro/desktop/en-us/dashboards_best_practices.htm
[12] https://clickup.com/blog/rubric-templates/
[13] https://www.betterevaluation.org/methods-approaches/methods/data-dashboard
[14] https://www.datapine.com/blog/dashboard-design-principles-and-best-practices/
[15] https://www.niu.edu/citl/resources/guides/instructional-guide/rubrics-for-assessment.shtml
[16] https://eprints.whiterose.ac.uk/184215/1/dashboard_evaluation.pdf
[17] https://charitableadvisors.com/developing-an-effective-dashboard-and-key-performance-indicators/
[18] https://ncea.org/NSBECS/NSBECS/Assessment_Tools/Benchmarks%20Rubrics/Dashboard_for_Rubric_Scoring.aspx
[19] https://visionedgemarketing.com/proper-care-feeding-marketing-dashboards-7-criteria-marketing-dashboards/
[20] https://towardsdatascience.com/dashboard-design-key-performance-indicators-and-metrics-2b13745f5b2f
[21] https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1073&context=librarian_pubs
[22] https://www.researchgate.net/publication/320668862_Evaluation_of_Effective_Dashboards_Key_Concepts_and_Criteria
[23] https://www.ibm.com/docs/en/elm/6.0.5?topic=dashboard-creating-effective-dashboards
[24] https://www.linkedin.com/advice/0/how-do-you-evaluate-usability-usefulness-system
[25] https://www.polymersearch.com/blog/dashboard-report-best-practices


## C5 - Dashboard Rubric
### Grade 4 - Accomplished
- Data visualizations are visually appealing, easy to interpret, and effectively communicate key insights
- A variety of interactive data visualization types are used (charts, graphs, gauges, maps, etc.)
- Interactive features like filters, tooltips, and drill downs allow seamless exploration of the data
- The dashboard layout and flow enables intuitive analysis and discovery

### Grade 3 - Competent  
- Data visualizations communicate information clearly with some visual appeal
- Some interactivity enables users to explore parts of the data more in depth
- The layout provides adequate flow for analysis, though some improvements could be made

### Grade 2 - Progressing
- Data visualizations are basic and communicate information without much visual appeal 
- Limited interactivity restricts deeper analysis of the data
- The layout is functional but does not facilitate intuitive analysis and discovery  

### Grade 1 - Beginning
- Data visualizations are confusing, cluttered, or do not effectively communicate key information
- Lack of interactivity severely limits analysis of the data
- The layout impedes understanding of the data and does not enable discovery
