Digital Module 17: Data Visualizations: Effective Evidence‐Based Practices https://ncme.elevate.commpartners.com.
Saved in:
| Title: | Digital Module 17: Data Visualizations: Effective Evidence‐Based Practices https://ncme.elevate.commpartners.com. |
|---|---|
| Authors: | Gregg, Nikole1 (AUTHOR), Leventhal, Brian C.1 (AUTHOR) |
| Source: | Educational Measurement: Issues & Practice. Fall2020, Vol. 39 Issue 3, p139-140. 2p. |
| Subject Terms: | *Best practices, *Visualization, Data modeling, Software measurement, Statistical measurement, Statistical software |
| Abstract: | In this digital ITEMS module, Nikole Gregg and Dr. Brian Leventhal discuss strategies to ensure data visualizations achieve graphical excellence. Data visualizations are commonly used by measurement professionals to communicate results to examinees, the public, educators, and other stakeholders. To do so effectively, it is important that these visualizations communicate data efficiently and accurately. These visualizations can achieve graphical excellence when they simultaneously display data effectively, efficiently, and accurately. Unfortunately, measurement and statistical software default graphics typically fail to uphold these standards and are therefore not suitable for publication or presentation to the public. To illustrate best practices, the instructors provide an introduction to the graphical template language in SAS and show how elementary components can be used to make efficient, effective, and accurate graphics for a variety of audiences. The module contains audio‐narrated slides, embedded illustrative videos, quiz questions with diagnostic feedback, a glossary, sample SAS code, and other learning resources. [ABSTRACT FROM AUTHOR] |
| Copyright of Educational Measurement: Issues & Practice is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
|
Full text is not displayed to guests.
Login for full access.
|
|
| Abstract: | In this digital ITEMS module, Nikole Gregg and Dr. Brian Leventhal discuss strategies to ensure data visualizations achieve graphical excellence. Data visualizations are commonly used by measurement professionals to communicate results to examinees, the public, educators, and other stakeholders. To do so effectively, it is important that these visualizations communicate data efficiently and accurately. These visualizations can achieve graphical excellence when they simultaneously display data effectively, efficiently, and accurately. Unfortunately, measurement and statistical software default graphics typically fail to uphold these standards and are therefore not suitable for publication or presentation to the public. To illustrate best practices, the instructors provide an introduction to the graphical template language in SAS and show how elementary components can be used to make efficient, effective, and accurate graphics for a variety of audiences. The module contains audio‐narrated slides, embedded illustrative videos, quiz questions with diagnostic feedback, a glossary, sample SAS code, and other learning resources. [ABSTRACT FROM AUTHOR] |
|---|---|
| ISSN: | 07311745 |
| DOI: | 10.1111/emip.12387 |
