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260.714.81
Data Visualization Practice for Non-Expert Audiences

Location
Internet
Term
3rd Term
Department
Molecular Microbiology and Immunology
Credit(s)
1
Academic Year
2022 - 2023
Instruction Method
Asynchronous Online
Auditors Allowed
No
Available to Undergraduate
No
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Contact Name
Frequency Schedule
Every Year
Prerequisite

Introduction to Online Learning

Description
When you give a presentation that includes a graph or chart, are you aware of the choices you're making in designing that visualization? Do you have a process for defining the goal of the visualization and choosing the appropriate chart type based on that goal? Are you cognizant how your choices in chart axes, series color, and even line thickness affect the ability of your audience to correctly process the main point of the visualization? This course aims to give students practical experience in creating basic data visualizations in Excel for use in presentations and infographics for non-expert audiences that are based on research-driven design principles.
Introduces students to Gestalt principles of visual perception and pre-attentive processing in service of creating data visualizations in Excel and presenting in PowerPoint to non-expert audiences. Utilizes multiple chart and graph types in Excel to create diverse visualizations for the general public. Focuses on storytelling in design and visualization techniques in service of creating effective data-driven presentations for non-expert audiences. Concepts around data visualization in Excel are transferrable to other platforms (e.g., Tableau).
Learning Objectives
Upon successfully completing this course, students will be able to:
  1. Apply Gestalt principles of visual perception to data visualizations in Excel and PowerPoint
  2. Compare strengths and weaknesses of different chart types for clarity of communication to non-expert audiences
  3. Create data visualizations in Excel for interdisciplinary and lay audiences
  4. Evaluate data visualization work by peers for clarity of message to non-expert audiences
Methods of Assessment
This course is evaluated as follows:
  • 20% Quizzes
  • 50% Project(s)
  • 30% Peer-feedback
Special Comments

Offered through the R3 Center for Innovation in Science Education