Credit Hours: 3
Instructional Mode: Online & Asynchronous
Student Collaboration: Weekly hour-long small group virtual meetings (student choice of meeting synchronously or asynchronously)
Faculty Designer: Dr. Martina Rau, Department of Educational Psychology professor
Instructor: Maria Widmer, UW-Madison MERIT Instructional Designer
“This course allowed me to step outside my comfort zone, without being too intimidating. I feel like in other communications-related courses, instructors throw you into the deep end and have you present work to large groups. Forming drafts, revising them, and presenting only to our small group felt safe AND like I was growing my skills a ton!”
Student end-of-course evaluation, fall 2023
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EdPsych 615 introduces students to communication methods using learning analytics data. Presentation modes include verbal conversations and visual representations. The course addresses questions including: What data is consumable? How can we make this data meaningful for a client? Students practice with stakeholder reports and presentations, which allows engagement in meaningful and effective communication strategies to enhance understanding of learning analytics data. Students will:
- Describe the benefits of data visualization for learning analytics.
- Evaluate and select visualizations that are appropriate for a given data story, context, and audience.
- Code and create new information visualizations.
- Discuss practices, issues, challenges, and opportunities surrounding the use of learning analytics visualizations.
- Identify and use appropriate accessibility strategies for visualizations.
Why this course?
It’s one thing to perform an analysis. It’s quite another to talk about it, write about it, and present it. This course is designed to take an analysis and turn it into action. Students use one of their own analysis from a prior course, and present it in multiple modalities to a multiple potential stakeholders.
How do students learn in 615?
Students engage with short (10-15 minute) video lectures, perform visualization critiques, work on a series of communication artifacts (data viz in Tableau, written 1-page summaries, PowerPoint presentations, etc.), and meet with their collaborative group on a weekly basis to support each other’s artifacts.
Schedule of Topics
| Week | Topic |
| 1 | Why Visualization? |
| 2 | The Human Visual System & Information Processing |
| 3 | Simple Goals: One- and Two-Dimensional Graphs |
| 4 | Complex Goals: Graphs for Analytical Patterns |
| 5 | Aligning Visualizations with the Audience |
| 6 | Workshop #1 |
| 7 | Judgment, Inference, & Decision-Making |
| 8 | Learning Analytics Visualizations |
| 9 | Communication: Storytelling with Data |
| 10 | Communication: Storyboarding |
| 11 | Workshop #2 |
| 12 | Ethics: Misleading Graphs |
| 13 | Ethics: Misleading Stories |
| 14 | Final Presentations |
What students say
“This course is great! Nuanced and balanced, it almost feels like a treat to take.”
Student end-of-course evaluation, fall 2023
Instructor Insights
“I find great joy in teaching EP615 because the verbal, written, and visual communication skills that students develop are applicable in so many domains of professional practice. Students are often happily surprised to see how much their communication artifacts change and improve over the course of the semester through rehearsal, peer review, and iterative design. Transforming raw data into actionable insights—and clearly communicating those insights to relevant decision makers—is an essential skill for learning analysts working to make a difference in the field of education.” – Maria Widmer
Sample Week
Materials including videos, assignments, and readings will be available at the beginning of each week. Below is a suggested guideline for spacing out assignments in order to provide enough time for work, interactions with the instructors, students, and student group, etc. While the rhythm may change depending on the week, students can generally expect to engage with course materials and each other in this way and thus may plan accordingly. Note the purposeful balance between individual and group assignments. Below is a sample from Week 4 of this course:
| Week 4: | Complex Goals: Graphs for Analytical Patterns | ||||||
| Monday | Tuesday | Wednesday | Thursday | Friday | Saturday | Sunday | |
| Learning Objectives | Understsand the critical distinction between exploratory and explanatory visualizations; Work with choropleth maps and dot strip plots in Tableau | ||||||
| Core Reading(s) | Few (2009); Trafton et al. (2000) | ||||||
| Individual Artifact | Review Tableau artifact by Thurs pm | ||||||
| Critique | Critique and submit by Thurs pm | ||||||
| Peer Workshop | Respond to Design Lab questions by Mon pm | ||||||
What More Students are Saying:
- On immediate application:
- On building confidence:
- On instructor feedback:
- On balance:
- On organization:
This class has already influenced how I approach presenting information at work! I have loved learning about data viz and will absolutely continue learning more about the subject. – End of semester evaluation, 2022
This course provided me with the necessary skills to help me with two separate internship opportunities. I would feel much more comfortable and confident in applying for positions that require experience with visualizations because of this course. – End of semester evaluation, 2022
She [the instructor] was incredibly supportive and gave deeply thoughtful feedback. She was a joy to study under, I would love to have more opportunities to learn from her in the future. – End of semester evaluation, 2022
This course was an excellent balance of theory and practice. I found it strengthened my analytical skills with respect to visuals in many different modes (not just Tableau) and it also improved my writing and communication skills. – End of semester evaluation, 2023
I thought the course was well structured and effective. The opportunity for group work was really beneficial. I enjoyed learning how to use Tableau and feel that my data communication skills have increased. – End of semester evaluation, 2023
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