Dana Center design principles: authenticity
eCOTS 2022 Workshop
Nicholas J. Horton and Benjamin S. Baumer
May 19, 2022
Dana Center Data Science Design Principle Framework
- The framework is copyright 2021 The Charles A. Dana Center at The University of Texas at Austin.
- The Dana Center has granted educators a nonexclusive license to reproduce and share copies of this publication to advance this work.
Link to Dana Center Design Principles
Design Principle: authenticity
The course presents data explorations that allow students to address relevant questions that arise in their communities.
Student perspectives
- Recognize specific ways in which mathematics and data are used in everyday decision making.
- Recognize questions that arise in the real world that can be addressed by exploring appropriate data.
- Contribute meaningful questions that can be addressed by exploring appropriate data.
- Identify bias and sources of bias in data, and describe the impact of bias in data on people and society.
- Experience in the process of collecting, cleaning, analyzing, and visualizing data to answer a data- based question of interest.
Faculty perspectives
- Provide opportunities to ask questions of data sets that are relevant to students, both in class and on assessments.
- Provide opportunities for students to ask questions about their school, community, or world that can be addressed by exploring appropriate data.
- Provide opportunities to investigate bias and the source(s) of bias in data and to discuss how bias impacts people and society.
- Provide students with real data, including data that require data processing and cleaning.
Small group discussion
Please take four minutes in groups to briefly discuss how you have incorporated Authenticity into your courses.
The group leader (person whose birthday is coming next) is asked to share one or two examples that arose in the discussion which resonated for the group.
How to operationalize?
Example 1: Open Case Studies
Example 2: ethics
