Dana Center design principles: assessment

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.

The course uses project- based assessments both as formative assessments and to evaluate student progress.

Assemble a collection of their work, which includes both data explorations that demonstrate understanding of the statistical problem- solving process and reflections on their learning process and their evolving understanding of the field of data science.
At the end of the course, have a portfolio of data science work that showcases their knowledge of data science and their technology skills. This portfolio might be shared with a potential employer or educational institution.

Provide students with projects through which they are exposed to new content and can demonstrate their ability to use this new content to answer questions through exploration of appropriate data. These projects will include products that demonstrate student learning and will be part of students’ portfolios.
Evaluate student progress throughout the course by considering students’ evolving portfolios as well as their reflections on their learning.
In the final project of the course, allow students freedom to decide the topic and methods used in their data exploration, so that they can bring together the various skills they will have developed over the course, allowing the teacher to assess student progress.