Data Literacy with Data Commons
“Data Literacy with Data Commons” comprises curriculum/course materials for instructors, students and other practitioners working on or helping others become data literate. This includes detailed modules with pedagogical narratives, explanations of key concepts, examples, and suggestions for exercises/projects focused on advancing the consumption, understanding and interpretation of data in the contemporary world. In our quest to expand the reach and utility of this material, we assume no background in computer science or programming, thereby removing a key obstacle to many such endeavors.
For more background about the course, see our FAQs page.
We embarked on a mission to imagine a Data Literacy curriculum aimed at anyone and everyone who consumes data and aspires to correctly understand and interpret it to help with better decision-making.
We list the following core objectives of such a curriculum:
- Exposing students (and practitioners) to the basics of data comprehension and interpretation.
- Introducing some basic and intermediate data-driven decision making concepts.
- Explicitly cater to the needs of students (and practitioners) who have no prior programming experience and a limited exposure to basic statistical concepts.
- Adopt a narrative-based approach to appeal to a wide range of audiences.
- Grounding most/all examples and illustrative assignments on real data.
- Using as many of the out-of-the-box and freely available data exploration tools to preclude any advanced or specialized knowledge.
- Make the curriculum materials openly available and support extensive customizations for any instructors who wish to adopt components/modules to suit their needs.
We suggest only the following prerequisites for this curriculum:
- High-School level Mathematics (basic).
- High-School level Statistics (basic).
Data Literacy with Data Commons is constantly a work in progress and we aim to keep making additions and complete the “TBD” modules over time. If there are discrepancies or if you do not find what you are looking for and/or if you would like to contribute to this effort by helping develop more content (or have suggested corrections), we would love to hear from you at email@example.com.
Finally, if you end up using any of this material or find it useful, we would love to hear from you at firstname.lastname@example.org.