ALS 1210 - Data Literacy: Cultivating Skills to Engage with Data

Fall, Spring. 1 credit. Student option grading.

A. Shea.

The ability to find, analyze and utilize data helps one communicate, interpret and engage with the world around them. Yet there is a divide between those who can work with and understand data and those who cannot. Ownership and manipulation of data is largely handled by corporations, researchers and government. How does a more diverse population gain access to the know-how to make sense of data? This class aims to equip students from a variety of non-technical backgrounds with the necessary skills to engage with data in meaningful ways (both quantitative and qualitative data). The class approaches data literacy as part of a broader process of inquiry into the world – not from a math or statistics-centric point of view.

Outcome 1: Outcome 1: Describe the strengths and limitations of the following data types: 1) self-reported data, 2) observational or trace data, and 3) experimental data.

Outcome 2: Outcome 2: Articulate real-world examples that demonstrate the harmful consequences of reliance on biased datasets and describe solutions to mitigate bias and such harmful consequences.

Outcome 3: Outcome 3: Identify sources for locating open and reusable datasets.

Outcome 4: Outcome 4: Apply FAIR data principles to evaluate a dataset.

Outcome 5: Outcome 5: Utilize open-source, web-based tools for simple data cleanup & analysis.