The Data Literacy concepts below are focused on teaching individuals how to be entry-level, informed consumers of data. The concept of data can often sound confusing or overwhelming, but just think of data as a form of information, just in a different format than words. Data Literacy focuses on understanding what data is, how to handle and use data, how to interpret graphs and visualizations of data, and how to effectively draw conclusions from data to inform decisions. We have split these concepts into three levels: Data Basics, Understanding and Using Data, and Evaluating Data.
Below are sample learning goals for each of the three levels. If you are interested in partnering with a library professional, this will give you an idea of some of the goals that we have designed for each level. If you have goals that you’d like to see added, please contact Millicent Weber, Data Science Librarian.
Data Basics
Sample Student Learning Objectives:
- Students will be able to define key data literacy terms (e.g., data, dataset, variable, observation, quantitative vs. qualitative data).
- Students will be able to identify different types and sources of data (e.g., primary vs. secondary, structured vs. unstructured).
- Students will be able to recognize the role of data in everyday decisions and various industries.
- Students will be able to describe basic methods of data collection (e.g., surveys, sensors, experiments).
Understanding and Using Data
Sample Student Learning Objectives:
- Students will be able to interpret tables, charts, and graphs (e.g., bar graphs, line charts, scatterplots, histograms).
- Students will be able to summarize data using basic descriptive statistics (mean, median, mode, range, standard deviation).
- Students will be able to use spreadsheets or basic tools (like Excel) to organize and manipulate data.
- Students will be able to ask and answer simple questions using data (e.g., “What does this data suggest?”).
- Students will be able to identify patterns, trends, and outliers in data visualizations.
- Students will be able to formulate hypotheses and support or refute them using appropriate data.
Evaluating Data
Sample Student Learning Objectives:
- Students will be able to assess the credibility and reliability of data sources.
- Students will be able to identify potential bias in data collection, interpretation, or presentation.
- Students will be able to evaluate whether a dataset is appropriate and sufficient to support a given claim.
- Students will be able to critique data visualizations for misleading or unethical design choices (e.g., truncated axes, cherry-picking).
- Students will be able to understand the importance of ethical data use, including privacy and consent.
- Students will be able to communicate findings from data clearly and accurately, acknowledging limitations.
