The plan’s goals include for a majority of students — more than 90% — to reach a foundational level of data literacy, as well as goals for subsets of students engaged in data-intensive academic programs and experiences to reach advanced levels of data competency. The success of our data competency QEP is attainable through:

a) the creation of targeted and specific learning outcomes (SLO’s) that can be implemented into our Elon curriculum alongside

b) a commitment to connect and elevate programs and centers that focus on data and its relative competencies while also

c) providing new resources and opportunities to all Elon students to develop data competency skills.

A data competent individual will be able to proficiently:

  • Access data – identify, locate, or collect data relevant to a context or issue while considering the quality, trustworthiness, and ethical treatment of data;
  • Prepare data – store, organize, clean, and appropriately manipulate data to support analysis and representations;
  • Analyze data – explore, visualize, and model data to gain information that is pertinent to the context or issue;
  • Interpret findings – make claims and propose actions based on the information gained through analysis, while identifying and addressing uncertainty, limitations, potential biases, and ethical ramifications; and
  • Communicate findings – create audience-targeted multi-media explanations that give a complete and honest delivery of findings.

These steps are not necessarily linear; the order of actions may vary according to field, dataset, and context, and can also be iterative.