During the Institute, learners are expected to dedicate approximately 4-5 hours per week (synchronous and asynchronous) to have an engaged and successful learning experience. We ask that participants actively plan the time they will spend on the institute each week, even on a daily basis. Once a week, we will hold a live, synchronous online meeting to discuss resources, activities, and projects in support of the five competencies:

All sessions will be Wednesdays, 3-4:30 p.m. ET, except for the launch session on Monday, January 22nd, which is 3-4pm ET.

  • Week 1:
    • January 22nd (Launch)
    • January 24th
  • Week 2: January 31st
  • Week 3: February 7th
  • Week 4: February 14th (Break Week - No Live Session)
  • Week 5: February 21st
  • Week 6: February 28th
  • Week 7: March 6th
  • Week 8: March 13th

Data Literacy Institute Competencies’ Learning Outcomes

Competency 1: Data Foundations

Learners will examine the why and how data matters in higher education. By the end of this competency, you will be able to:

  • Recognize and communicate the value of data to your higher education institution
  • Examine the data lifecycle - from collection through processing to storage and preservation and the varying perspectives at each step.
  • Identify your organization’s data governance policies, understand leading practices in data governance in higher education and assess alignment with your institution.

Competency 2: Data Discovery

Learners will explore key challenges in higher education using methods and tools to locate needed data, and understand data access processes and data definitions. By the end of this competency, you will be able to:

  • Explain the importance and nuance of research questions or user questions when identifying data sources and submitting data requests.
  • Describe the importance of asking questions to clarify the challenge/issue being researched.
  • Identify internal and external data sources available to you and relevant access processes and timelines.
  • Detail the meaning of data elements and determine whether the data suits your analytic needs.

Competency 3: Data Evaluation

Learners will identify and evaluate the quality of data in the context of a defined area of inquiry. By the end of this competency, you will be able to:

  • Identify various data categories and types.
  • Critically evaluate the quality of a dataset for completeness, accuracy, and timeliness relative to your context of inquiry.
  • Examine the initial data question and determine if revision is needed based on available and/or collected data.

Competency 4: Data Handling

Learners will assess the sensitivity of data that leads to security and privacy practices, as well as the roles and responsibilities of those who manage, receive, and/or use the data. By the end of this competency, you will be able to:

  • Discuss how to securely handle data based on classification (e.g., unrestricted vs. confidential).
  • Locate and articulate your institution’s information security and privacy policies.
  • Evaluate how federal and state regulations impact the handling of higher education data.
  • Support best practices regarding data sharing, storage and preservation and/or destruction.

Competency 5: Data Storytelling

Learners will recognize various elements and principles for visualization, interpretation and evaluation of the results. By the end of this competency, you will be able to:

  • Recommend ways to communicate data clearly, coherently, and in ways tailored to the needs of the target audience (including visualizations).
  • Interpret findings most meaningful to the defined challenge/issue.
  • Provide relevant background and context for data narrative.