Identifying Key Questions and Metrics: Why Building a Culture of Data Literacy and Inquiry is an Essential Part of any Institutional Research Program

AUGUST 24, 2023

HUDSON HARPER, Education Data Strategist/Consultant

Institutional Research (IR) is a crucial part of any educational institution's strategic planning process. The goal of IR is to provide decision-makers with actionable data to help guide policy, program, and resource allocation decisions. The first step in any IR program is to identify the key questions that the school wants to answer and the metrics that will be used to measure progress.

Identifying Key Questions and Metrics

The questions and metrics identified should be aligned with the school's strategic goals and priorities. These questions could include things like:

  • What is the retention rate for first-year students?
  • How does our graduation rate compare to peer institutions?
  • What is the average salary of our graduates after one year of employment?
  • What is the percentage of students that complete internships before graduation?

Metrics might include things like student enrollment numbers, faculty-to-student ratios, or graduation rates. By identifying the key questions and metrics, institutions can ensure that they are collecting the right data to make informed decisions.

Gathering and Analyzing Data

Once the key questions and metrics have been identified, it's important to gather and analyze data to help answer those questions and track progress against those metrics. This can involve a variety of data collection methods, including surveys, focus groups, and data analysis tools. It's also important to ensure that the data being collected is accurate and reliable and that it is being used in a responsible and ethical manner.

Why a Culture of Data Literacy is Important

Developing a culture of data literacy and inquiry is crucial for the success of an institutional research program and the overall success of an educational institution. However, if staff and faculty lack a strong background in data analysis, fear of how data will be used can hinder the development of this culture and lead to ineffective decision-making based on assumptions or biases. Poor data culture can lead to missed opportunities, ineffective resource allocation, and ultimately harm the institution's reputation. Investing in training and support for staff and faculty, establishing clear guidelines and policies for data collection and use, building trust, and valuing the use of data can help prevent these negative outcomes and promote more effective decision-making and improved outcomes.

Building a Culture of Data Literacy

To build a culture of data literacy, educational institutions can take several concrete steps:

1. Provide Training and Support

One of the most important things an institution can do is provide training and support to staff and faculty. This can involve offering workshops, webinars, or other training sessions focused on data collection, analysis, and interpretation. In addition, institutions can provide access to data analysis tools and software and offer ongoing support to help staff and faculty use these tools effectively.

2. Establish Clear Guidelines and Policies

Establishing clear guidelines and policies around data collection, analysis, and use is an important step in building a culture of data literacy and inquiry. This includes guidelines for data security and privacy, policies around the types of data that can be collected and how it can be used, as well as a clear policy for distinguishing between data being used for inquiry versus data being used for evaluation. By establishing these guidelines and policies, institutions can foster trust between staff and faculty and the institution's leadership, which is essential for the success of an institutional research program and the overall success of the educational institution.

3. Foster Collaboration and Communication

Building a culture of data literacy also requires fostering collaboration and communication between staff and faculty. This can involve creating opportunities for staff and faculty to share data and insights, as well as encouraging collaboration on research projects and initiatives. By fostering collaboration and communication, institutions can help break down silos and encourage the sharing of best practices and insights.

4. Celebrate Successes

Finally, it's important to celebrate successes and recognize the contributions of staff and faculty who are working to build a culture of data literacy. This can involve highlighting successful research projects or initiatives, as well as recognizing staff and faculty who have made significant contributions to the institutional research program.

By taking these concrete steps, educational institutions can build a culture of data literacy and inquiry that supports effective decision-making and drives continuous improvement and innovation. While building this culture may take time and effort, the benefits of providing objective data-driven insights that inform effective decision-making are worth the investment.