Data can provide many powerful benefits in higher education, from promoting student success and improving alumni outcomes to better strategies for achieving institutional initiatives. Data literacy, which includes understanding and applying data research tools and methodology, is essential for appropriately leveraging data to meet those goals. A lack of data literacy can result in inaccurate conclusions that negatively affect outcomes for individual students and entire institutions.
The advantages of data literacy make it a valuable skill for professionals at all levels in higher education. Educators and administrators alike can use data to improve learning outcomes for specific lessons, explore new approaches to education and develop policies and procedures that enhance the institution.
Basic data literacy begins with four key components: crafting relevant research questions, using appropriate methodology, understanding terminology and effectively exploring data.
The proper questions are the foundation for effective research and the use of data. After determining the knowledge you hope to gain from your research, you can then develop the questions that will best provide that information. This process will ensure the collected data contributes to your goals and prevents wasted time on questions that aren't relevant or actionable.
Your research questions also help inform the research methods that will best serve your data needs, whether your particular focus is on current student achievement or alumni outcomes.
One such approach might be to use the New World Kirkpatrick Model as a basis. Depending on need, there are four possible levels of evaluation that should guide your research method and analysis:
Level 1: Reaction
Ask questions to determine if programs or events are well-received, engaging and relevant for participants.
Level 2: Learning
Identify the knowledge or skills participants gain through the program or activity.
Level 3: Behavior
Go more in-depth on the outcomes of the event or activity under study to determine how well participants apply the new information or understanding they have gained.
Level 4: Results
Research questions around results compose the final level, asking how outcomes are achieved based on the participants’ experiences.
The most effective methodology to use will depend on the type of program you're implementing, the research questions you want to answer and the available sources of information. Based on these factors, you can determine whether quantitative, qualitative or mixed methods will best serve your research and data collection goals.
Quantitative research focuses on the collection and analysis of numerical data to identify patterns or relationships. Quantitative methods are objective by nature and take the form of experiments and surveys with a large subject base. Qualitative research methods allow for a different depth of understanding as they focus on individual experiences, the context of the program being studied and even the specific words participants use to talk about the program. Interviews and focus groups are common to a qualitative approach.
A mixed-methods approach can help you leverage the advantages of both types of research, as it combines quantitative and quantitative methods for a complete understanding.
Another key to data literacy across your institution is to define the terms used in your research. Educators, administration and other stakeholders may understand specific terms differently based on their background and experience. Defining terms like graduation year and program will ensure that your study and its results are universally understood and appropriately applied.
The processes and systems your institution already has in place can help you clarify the essential terms used in your research. Your organization may even have a data dictionary that can serve as a baseline for explaining and using specific terms and programs. You can also take advantage of resources such as the Graduate Explorer Data Dictionary from Steppingblocks to create an institution-wide understanding of the data you collect and what it means.
The right data tools and resources can make all the difference in the effectiveness and efficiency of your data analysis. Data exploration tools can also provide new ways to understand, visualize and communicate the results of your research, making it easier to take action. This facilitates better achievement of student, classroom and institution-level goals.
To understand the information collected in your particular program or event, begin by looking at the tools and resources your institution provides to help you explore the information you've collected. These tools may be readily available and come with the added benefit of support from colleagues who have already used them.
Additional tools for analysis can further enhance your data exploration and understanding. One example is Tableau, a free data visualization software that features templates to jumpstart your data review and reporting.
Understanding how research questions, methodology, defined terms and data exploration contribute to your research is just the beginning of data literacy. A deeper study of each of these areas will equip you to better contribute to alumni outcomes, student success and the overall goals of your institution.
Some areas to consider are the aspects of data literacy you would most like to strengthen and the additional information you need to make better use of student and alumni data in your specific role. It's also important to look at the gaps in your knowledge of data and your institution’s gaps to make impactful changes in research and results.
If you're ready to take the next steps in data literacy and research, contact us today for a free consultation or to receive a free Graduate Outcomes report for your institution.