For many faculty members, data can feel intimidating. Spreadsheets, statistics, and rows and columns of numbers seem very distant from the day-to-day work of teaching. But data doesn’t have to be scary. If we shift our perspective, we can start to see data as another way to tell a story, of understanding what’s working in our teaching and what isn’t. Data can highlight actions and their impact, and provide a way to ask, “Did this work?”
Many colleagues have told me they were hesitant to rely on analytics. “I know when my students are struggling,” one of them said to me. And I don’t doubt she was right—years of experience had sharpened her instincts. But when she started tracking discussion board engagement patterns, she noticed something surprising: students who did not post early often never posted at all. With this insight, she adjusted her approach, adding a quick, informal check-in mid-week. As a result, my colleague was able to affect a dramatic increase in participation. Her experience told her something was off, but data helped pinpoint exactly where and how to intervene.
Good teaching involves an ongoing process of reflection, iteration, and growth. It asks faculty to have the courage and curiosity to experiment. And data plays a crucial role in this process by enabling faculty to shift from passive observation to active intervention, empowering them to take charge of their instructional choices.
Developing Metrics That Matter
One big challenge for faculty can be determining what to measure to begin with. We may naturally track grades, participation, or assignment completion rates. But those numbers alone won’t tell the full story. Data starts to become useful when it informs teaching strategies—when it helps us understand not just what’s happening, but why!
Think for a minute about the teaching and learning areas, for example, in an online course. The discussion forum might be a useful location to scout. If only half your students engage in week one, that can signal something is amiss. Maybe the prompt isn’t resonating. Maybe students aren’t sure what’s expected or they’re hesitant to be the first to post. Instead of treating low engagement as a fixed reality, data invite us to consider other perspectives. What can we do to encourage participation? Could a video introduction or a mid-week follow-up make a difference? Might providing brief models of successful posts by previous students help inspire current learners? Small shifts, informed by the patterns we see, can have a big impact.
Data can’t replace intuition. But faculty can create an environment where data and intuition complement each other—to highlight trends, validate hunches, and help us see what we might otherwise miss.
Data as a Tool for Continuous Learning
Data isn’t just about measuring. It provides a pathway that facilitates learning, and can lead to iterating practices, including reflecting on one’s processes. It allows faculty to figure out what works and to apply those insights to improve student learning.
In one of my courses, I experimented with personalized video feedback. The quantitative results told one story. Grades showed only a slight variation. But submission rates for the final paper jumped from 87.2% to 96.2%. And the qualitative feedback was more revealing. Students felt a stronger connection to me as their instructor. One student commented, “This course and your presence have inspired me to learn and grow in essential areas. I am now experiencing firsthand why this class is a solid foundation for building my communication.”
And they understood my comments more clearly – and they could have the proper impact. One student reflected, “Your recognition of my strength in this area is a huge accomplishment for me.”
Numbers showed a trend, but the real takeaway came from students’ words. Data helped me refine my approach, not by pushing me toward a rigid, numbers-driven system, but by reinforcing something fundamentally human: students respond to presence and to connection. Knowing that there’s a real person on the other side of the screen matters.
A colleague took this insight further. Instead of just adding video feedback, she began incorporating brief check-in messages. “I used to wait until the final draft to give feedback,” she told me, “but when I started sending a quick message during the drafting process, students responded!” The most valuable educational insights often arise from the tension between what can be easily measured and what truly impacts learning. While numbers offer clarity, faculty intuition and student feedback add depth.
Scaling Data-Driven Teaching Across Institutions
Too often, institutions rush to slap together new dashboards before they even define the problems they’re trying to solve. A dashboard filled with charts and metrics is only useful if it leads to meaningful action. That’s why a data initiative should start with careful problem definition—asking what specific student learning or engagement aspects need improvement and why these particular issues matter.
For faculty–those interacting with students day to day in the classroom—the key is asking the right questions:
- What trends am I seeing in my classroom? Regularly reviewing participation and assignment completion can reveal when students start to disengage—giving us a chance to step in before they fall too far behind. If student engagement drops off in the middle of the term, faculty can intervene earlier by sending reminders, offering additional resources, or changing how they present the material.
- What small changes can I make? Simple adjustments—like tweaking an assignment prompt or adding a mid-week check-in—can have a significant impact without requiring a complete course redesign. If a particular assignment has a low completion rate, consider refining the instructions, adding more scaffolding, or offering a mini-lesson on the key concepts.
- What’s actually working? Reflection matters. If we send an extra reminder and participation improves, great! If not, what else can we try? Teaching isn’t about finding a single perfect strategy. It’s about staying flexible, responding to students, and continually refining our approach. Did participation improve after sending a mid-week reminder? Did the tweak to the assignment instructions lead to higher completion rates? This iterative approach transforms data from a static measure into a dynamic tool for improvement.
Institutions play a crucial role in supporting this work. Access to dashboards and analytics platforms is helpful, but training, socialization, and discussion are just as important. One of the most successful institutional initiatives I’ve seen started not with dashboards, but with conversations. Faculty from different disciplines met regularly to discuss what data they found meaningful. These discussions led to changes that weren’t just about numbers but about creating learning environments that responded to student needs.
Keeping the Focus on What Matters
At its best, data can help sharpen our teaching by supporting our hunches and leveling up our intuition in order to make informed decisions that support real student learning. But numbers will never replace experience. Trends will never tell the whole story. The real magic of teaching happens in the human connections we build, the moments of insight and engagement that aren’t always measurable. As one faculty member put it, “I don’t want data to tell me how to teach—I want it to help me teach better.” That’s the goal. Not just dashboards and metrics, but deeper understanding and meaningful change.
