How program leaders use curriculum mapping and student performance data for better program evaluation
Program leaders in health professions education are expected to evaluate curriculum effectiveness, track student outcomes, and prepare for accreditation, all while managing data scattered across multiple systems. The result is often an overwhelming process where more time is spent gathering data than using it to drive decisions.
In this Enflux panel discussion, Staci Miller, Head of Customer Success at Enflux, speaks with Melissa Lazinski, Program Director of the PT program at the University of South Florida, and Rebecca Ditwiler, DPT Curriculum Coordinator, about how their program moved from fragmented data to a more connected, insight-driven approach.
They share how integrating curriculum mapping, assessment data, and student performance data improves higher education program evaluation, strengthens faculty alignment, and supports accreditation readiness. The conversation highlights practical strategies for connecting data sources, improving tagging processes, and turning complex data into actionable insights.
The challenge of fragmented data in program evaluation and curriculum mapping in higher education
Enflux: When you first stepped into your roles, what made you realize that your program lacked a clear, program-level view of your data?
Melissa Lazinski: When I first stepped into my role, and even before that, when I chaired the Outcomes Committee, I found myself going to multiple people and digging through different files just to gather basic information. Much of our data was siloed and essentially “owned” by different individuals across the program, making it difficult to compile even a simple report. And that was just the first step; actually interpreting the data came several steps later.
Before becoming Program Director, one of my top priorities was to create a more organized system, something that would allow us to compile important information in one place and make it accessible quickly and efficiently. Real-time access to information was also critical. I wanted to ensure that we weren’t just collecting data but actually using it to inform timely program evaluation decisions.
Rebecca Ditwiler: From the curriculum side, Melissa and I have been working closely together on this for a few years. One of the key challenges we identified early on was that while we had done some tagging and curriculum mapping, we didn’t have a centralized way to evaluate whether our curriculum was achieving the intended outcomes.
We lacked visibility into whether we were meeting mapped objectives and how effectively those objectives were being assessed. That made meaningful, higher-level program evaluation very difficult.
Additionally, after a curricular redesign, especially during the post-COVID period, it became essential to assess whether the new curriculum was functioning as intended. But we didn’t yet have the systems in place to bring all of that information together. So we were facing significant work just to get to a point where we could begin evaluating the program effectively.
Enflux: Where did the challenges of having so much data in so many places begin to really impact the program?
Melissa Lazinski: One of the biggest challenges for me was data triangulation. I had student survey data, test scores, and other data points, but no way to view them together. I had to go to multiple people, dig through different data sources, and manually piece everything together.
There was also the issue of timing. Data was collected at different points throughout the year and often reviewed all at once at the end. That made the process more time-consuming, and that’s where the “time” challenge really comes into play. Because of that, I didn’t have access to timely insights or a clear program-level, “thousand-foot view.” Without that perspective, it’s difficult to make informed decisions in higher education program evaluation or develop effective action plans. So much time was spent gathering and organizing data that insight generation and action planning took a backseat.
Rebecca Ditwiler: From the curriculum perspective, the disconnect became even more apparent when our accrediting body updated its standards. Suddenly, we weren’t just evaluating a newly redesigned curriculum, we also had to determine whether we were meeting a new set of standards.
At the time, the system we were using wasn’t very user-friendly. It required significant effort from both staff and faculty to input and access information. It wasn’t intuitive for administrators and added extra burden for faculty. That’s when it became clear that we needed a different approach, one that would allow us to efficiently access the information needed for program evaluation, accreditation, and faculty understanding.
Connecting curriculum mapping, student outcomes, and performance data
Enflux: How does curriculum mapping connect to student outcomes and performance in practice?
Rebecca Ditwiler: This has been one of the biggest benefits for us in using Enflux. One of the most valuable things we now have is a centralized curriculum map that reflects our current curriculum aligned with the new standards we’re expected to meet.
What’s powerful is that it doesn’t just live in one place, it’s connected to other systems. Data flows in from platforms like Canvas LMS and ExamSoft, allowing us to see not only how things are mapped, but how students are actually performing.
This allows us to ask more precise questions:
- Are we assessing at the level our objectives require?
- How are students performing in specific mapped areas?
- Where are the gaps between teaching and assessment?
Instead of manually pulling data, faculty can review insights and focus on interpretation.
Even if something is mapped and assessed, we can now determine whether students are truly mastering that content. For example, we can look at how many students are answering specific items correctly across a cohort, or even drill down to individual performance. Before having a system like this, we were constantly pulling and compiling data manually, which required a significant amount of faculty time. Now, instead of manually pulling data, faculty can review insights and focus on interpretation.
We’re also really looking forward to how this will support our upcoming accreditation visit, since everything we need can be accessed in one place. And beyond curriculum, this also gives us a clearer picture of overall student performance data.
Melissa Lazinski: We have several program-level learning outcomes that are part of our overall evaluation plan, and it’s now so much easier to access and analyze those data points. We can look at performance longitudinally, across cohorts and over time, which gives us a much clearer understanding of trends. It also allows us to quickly identify areas of deficiency. From there, we can develop targeted action plans and then actually measure the impact of those changes afterward. What’s really powerful is that our decision-making is no longer based on intuition or “gut feeling.” Instead of guessing what the problem might be and trying a solution, we can clearly identify the issue first, and then design a more effective response.
I think many of us have experienced situations where there’s a poor outcome, followed by a quick, reactive solution that doesn’t fully address the problem. Often, that happens because the root issue wasn’t clearly understood.
Having this level of precision allows us to make decisions that are not only more informed, but also more efficient.
Enflux: Once curriculum mapping was connected with assessment and student performance data, what changed in how you understood your program’s curriculum and outcomes?
Rebecca Ditwiler: Honestly, we’re still learning; it’s definitely an ongoing process. The biggest shift isn’t just my understanding as the curriculum lead, but how faculty understand the curriculum overall.
Previously, assessment items were often created based on what was taught, without full alignment to objectives or cognitive level. Now, because we track and review this, misalignment is much more visible. For example, a faculty member might notice that students performed poorly on a question, but then realize that the item was written at a much higher cognitive level than how the material was taught. That kind of insight is incredibly valuable. It provides a clear window into what’s actually happening within individual courses and across the curriculum as a whole.
I think the biggest “aha” moment has been this increased visibility, especially in how faculty engage with the data. We’re now able to share insights more effectively, review them collectively, and make data-informed decisions as a faculty group. That shift has been really powerful.
Melissa Lazinski: From a faculty development perspective, this visibility has been key. Many health science educators don’t have formal training in education theory, so concepts like alignment and assessment design can feel abstract or burdensome.
When faculty can see how objectives, assessments, and outcomes align, it lowers the barrier. Instead of asking them to trust the process, we can show them the impact.
That has improved buy-in and strengthened engagement. Faculty are now more involved in interpreting data and contributing to more informed decisions.
How data visibility transforms student advising and mentorship
Enflux: From an advising or mentoring standpoint, has this level of visibility changed how you support students?
Rebecca Ditwiler: One of the biggest benefits has been seeing a complete snapshot of a student’s performance at a single point in time. Previously, understanding a student’s performance required pulling reports or navigating multiple courses. Now, mentors can quickly access a full view across all courses in a semester. This is especially valuable during advising meetings. If a student fails an exam, we’re no longer limited to that one data point, we can see their performance across the entire program. That enables more meaningful conversations, identifying trends, spotting concerns, and discussing proactive support.
It also shifts the dynamic. Students know we understand their performance and are using that insight to support, not just evaluate them. And importantly, this is real-time, not a static report, which significantly improves how we guide students.
Melissa Lazinski: We often assume students understand how they’re performing, but they don’t always see patterns or identify weaknesses. They need help interpreting the data. With the right guidance, Enflux becomes a powerful learning analytics tool, helping students see the bigger picture and focus on targeted intervention strategies instead of guesswork.
From a program perspective, this has also been critical. As chair of the progress committee, I review students each semester who may be struggling. Having a centralized record allows us to see the full picture: past performance, action plans, and trends. Ultimately, this leads to more informed and fair decisions, especially when those decisions impact a student’s future.
Enflux: How has your use of Enflux changed the way you prepare for accreditation or self-study?
Rebecca Ditwiler: We started with an outdated curriculum map, so we’ve done significant work to rebuild it. Our approach is collaborative: the curriculum committee leads, but faculty are actively involved. We tagged syllabi to align with new standards and used Enflux to identify gaps.
While each CAPTE standard was mapped at least once, accreditation requires demonstrating progression, typically two to five objectives per standard. We’re now identifying those progression points and determining how to report on them. Faculty involvement is key, they understand which objectives are tied to accreditation and their role in delivering them. Shared ownership makes the process manageable.
Melissa Lazinski: What’s made a big difference for us is having a structured framework to organize all of this information. Instead of trying to build our own system from scratch, we now have a place to input data in a consistent, organized way. It becomes more of a “fill-in-the-blank” process rather than trying to invent a system while also managing the complexity of accreditation requirements. That structure significantly lowers the barrier for faculty participation. Instead of spending time collecting, organizing, and formatting data, faculty can focus on contributing information and engaging with the outputs. And that’s critical during accreditation. A centralized learning analytics system reduces that burden and helps align faculty more effectively.
The experiences of Melissa Lazinski and Rebecca Ditwiler make one thing clear: effective higher education program evaluation requires more than collecting data; it requires connecting it.
At the center of this transformation is the ability to make data-informed decisions with confidence and efficiency. Learning analytics for higher education, like Enflux, enable programs to integrate siloed data, streamline reporting, and surface the insights that matter most, without adding administrative burden.
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