Step into a dozen classes on any university campus and you are likely to see practices that cut against everything we know about high-quality teaching and learning: Hour-long lectures with almost no student interaction. Little effort made to expose prior knowledge, draw out misconceptions, or personalize the learning experience. Students sitting in fixed rows with barely a nod at building community. Infrequent, stress-inducing assessments. And minimal attention paid to connecting what happens in the classroom to anything outside it that might matter to the learner.
It’s a broad brush for sure, and there are many talented instructors in our midst adopting evidence-informed practices in their courses. But as a whole, the results we are delivering speak for themselves: Failure rates in excess of 20 or 30 percent in a given class, sometimes even higher. College dropout rates above 30 percent nationally. The current state of affairs is made all the more painful because when it comes to learning, we know what works.
In the face of a national crisis in college-going and degree-attainment, we need to do better, and fast. The time has come for a higher ed moonshot—an urgent shift from the traditional lecture-based model to one that makes evidence-informed teaching the standard for course design and delivery. Part and parcel to this is making data-informed iteration an expectation for continuous improvement.
Transforming institutional practice this deeply will not be easy, but it can be done. Health care systems, for instance, compel alignment to evidence. Failures in a clinical setting are publicly reviewed to seek understanding and intervention to minimize its likelihood in the future. Health care providers must commit to professional development and continuing education to maintain current knowledge. We can do this in our industry just as well.
So what can be done to make the shift to evidence-informed teaching in 10 years instead of 100? Let me offer five solutions.
1. Make DFW rates for every course visible to the university community
We cannot manage what we do not measure. This is not about public shaming. But by shining a light on where we’re falling short, we can encourage faculty to reflect on their current approach, and seek support from colleagues or their centers for teaching and learning to drive improvement.
2. Identify large enrollment courses with high DFW rates, and treat them as urgent priorities
A failure in one course can have a devastating effect on a student’s academic trajectory. We need to act with urgency to eliminate these barriers by working with faculty on course redesign initiatives. At the same time, we need to embrace a spirit of community and shared purpose to align on success metrics and hold one another accountable to confirm with data that what we’ve changed has actually improved outcomes. If the evidence suggests otherwise, then commit to a clear-eyed review of the results and learning from mistakes as a community.
3. Make professional development a central part of the institutional mission
We need to ingrain ongoing discussions and initiatives to improve the quality of instruction into the cultural fabric of departments and institutions as a whole. This includes investing in instructional designers as part of a modern center for teaching and learning, and supporting faculty learning communities to develop and implement evidence-informed course design. Creating the time and space for professional development should, as a starting point, include efforts to establish minimal evidence-based design standards (e.g., active learning, frequent, low stakes assessments) for all courses.
4. Embrace data to create feedback loops that spur tangible improvement
Colleges and universities are huge repositories of data. But only recently have they begun to systematically leverage this data to improve academic advising and increase student success. Are gateway courses adequately preparing students for subsequent classes? Are degree requirements overly complex? Are students withdrawing at an unusually high rate from courses they need? It has never been easier to pinpoint and act on these issues.
We also need to give faculty the tools to gauge student progress early and often. Educational technology offers enormous opportunities to track student progress in real time, especially when we use these tools to create a regular cadence for assessments. The use of frequent diagnostic and formative assessments enable students to receive the feedback they need to course correct before it’s too late. These tools can also identify and help to replicate instructional practices that are making the difference and scale what’s working more quickly across courses.
5. Celebrating the evidence of success
Improving student outcomes takes time, and a healthy dose of humility and endurance to keep pushing forward when our best assumptions don’t go according to plan. We need to celebrate these efforts, not just with awards and recognition, but with practices around promotion, tenure and budget allocation aligned to this priority. But at the core, recognizing transformational course redesign needs to be couched in tangible improvements in student outcomes, reinforcing that we honor what we value.
We know that teaching and learning is deeply context-sensitive. The discipline at the center of a course, the variation in readiness among students, the social environment surrounding a class, and more, conspire to create a gap between learning science and its application. But by embracing best practice, and using data to iterate and improve, we can design courses that promote belonging, that allow students to apply learning, and, above all, cultivate the critical thinking, communication, discipline-specific skills and understanding necessary to fuel their success in higher education and beyond. We can end the tradition of high failure rates in our gateway courses. We can successfully graduate more students. What are we waiting for?
