Like the rest of the world, educational institutions (K-12 and higher ed) are obsessed with data, believing that everything in society can and should be quantified and, therefore, measured. The risk we run is that we will gorge ourselves on the ever-increasing stream of quantifiable information, while becoming anemic in relation to the things that we can’t (yet) measure or are failing to accurately account for. We’re coming to respect the vast power and value of data — but just beginning to grapple with its limits.
As a nation, we talk obsessively about data-driven decision making, and businesses are staking their futures on it. Colleges and universities have been relative latecomers to this revolution, but are now investing millions of dollars in software, data platforms and in institutional research and data analytics units. This is good and needed. We know too often our ways are old, tired, inefficient, and sometimes ineffective. We are searching for innovation, measuring and seeking to assess everything to show our value in a world that values us less and less. At many, if not most institutions, tight budgets mean we need to ration resources fairly and logically. And data is seen as the best tool to help focus limited resources.
We now regularly inundate faculty and departmental chairs with data and what we don’t have we ask them to develop for us. We are, however, starting to use data to make better, more informed decisions and to more efficiently allocate resources. We are behaving more responsibly and transparently. But that is only part of what we need to do to move forward.
Another part of what we need to do is recognize that data is not a silver bullet. In our rush to embrace the new, we risk losing our most valuable asset: our humanity.
What we don’t do well, or at least not well enough, is connect the data to the human-side of actual learning and teaching. We need to recognize that good teaching is as much an art that requires human connection between faculty and students. All the data in the world will not move education forward unless it is paired with superior teaching, qualified teachers, and environment that is conducive to learning.
There are some hopeful signs that we may be beginning to make the connection. Large public universities, such as Arizona State, Georgia State and CUNY’s Lehman College, are leading us in the use of data to track students and identify moments of need and worry in their academic lives (courses, areas of studies, life moments, financial conditions etc). Looking at large data sets and seeing patterns gives us the knowledge to recognize problems that would be invisible close up. This allows us a chance to intervene before a moment of crisis.
For instance, if we look at large streams of data over longer periods of time, we might see that certain courses can become speed bumps for certain students stalling their progress or forcing them out of college altogether. A slight change in pedagogy, teaching methods, or the sequence of when the course is offered to these students, might make the difference in greater success.
Too many, university leaders read about quantifiable successes and focus on repeating or adding to those numbers only through data analysis. They forget that a central reason why Lehman has found some success is because they had a serious hunch (hypothesis) on where there was an issue, used data to pin-point it, dove deeply into it and sat back to see the patterns emerge. In short, they used the tried and true scientific method. But of equal importance, once they saw the issues, in this case courses that had the greatest difficulty for certain students, they went to the faculty and departments who teach these courses and collectively developed a solution that included new ways or modes of teaching (what was for these students exceptionally difficult material). In short, they changed the teaching and that change in teaching made the difference.
The success at Lehman is an example of merging the science and art of teaching. Without the data, the patterns wouldn’t have been visible, there wouldn’t have been the true accuracy to match the struggling students and the courses they struggled with most. Without the data, too many students would have hit particular speed bumps and either begun a downward spiral or simply vanished. Without the faculty, however, and their expertise in content and teaching, the college would not have been able to develop new ways to successfully teach these students.
As the Lehman example reminds us, we ignore teaching and pedagogy at our own peril. Data alone could only identify the problem, faculty were needed to solve it. Teaching matters. Colleges and universities, therefore, need to invest in faculty, as they are on the front lines. They have daily contact with students. We need more faculty and they need resources. Investment in Centers for Teaching and Learning that can train professors and college instructors in new methodologies are also needed. Investments in adequate classroom space, understanding how class size plays a role in student success, and a realization that technology needs to serve instruction all need to be addressed. And we need to continually invest and hire more full-time faculty who will be present beyond the classroom.
It is the marriage of data and human interaction, of the art and science of education, that will allow us to reach more students, to affect greater change and growth and help us to unleash student potential.