To Ephiphany--and Beyond!

Productivity has been in the news a lot over the past few months. Economists, politicians, and pundits all cite productivity as the leading factor contributing to the jobless economic recovery.

Read beyond the headlines and technology emerges as the official explanation for the recent productivity gains in the American economy. Admittedly, many of us are working longer and assuming additional responsibilities for no increment in pay. But our extra efforts notwithstanding, Federal Reserve Chairman Alan Greenspan and other sage observers tell us that the current productivity gains reflect, in part, returns for the corporate investment in information technology over the past two decades.

In this political season it is probably best to let politicians argue over the numbers and nuances of recession and recovery. Then again, I always thought that Ronald Reagan, an economics major at Eureka College (Class of ’32), had it right: a recession is when your neighbor loses his or her job, while a depression is when you lose yours.

However you feel about the current economy, economists have a fixed and firm definition for productivity. My daughter’s econ text offers this definition: “the amount of product produced by each unit of capital or labor.” Technology, we know, contributes to productivity because it enables us to produce more or better products or services at a constant or reduced cost, i.e., with fewer “units of capital or labor.”

Interestingly, it took a long time for Greenspan and company to find evidence of the technology bang for all the corporate bucks spent on IT over the past two decades. For example, consider the billions that corporations spent on desktop computers, software, and training during the first 10-12 years of the current IT revolution, from the IBM PC to the beginnings of the Web (1982-1994). The year 1994 is important because that’s when corporate spending on information technology finally surpassed corporate expenditures on manufacturing technology. Yet it took more than a decade, well into the late 1990s, before Greenspan and other economists could proclaim a real return on investment (ROI) for the corporate spending on IT. Of course, economists have a fixed and firm definition for productivity.

Which leads us to the meaning of productivity in education. I suspect that most of us in academe struggle to define productivity for our sector of the economy. We generally prefer not to view our work in terms of inputs, outputs, or products. Ours is a true profession, a calling if you will. We may “produce” knowledge, scholarship, and instruction, but we don’t manufacture these “products” and typically resent any effort to categorize our work in this manner.

In economic terms we know how to improve the instructional dimensions of “academic productivity.” For example, we could contain salaries, transfer more of the teaching load to assistant professors or part-time faculty, or increase class size. By definition, any of these strategies would make academe “more productive” because we are changing (reducing) the ratio of inputs (capital and labor) to outputs (number of students taught).

Of course, these simple strategies fail to address complex quality issues or key outcome measures, such as student engagement and learning.

Enter technology. Like others, I know, really know—in my head and heart—that technology makes me more productive. When I gave up my typewriter for a personal computer more than two decades ago, the technology provided a competitive advantage: I could write (and rewrite) papers and proposals, create graphics, develop and update project budgets, and prepare conference materials better and faster than without the computer, and better and faster than my peers who did not use a computer.

And technology as an instructional resource? Here’s where things get messy. Yes, technology—from film and television to online content and interactive simulations—can aid and enhance instruction and learning. But we do not have a clear definition for instructional productivity or precise methods to measure student learning and outcomes. At the classroom, program, and institutional level, we do not have firm definitions and consistent measures to assess what we do with IT resources or the impact of institutional IT investments and deployment efforts.

The absence of consistent metrics and definitive research—comparable to the data used by economists to measure productivity or pharmaceutical companies to document the benefit of new medicines—means that we occupy an ambiguous gray zone. We are left, knowlingly or not, citing former Supreme Court Justice Potter Stewart’s 1964 opinion on pornography; he couldn’t define it, but he knew it when he saw it.

So while we many not be able to define academic productivity, we know it when we see it, or more precisely, when we experience it. In other words, we have evidence by epiphany.

Unfortunately, evidence by (individual or institutional) epiphany fails to provide the much-needed data and documentation required to respond to questions about the impact and benefits of technology in instruction and institutional operations. We need more than a voice vote of the faculty senate to confirm that IT makes a difference.

For me, the conceptual map charting the impact of IT on instruction and curriculum was published more than a decade ago. Writing in Change magazine (Jan./Feb. 1991), and summarizing five years of research on IT and the curriculum for the National Center to Improve Postsecondary Teaching and Learning at the University of Michigan, Robert Kozma and Jerome Johnston were ahead of the curve (and the Web!) in their discussion of key IT issues affecting the curriculum and the continuing IT challenges affecting faculty, academic programs, and institutions. Their 1991 article, “The Technological Revolution Comes to the Classroom” also calls for “systematic assessment” focused on what, in 2004, continues to be the need for evidence about “which innovations make a difference in teaching and learning” and the “need to understand the connection between educational computing, learning, and teaching.”

Data from the 2003 Campus Computing Survey reveal that only a third (33 percent) of U.S. colleges and universities have campus initiatives to “assess the impact of IT on instructional services and academic programs.” Consequently, it is not surprising that we continue to rely on individual or institutional epiphany for evidence about the impact and benefits of information technology on teaching, instruction, student learning, and outcomes.

Chairman Greenspan’s statements linking corporate investment in IT with productivity are important for us in education. His statements confirm that infrastructure fosters innovation and that infrastructure enhancement requires sustained investment. It also means that we need consistent data and continuing assessment efforts. Finally, given the short half-life of IT hardware and software, Greenspan’s pronouncements about technology and productivity suggest that IT is really an operating cost, rather than a capital cost.

The current financial challenges affecting American higher education have led some college presidents to talk about “doing more with less, and doing it better.” In contrast, the quest for evidence about IT beyond epiphany means that we must, simply, do more assessment, do it better, and begin doing it now.

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