“How to bring the benefits of personalized instruction to all students, at scale in many different subjects and on a continuous basis” was a hot topic when I joined the community of teaching scholars about thirty years ago. Personal computers and the emerging internet were opening exciting new possibilities. The future seemed limitless, but the difficulty and cost of software development soon raised formidable barriers. As with all significant innovations, there were many barriers to adoption. Many successes over the years had demonstrated the goal’s feasibility and importance, but the holy grail of application at-scale across subject areas remained beyond our reach.
Now I believe that AI-based learning platforms bring affordable individualized learning within reach. While I will continue writing on predictive economics as in my two recent blogs, I also am launching a new series on the use of AI in college teaching and learning. GrayDI’s new Course Companion offering provides an example of what’s possible. My goal in these blogs is to describe my own and others’ current insights about the impending changes.
Today I’ll share some vintage ideas from Chapter 5, “Technology’s Misunderstood Potential,” of my Honoring the Trust (Anker Publishing, 2003), and also “Leveraged Learning,” an earlier unpublished paper with Sally Vaughn Massy, Today’s blog paraphrases the earlier ones. My occasional “present-day” comments are set off in square brackets ‘[ ]’. The ideas demonstrate that today’s innovations are part of a long historical trend.
Technological Change as Seen in 2003
“Information technology will change everything, and that worries me because ‘everything’ covers a lot.’” This statement by Cornell senior vice president Fred Rogers to the 1998 Forum for the Future of Higher Education sums up both the excitement and angst generated by the information revolution in universities. Historian Tom Hughes [and later, Clay Christensen] speak of how “disruptive technologies” upset the established order of things. The disruptive effects have been compounded In academe by misunderstandings about the goals of technological innovation.
In 1998, technology was beginning to transform “the business of the university’s business”—how teachers teach and students learn. Using technology with a maximum degree of effectiveness represents a core educational competency. My purpose in 2003 was to explore technology’s impact on education and explain why its potential was (already) widely misunderstood. But first, the chapter described what happened in certain non-educational industries when their underlying technologies were upended.
“History reveals technology as value-laden and human shaped,” wrote Hughes in the introduction to his paper, “Through a Glass Darkly: the Future of Technology-Enabled Education.” That’s why “technological change is difficult to fathom and anticipate as political and social history.” Individuals may choose whether to adopt or ignore a given innovation. For example, they may judge that it will not succeed, or that its cost outweighs its benefits. Even if they do go forward, they may or may not implement effectively. Early missteps can delay the diffusion of an innovation, but they are unlikely to block it forever.
Early applications of a new technology may underwhelm. The first railroad in the United States operated between Schenectady and Albany in 1836, a distance of only 13 miles, using the revolutionary DeWitt-Clinton engine. But that revolutionary engine pulled old-technology stagecoaches with wheels modified to run on tracks—as odd a picture as some of today’s efforts to use technology in education may look to future generations.
Innovation relaxes constraints that impede progress. For example, professors might like to reach more students but their lectures are constrained by room size or the on-campus student population. Hi-definition, closed-circuit television [the “next big thing” in the mid-to-late 20th century] relieved these problems, but rigid formats and the loss of student interaction imposed their own limits. There is a powerful lesson here: innovation relieves some constraints but others almost surely will arise. Eventually, these, too will be overcome.
How the electric motor “flattened the factory” illustrates the successive elimination of constraints.
The factory of the mid-nineteenth century was a multistoried affair, expensive to build and inefficient in organizational structure and materials handling. Economies of scale in energy dictated a single prime mover—a steam engine which, given the technology of the time, had to be linked to most machines by vertical rather than horizontal driveshafts. The first electric motors simply replaced central steam engines, leaving the driveshafts and multiple stories in place. Later technology allowed the motors to be put at individual workplaces regardless of location. The inefficiencies of the multistory mill could at last be eliminated.
A similar narrative applies to computers. In the beginning, economies of scale dictated a single mainframe to which people brought their work for batch processing. Technological advances enabled remote input-output systems and then mainframe timesharing. Further advances led to minicomputers and eventually to personal computers and laptops. However, real distributed processing didn’t happen until local area networks (LANs) provided ubiquitous connectivity. Distributed computational power confers huge advantages, just as when electric motors were distributed to workplaces in factories. The full potential of these advantages has yet to be realized [in 2003]. Major paradigm changes take time, and the Internet came of age only in the mid 1990s. It took decades to flatten the factory.
The creation, storage, retrieval, and transmission of information are the core technologies of colleges and universities. Thus it is no surprise that the information revolution is transforming higher education. Other industries changed fundamentally when their core technologies were upended. Now it is higher education’s turn. We don’t know where the changes will lead or how long they will take, but we must incorporate them in our planning.
Leveraged Learning
Shared interest in technology’s promise for education brought thirty thought leaders from academia, business, policy, and philanthropy together at Stanford university in 1995 to participate in the Forum for the Future of Higher Education’s Technology and Restructuring Roundtable (which I chaired). Our theme was whether information technology could “significantly improve education quality and productivity.” Our report, “Leveraged Learning,” answered that question in the affirmative.
The concepts of asynchronous learning and course objects were essential for identifying leveraged learning opportunities. Asynchronous learning frees students and faculty from the need to convene at the same time and place as in classroom-based synchronous learning. Course objects facilitate the actual asynchronization of learning.
Course objects:
- Encapsulate knowledge in software by storing information in the form of text, formulas, pictures, data, etc.
- Provide access methods to help students process information it effectively.
- Generate events that stimulate student engagement and evaluate learning progress or lack thereof.
Notice that the software does more than simply make information accessible, as in libraries. It engages the student in active learning, allows repetitive trials, and evaluates student mastery. It leverages student and faculty time, and lets them participate in the learning process asynchronously. [These principles were being actively considered, and implemented to the extent possible with extant technology, thirty years ago.]
Seven sources of learning leverage were identified. Technology will:
- Promote active learning that fully engages students in their education rather than passive receivers of ‘canned wisdom’ from lectures.
- Mass customize instruction: tailor learning to an individual’s preferred pace, learning style, and prior knowledge.
- Surmount long-standing barriers in the transmission of codified knowledge: provide on-demand access to facts and theories, and repeated practice in the development of cognitive skills.
- Promote cooperative learning: educational management software will facilitate group problem-solving without regard to time, place, or the need for faculty interlocutors.
- Break down academe’s historically rigid structures: for example ,by linking materials and activities among courses.
- Free students from the confines of their campus: they will take courses remotely and their research will transcend barriers across the Internet.
- Shift the faculty’s prime role from “sage on the stage” to “well-informed tutor”: that is, from converying facts and theory to helping students interpret what they’re learning and demonstrating how to approach challenges in their disciplines.
These benefits are as relevant today [2026] as they were in 1995.
Notice that all seven benefits aim to improve the quality of student learning outcomes. Some also offer possibilities for cost savings, but others may increase cost. However, affordable learning improvement for all students was, and should continue to be, the faculty’s primary motivator for technologically-leveraged learning innovation. Would-be innovators should remember this objective and repeat it often to all who will listen. I’ll elaborate on it, and on the technology applications themselves, in subsequent blogs.
