The Coming of the Learning Engineer: Questions of Faculty Work in the Digital Age
Concurrent Session 1
What does the faculty know about learning? According to reformers, very little. Lessons from the learning sciences have been slow to penetrate teaching. Thus, new initiatives hope to make “learning engineers” central to online course development. Can the idea meet the challenge of maintaining important features of faculty work?
What does the faculty know about cognition and learning? According to recent reform proposals, very little. While the learning sciences are an increasingly well developed field of inquiry its lessons have been slow to penetrate the everyday activities of college and university scholars who teach—and that would be almost all of them. The problem, as presented in a new report (April 2016) from MIT, is particularly acute in online course development. Thus, “transformative improvements” in course design and student performance will depend on what professors make of “the growing body of research that seeks to understand learning at the fundamental scientific level.” Postsecondary education, alas, “does not appear to have an integrated pipeline that promotes transfer of concepts to reality.” For MIT the stakes are high, as is evident in the title of its report: Online Education: A Catalyst for Higher Education Reform.
How can institutions correct for the lag in faculty preparation for online teaching? MIT’s Online Education Policy Initiative recommends the creation of a cadre of postsecondary professionals named “learning engineers.” With other abilities, they will be “familiar with the languages of several fields in the learning sciences in order to communicate with experts and stay up-to-date on current research.”
Interventions in online course design, as the task of “learning engineers,” represents an approach to managing faculty work in the digital age favored in institutional initiatives. One similar to MIT’s was also launched this year at Carnegie Mellon University (CMU). The Simon Initiative (SI), is named for the CMU Nobel Prize economist and computer scientist Herbert Simon, who introduced the idea of the “learning engineer” almost 50 years ago. With CMU’s newly organized Global Learning Council (an international “best practices resource”), the Simon Initiative (www.cmu.edu/simon/) has as its motto: “Harnessing a Learning-Engineering Ecosystem.” It promotes “Technology Enhanced Learning” (TEL) as the product of “A continuous cycle in which learning science informs educational practice and in which data from instrumented educational practice informs learning science leading to better learning outcomes for students.” Learning engineers, as imagined originally and now again at CMU, and as advocated also today by MIT, will guide course design in the direction of a reciprocal instructional ideal.
This presentation is in three parts. It begins with the genealogy of the idea of the “learning engineer.” When Simon introduced it nearly 50 years ago it was to remedy what he saw as a flaw in the academic system. Speaking to a group of university presidents in 1967 he urged them, in pursuing their “central professional task,” to apply resources that could compensate for the pedagogical “amateurism” of the faculty. Simon offered what became a common criticism of professors. Thus, “however impressive in their competences in their disciplines [they] are almost completely untrained in the skills of teaching.” The solution Simon proposed was the installation on campus of “learning engineers” whose chief task would be to guide the faculty toward a scientific and systematic approach to course design and teaching. Simon understood the disruptive potential in his proposal, “I know of no way to introduce professionalism into the learning process on the college campus without disturbing highly venerated practices and strongly held myths.” It was for academic leaders to display the authority necessary to rescue teaching from “entrenched privilege.” They could count on what Simon and his computer science colleagues knew about “learning effectiveness” and could anticipate that in time (Simon guessed at 10 years) the faculty would recognize the suitability of the new format for organizing instructional responsibilities.
Little came of Simon’s proposal at the time but by the beginning of this century CMU had become a leader in an allied approach to reshaping what was expected of the faculty. Its Eberly Center for Teaching Excellence pioneered in representing at its elaborate website and in a book (2010) scientific knowledge of “How Learning Works.” And the (mainly) STEM courses making up CMU’s celebrated Open Learning Initiative (OLI) can be seen as platforms for activities associated with the idea of the “learning engineer” and of the priority to be given to the “production function” and efficiency in online teaching, or the introduction of “productivity-enhancing automation.”
After setting out the background to the “Coming of the Learning Engineer” in our time (or perhaps more precisely the “Return of the Learning Engineer”), in its second part the presentation turns to its meanings for “Faculty Work in the Digital Age.” We can welcome the idea of the “learning engineer” today as a sign of criticism of educational tradition, including the potential for the distribution of instructional roles to reflect digital innovation. That is what prompts computer scientist and university administrator Richard DeMillo, in his recent case for the benefits to higher education of the technological “revolution,” to ask again and again about the fate of the faculty. For example (in Revolution in Higher Education: How a Small Band of Innovators will Make College Accessible and Affordable [MIT Press, 2015]): “In virtually every known category of learning, technology appears to be driving improvements in learning achievement. . . . But, even if technology successfully enhances student achievement, the university workforce is not necessarily designed to accommodate it. Universities are designed so that there are many professors teaching relatively few students . . . . What happens when even better results for even more students can be achieved by hiring fewer professors?”
Proponents of instructional teams with “learning engineers,” including DeMillo (though he doesn’t use the phrase), see them as a way of making the faculty more productive in applications of technology and allowing for the scaling up of online courses. But there are important questions to be asked of the MIT/CMU idea, with what it represents of a change in how we see the online faculty:
1) What are the implications of “unbundling” (as the term is used in the study of higher education administration) the role of the faculty so that in online course design according to the “production function” professors would serve as “content experts” and would presumably—since in the eyes of critics they teach mainly from experienced-based “intuition”--yield authority to experts in the learning sciences?
2) How will course design enabled by “learning engineers,” with its determination to feature efficiency and “scalable processes,” influence perceptions of faculty roles and the recruitment of professors to online teaching?
3) What does a learning sciences-inspired view of online course design and teaching, with new roles for “learning engineers” and the turn toward “big data” for “learning analytics,” mean for postsecondary educational research, particularly in redefining how we understand what we want from the faculty, and what the faculty expects of itself in the assessment of student performance and the strengthening of online teaching?
Together the questions suggest what the idea of the “learning engineer” and proposals for the reconfiguration of online course design can mean for traditions of faculty work. In its third part the presentation will identify a different path for strengthening faculty recognition of the uses of the learning sciences. It features models of individual professional development built primarily on instructional autonomy and represented in recent books (similar to How Learning Works but unattached to ambitious national and international reform initiatives) like Michelle Miller’s Minds Online: Teaching Effectively with Technology (Harvard University Press, 2014) and James Lang’s Small Teaching: Everyday Lessons from the Science of Learning (Jossey-Bass, 2016). Such work, to the degree that in its collegial tone it can influence the faculty via reading and/or in professional development programs, represents a direct line from theory to practice. Note: A brief annotated guide to these and similar resources will be distributed at the session.
Following the presentation participants will be invited to address any or all of the three “Questions of Faculty Work in the Digital Age” in the context of proposals for the coming (or return) of the “learning engineer.” And participants will be encouraged to comment on the relative merits of institutional initiatives (like those now at MIT and Carnegie Mellon) and individually oriented ones represented in prospects for bringing theory into practice via a faculty oriented book-based discourse on the uses of the learning sciences.