Solving the NGLC Puzzle (Part 2 of 2)

Author: Stephen R. Acker, Research Director
Ohio’s Scaffold to the Stars

In yesterday’s post, we began to explore some strategies for solving the NGLC puzzle. NGLC tasked its grant recipients with a difficult, multi-part challenge:  (1) Innovate (2) at scale (3) within an organizational setting that (4) generates confirmatory evidence in (5) a short period of time. NGLC provides substantial and flexible resources to try and meet this challenge. Accordingly, we’re using Ohio’s Scaffold to the Stars, our NGLC open educational resources (OER) project, to consider strategies for solving this puzzle. To recap the project, Ohio’s Scaffold to the Stars assembled modular OER content, selected by faculty/librarian teams and housed in a database at OhioLINK, a library consortium that serves the state of Ohio, to serve a sequence of math and applied statics courses.

Yesterday we considered the first three parts of the NGLC challenge: we begin today with the fourth.

(4) that generates confirmatory evidence: We are infatuated by “big data,” but need to mature our relationship with big data before accepting its guidance in driving innovation. We can be seduced into aggregating our data across different instructors, institutions, and stages of innovation for the sole purpose of increasing the statistical power of our analyses. The closest parallel that comes to mind is treating the European Union as a single entity that holds the cultures, economies and histories of its 27 member countries as “in common.”

Lesson Learned: Look for commonalities in the learning environments you study, but be respectful of the differences as well. Conclusions drawn from really big data can be extraordinarily powerful when statistical controls can parse enormous universal populations into large and uniform sub-populations. However, if the size of the learning outcomes data set is established by putting together small numbers of students taught by different instructors, in different disciplines, and different institutions, the data are as likely to wash-out meaningful relationships as to support causation.

(5) in a short period of time: The value of learning innovations emerges over multiple generations of actors. Teachers may do well in their inaugural effort, but they improve the second and third time they teach a course or embrace a new pedagogy. Students develop learning strategies over time, and their outcomes improve with experience. The most concrete example of this phenomenon was shared in a focus group with students after their first trial with digital resources—several complained about difficulty finding material by scanning through screen after screen of material. As unlikely as it seems, they had not found the interface’s search function. For this novice population, the discoverability in digital texts was actually a liability.

Lesson Learned: Introducing an innovation is a bit like starting a diet—one should celebrate the initiation of a good practice but not expect dramatic results until somewhere down the line. Since learning is an interactive experience, we should not expect improved outcomes until the learning innovation and those who encounter the innovative learning environment have both matured. In my personal experience, even promising innovations won’t stick until their third introduction.

Summary strategy for solving the NGLC puzzle: Here again is the NGLC puzzle:  (1) Innovate (2) at scale (3) within an organizational setting that (4) generates confirmatory evidence in (5) a short period of time.

Posts in the NGLC blog series present sound advice to follow to solve this puzzle. However, taken independently each strategy tangles with the same formidable hitch: a single threat to innovation can derail the most brilliant strategy, killing the adoption and diffusion of the most promising innovation. Successful innovation must confront all threats simultaneously, and must recognize the differences between innovations championed by individuals and those adopted by organizations. The Next Generation Learning Challenge puzzle offers a useful structure through which to introduce, promote and protect innovation.

Concluding aphorisms (please contribute):

Minds vibrate in different time signatures. You need syncopation within the bar to establish the project rhythm.

Think of innovation as a living thing, both fragile and resilient, needing resource to thrive, and guidance to grow.

Innovation is a noun (structure) with the energy of a verb (agency).

Maintain optimism; successful innovations don’t blossom until the third iteration of offering.

Students, faculty, institutions, collaborators shouldn’t be penalized for taking risks.

Crisis precipitates opportunity- your innovation lives at this precipice as a solution to an existing, not future, problem.

Progress with the energy of youth; pause at the feet of experience.

All hands on deck—buy-in is needed from all levels in an organization for innovation to become institutional practice.

Above all, earn trust.


Cornner, H. (1994). The man who tasted shapes illustration credit: “Table for One.”

Cytowic, R. (2003). The man who tasted shapes. Cambridge, MA: MIT Press.

Stephen R. Acker is emeritus professor, The Ohio State University, where he served as founding director of Technology Enhanced Learning and Research. He has served the last five years as Research Director, The Ohio Digital Bookshelf Project, jointly sponsored by OhioLINK and The Ohio Board of Regents. As of July 1st, he can be reached at or in Breckenridge, Colorado.

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