Taking the Lead: Why Instructional Designers Should Be at the Forefront of Learning in the Age of AI
Education is at a critical juncture and needs to draw leaders from a broader pool, including instructional designers
Imagine a village stone cutter in early Dark Ages Europe. His whole life has been spent toiling laboriously on building cisterns, small huts and fortifications. And then, one day, he encounters a traveling merchant, a recent visitor to Rome and Constantinople, who regales the stone cutter with descriptions of a wondrous new structure called a “cathedral.”
The stone cutter’s mind reels with images of ribbed vaults, flying buttresses, and soaring archways — an architectural marvel of marble and stained glass creating a communal, awe-inspiring experience. A spiritual citadel open to all, regardless of rank or status, where one can look up into the spacious, broad ceiling and contemplate divine grandeur.
The stone cutter rushes to meet the village priest at the doorway to a simple wooden church to share what he has heard. The old priest listens (or pretends to listen) indulgently. And then, when the stone cutter has finished, the priest smiles and says, “Well, that’s all very interesting. But what is really needed is a better set of stone steps for the rectory.”
The stone cutter, disheartened by the lack of interest from the priest, returns to the drudgery of his everyday work, carving limestone while dreaming of cathedrals.
The world of a medieval stone cutter and a modern instructional designer (ID) may seem separated by a great distance, but I wager any ID who upon hearing the story I just shared would experience an uneasy sense of déjà vu. Take away the outward details, and the ID would recognize many elements of the situation: the days spent in projects that fail to realize the full potential of their craft, the painful awareness that greater things can be built, but are unlikely to occur due to a poverty of imagination and lack of vision among those empowered to make decisions.
Finally, there is the issue of resources. No stone cutter could ever hope to undertake a large-scale enterprise without a multitude of skilled collaborators and abundant materials. Similarly, instructional designers are often departments of one, working in scarcity environments, with limited ability to acquire resources for ambitious projects and — just as importantly — lacking the authority or political capital needed to launch significant initiatives. For these reasons, instructional design has long been a profession caught in an uncomfortable stasis, unable to grow, evolve and achieve its full potential.
That is until generative AI appeared on the scene. While the discourse around AI in education has been almost entirely about its impact on teaching and assessment, there has been a dearth of critical analysis regarding AI’s potential for impacting instructional design.
This is not surprising considering the short shrift higher education has traditionally given to instructional design. Instructional designers began arriving in college and universities en masse in the late 1990s and early 2000s to help build courses for the online learning programs which had just begun to proliferate. Like 19th century immigrant laborers brought into the United States to build the railroads, IDs were valued in higher ed for the fruits of their labor, but otherwise regarded as a foreign element. They were newcomers to the traditional academy, welcomed as long as they understand that their place is at the periphery and not the center.
During the COVID period, there was brief hope among IDs that the emergency situation, which necessitated an abrupt shift to 100% online learning, might lead to greater recognition of the contributions of instructional designers. The expertise of IDs in rapidly developing quality online courses was crucial in preventing a complete catastrophe for colleges. However, once the pandemic abated, the old status quo quickly returned. Faculty received plaudits and praise for their resilience during the crisis, while the essential contributions of instructional designers and educational technologists went largely unrecognized. Higher education’s “officer class” received the glory, while instructional designers were sent back to the barracks.
The desire among instructional designers to escape this power imbalance is evident in the increased embrace of the term learning designers instead of instructional designers. This language shift reflects their ambition to break free from the traditional role that subordinates them to college instructors and other subject-matter experts, instead recognizing them as independent professionals with genuine agency. The advent of AI provides a unique opportunity for instructional designers to alter this power imbalance.
Aligning instructional design with AI is more than a partnership of convenience. The connection between instructional design and artificial intelligence is older and deeper than most people realize. The two fields have a shared lineage in the transdisciplinary domain of cybernetics, which was defined in 1948 as “control and communication in the animal and the machine” by computer scientist Norbert Wiener. Both instructional design and AI are systems which, at their core, are concerned with feedback loops which enable people and machines to achieve their goals. It is not a coincidence that Nobel-Prize winner Herb Simon, whose ground-breaking work on cognition and decision-making, was a major influence on the development of both artificial intelligence and the psychology of how people learn.
We can use Instructional Design to Build Informal Learning Libraries.
An alliance between AI and instructional designers portends something more than a fortunate career development for IDs. It signifies the next step in the evolution of knowledge transfer.
In the 1990s, the World Wide Web undermined the virtual monopoly on wide-scale information sharing held by mass media, government, and the educational establishment. Inevitably, this sea change generated anxiety in information institutions about the possibilities of networked communication. Anyone working in education during the early 2000s can recall the consternation triggered by the arrival of Wikipedia (2001). Underneath genuine concern about false information that might be disseminated through a wiki platform, there was an uneasy awareness that a significant knowledge domain— the reference book industry — had been disrupted. What had occurred to one information monopoly could happen to another.
There were those who welcomed this development. Author and noted learning professional Jay Cross drew attention to this issue in his book Informal Learning (2006). Cross pointed out that a vast amount of the knowledge that people possess is actually accumulated outside of classrooms and training sessions, through conversations, experiential learning, self-study and peer-to-peer mentoring. Since informal learning is almost impossible to track, we often incorrectly credit formal learning environments for knowledge and skills acquired through informal learning networks.
Informal learning also harnesses the tremendous power inherent in self-directed learning, which allows the learner far greater agency than formal learning. In Cross’s view,
“Formal learning is like riding a bus: the driver decides where the bus is going; the passengers are along for the ride. Informal learning is like riding a bike: the rider chooses the destination, the speed, and the route.”
The rider chooses the destination. The implications of this statement are staggering when one considers it in light of what AI now allows learners to accomplish on their own. For the first time in history, serious learning no longer depends on the presence of an authority figure (teacher) to direct the learning activity. Only the invention of the printed book can rival AI in its liberatory impact on self-directed education.
In an earlier article, I addressed the need for teachers to re-evaluate their role in light of the changes that AI will bring to any learning enterprise. While there are some reassuring developments involving educators engaging with AI in a positive manner, it remains to be seen whether the majority of teachers will follow anytime soon. The educational establishment is not famous for embracing change. (Consider the number of faculty who had no experience teaching online when COVID hit, despite the fact that online learning had been a major component of higher education for more than a decade.) If a majority of faculty members fail to engage with AI, they will be ceding an important space, leaving it for instructional designers to occupy.
AI harnessed to evidence-based learning provided by instructional designers can accelerate the pace of the informal learning revolution. Using AI, instructional designers can begin to create libraries of interactive learning content (such as simulations, chatbot tutors, and tools for retrieval practice) which can be used either in formal classroom instruction or by independent learners working without the assistance of teachers. Here is one example, a growing repository of short sims (a form of interactive learning pioneered by Clark Aldrich).
The phrase “platform agnostic” is typically used to describe software that can run on a variety of computing platforms. I propose that instructional designers think of themselves as pedagogical agnostics, equally at home either partnering with subject-matter experts for formalized learning experiences or by creating artifacts for learners to use on their own. High quality informational videos on YouTube are an excellent example of content used effectively in both situations.
Indeed, YouTube is a perfect example of the power of an informal learning network. Although much of its content is marketing and entertainment, a significant portion is devoted to informational/instructional videos. As of July 2024, YouTube has 2.70 billion monthly active users, making it the single most powerful learning platform in history.
Wikipedia and YouTube are digital spaces where instructional designers have practiced their craft without relying on permission from the educational establishment. These spaces provide a foreshadowing of a vibrant learning ecosystem that can be built and exist outside of formalized learning environments (but which can still be used in classroom learning if needed). Using AI, instructional designers can take this ecosystem to its next level — by creating dynamic resources that benefit learners pursuing either informal or formal learning experiences.
To illustrate this point, let me conclude with two promising areas of development that are rich with potential for AI-augmented instructional design, both of which meet the “pedagogical agnostic” principle.
First, Re-invent Open Educational Resources
For decades, open educational resources (OER) have been one of the most vibrant and celebrated movements in higher education. By offering educational resources for free, it has reduced the cost barrier, which is one of the most pressing challenges for many students of limited financial means.
But while this movement has made use of the World Wide Web as its vital delivery system, much of the content it provides remains firmly entrenched in the pre-internet world. OER repositories are filled with textbooks, static images, assignment handouts, and slidedeck presentations (which, in both form and content, are little different from the projected transparencies educators used extensively in the second half of the 20th century).
Standard OER collections rarely leverage the unique affordances of the digital environment, making these content libraries unappealing to many users. Additionally, these collections primarily focus on content for formal classroom learning, offering little material for independent learners.
A new type of OER repository is needed, one where all materials use the capabilities of a digital environment to provide rapid, high-quality feedback to learners. The content should be fully interactive, developed based on evidence-based learning science principles, and inclusive of both formal and informal learners. Instructional designers are ideally suited for the task of building such a resource.
Consider e-textbooks linked with simulations that allow the learner to practice key competencies related to core learning outcomes. For example, an e-textbook on IT networking could have a link to a simulation that allows the learner the opportunity to practice providing IT support.
Second, Transform Career/Workforce Education
Career-integrated learning is another subject whose enormous potential has been left largely underdeveloped in higher education, in part because many college instructors are wary of higher education diverging too far from academic learning, preferring to reserve professional education for graduate programs. And yet, it cannot be denied that the desire to be better prepared for a competitive job market is what encourages many undergraduates to pursue post-secondary education. They cannot afford to wade through four years of college (and its attendant debt) before committing to career preparation.
The pressing need to provide post-secondary students with a greater variety of career-integrated learning opportunities represents an enormous opportunity for colleges to build much needed new programs outside of traditional academic divisions. Herb Simon, who had decades of experience promoting innovation at Carnegie Mellon University, once observed that it is easier to fill a vacuum than to fight against entrenched ideas.
Building a career-integrated learning division separate from the traditional academic divisions meets such an unsatisfied demand and — crucially —represents an area where there are neither entrenched ideas nor factions prepared to resist experimentation and innovation. This, in turn, makes career-integrated learning a fertile ground for instructional designers to build a range of new learning artifacts, such as simulations for workplace competencies.
Such a program could begin to expand beyond the operational constraints of typical college programs by offering to graduates, for a reasonable fee, ongoing access to professional educational resources, such as learning simulations on new topics, career-specific AI tutoring, and automated email quizzes to promote retrieval practice (protection against the forgetting curve, a significant problem for which higher education has never devised a solution).
Equally important in this new paradigm is the embrace of workflow learning, a concept that has gained traction in the Learning and Development (L&D) field. This approach views learning as a continuous, contextual process integrated into daily work, rather than an isolated activity like traditional training sessions or standalone courses. As a result, workflow learning aligns well with a post-secondary education model that blends academic and practical training.
We are at a critical juncture for AI-augmented learning. We can either stagnate, missing opportunities to support learners while educators continue to debate whether the use of generative AI tools is a good thing, or we can move forward, building a transformative model for learning akin to the industrial revolution’s impact.
Too many professional educators remain bound by traditional methods. The past two years suggest that leaders of this new learning paradigm will not emerge from conventional educational circles. This vacuum of leadership can be filled, in part, by instructional designers, who are prepared by training and experience to begin building in this new learning space.
Literature provides an instructive model. In the classic American novel, Huckleberry Finn, the title character is a feisty youth, filled with scrappy energy and considerable ingenuity, who is held back due to his lowly class status in a rigid, tradition-bound society resistant to change, blinded by pride to its own decline.
Rather than submit to the norms of the old order, Huck Finn determines to set forth into unsettled regions where he can be free and true to himself. As Finn says in the final sentences of the novel,
“I reckon I got to light out for the Territory ahead of the rest, because Aunt Sally she’s going to adopt me and sivilize me, and I can’t stand it. I been there before.”
It’s time for instructional designers — and other educators yearning for change — to follow Huck Finn’s example and venture out beyond established frontiers, where they can build a brave new world for learners.
Who is with me?
