Learning Engineering: New Profession or Transformational Process?
In other words, learning engineering gives us a process for connecting science, solutions, and scale in the service of better learning.
Learning engineering gives us a process for connecting science, solutions, and scale in the service of better learning.
Grush: How have instructional designers reacted to the potential of learning engineering in their professional space?
Wagner: I remember reading Audrey Watters's blog on the topic of The History of the Future of the Learning Engineer, reflecting on MIT's announcement that a whole new category of professional called a "learning engineer" would be taking on roles that sounded suspiciously like instructional design jobs. At the time, she snarkily noted that IDs might not mind having an Ivy League job title elevated from "designer" to "engineer".
IDs haven't really seen learning engineering emerge as the direct competition that was originally feared. These days, they are busy taking care of their stakeholders' instructional, learning, and experience requirements. Instructional designers don't have the luxury of doing much iteration or experimentation in their instructional designs. Learning scientists have a different orientation to their work.
There is a school of thought among some learning scientists suggesting that learning engineering is the practical extension of learning sciences in action. These learning scientists do research, data analysis, and classroom experimentation. They build tools to test assertions. They iterate and formatively evaluate and revise. When they finish their experiment they publish their results.
Meanwhile, IDs continue to support faculty and programs. Instructional designers know they need to do more with data-enabled design in their work. They know they need to up-level analysis skills as an important addition to the ID skillset. Remember, traditionally IDs developed design expertise while working with subject matter experts. But we now have access to ample information and data about our learners from the platforms they use.
Instructional designers know they need to do more with data-enabled design in their work… We now have access to ample information and data about our learners from the platforms they use.
Even so, learning engineering is not necessarily the next generation of instructional design. It is more learning sciences-oriented than that. Thinking of learning engineering as the applied extension of the learning sciences is a tough case to make, ontologically. The learning sciences and engineering appear ontologically independent from one another, which means that combining them, or imagining that one is an extension of the other, is not tenable.
Learning science in practice as learning engineering looks more like a quasi-experiment — not an effort to prototype a promising product or experience, much less a fully scaled solution!
Learning scientists collect data from iterative human design efforts, but may not go on to the next stage of development after the experiment is concluded. Designers and engineers are at different points in the overall learning engineering value chain, with both inclined to focus on developing the next phase of their respective parts of the work.
Grush: How else have researchers in the learning sciences contributed to learning engineering?
Wagner: Learning science researchers are creating what they call learning engineering. It's just that their vision doesn't deal much with either the design or engineering parts of this value proposition.
But who can blame them? They are encouraged by agencies including the Institute of Education Sciences and the NSF, and foundations like Schmidt Futures and others to believe that their version of learning engineering is going to drive the future of U.S. education. They may be surprised to learn that new discoveries are relatively less useful in the design and engineering phases of development, where it is more reliable to use established science in real-life designs and in real-life learning settings.