By Vjekoslav Hlede, PhD
This column aims to highlight the rapid changes occurring in E-learning methods, approaches and challenges, as well as its supportive technology, and how these will impact medical education.
Book review: Justin Reich, Failure to Disrupt: Why Technology Alone Can’t Transform Education
We have all heard those big promises about technology that will improve education and CME/CPD for good. Most of us were thinking, “Hmm, that will be an excellent addition to our CME/CPD services.” And we waited. And we waited patiently. And we sometimes asked ourselves why many of those big believable promises did not happen. This book provides a convincing explanation of why they did not happen and what we can do better.
Justin Reich is a professor at MIT and Director of the MIT Teaching Systems Lab. In his latest book, Failure to Disrupt: Why Technology Alone Can’t Transform Education, (Reich, 2020), Justin delivers healthy skepticism about learning technology. This skepticism will curb our attempts to romantically dream big and hope that technology alone will address many of our complex problems. Simultaneously, the book’s insight will empower us to find areas where we can make noticeable improvements. It helps us avoid errors we made in the past and better plan CPD in our increasingly digital future.
The book provides an easy-to-understand, high-level overview of the biggest challenges affecting online education. Jal Mehta, Professor of Education, Harvard Graduate School of Education, explains: “If you had to pick one book to learn about all things online learning, this would be the one.” Since all the issues discussed in the book affect online CME/CPD learning delivery, this recommendation is especially valid in the context of CME/CPD.
Technology-enhanced CPD is an immensely multifaceted endeavor. The learning/educational technology industry, learning theorists, accreditors, licensing organizations, evolving medical, academic, and digital cultures, and above all, the massive transformation of the healthcare system create a cacophony of often conflicting needs and directions. The high-level “bird's-eye" overview Reich provides helps us map how technology interacts in this complex socio-technical system.
A map of the system is the key. Many unkept promises, false starts, and unfinished edu-tech projects are caused by a lack of understanding of the socio-technical system. Reich helps us map the system, better navigate through challenges, and make sustainable improvements.
I found interesting and often actionable insights on each page. Therefore, I recommend reading the whole book. However, busy professionals may decide to read just the introduction and conclusion. And they will not be sorry. In 16 pages, Reich presents the history and present of the three primary modalities for online learning at scale: (1) instructor-guided, (2) adaptive, algorithm-guided, and (3) peer-guided networked learning. He explains why innovations, massive hype, and huge investments are not delivering on their big promises. Instead of significant transformative changes, we see only small, incremental improvements.
Technology has failed to disrupt. And that is where the opportunity lays, Reich explains. There is no good reason to believe the situation will change. Technology alone cannot disrupt. Be skeptical of charismatic technologists who predict sweeping changes, Reich warns. Tinkering is the way to go. Tinkerers understand that education is a highly complex system. We have a tremendous opportunity to improve it. However, the improvement comes as a result of repeated incremental changes in the socio-technical system, rather than the simple sweeping implementation of new technology. Tinkerers are optimists, but they use critical thinking and research to find what is possible and how to achieve it.
Reich (semi-jokingly) proposed the Reich Law: People who do stuff do more stuff, and people who do stuff do better than people who don't do stuff" (Reich, 2020, p. 24).
That is the magic sauce. Instead of looking for the silver-bullet technology that may (in the indefinite future) address all our needs, we should tinker with the available technologies—to improve our performance. And do it again, and do it better and better.
Reich provides multiple tools that can help us while we are tinkering with how to do it better. The book is the most important tool in the toolbox. Other tools are (1) the website, which includes a discussion board where you can chat with other readers and the author, (2) a series of (recorded) webinars that are available to registered users, and (3) a YouTube video presenting the highlights from the book.
What are the key messages?
There are three types of established technology-enhanced learning (TEL) formats that support learning at scale. The learning formats and associated technology stacks are built around the question: "Who defines the learning process for learners?" The answer can be faculty (and a learning design team), an algorithm, or a network of peers (networked learning communities). Each TEL format has a 60+ years long, well-documented history.
TEL innovations are often built around new technologies and established pedagogies; they are rarely associated with pedagogical innovation. Therefore, the history of the technology-enhance learning formats in use can (1) help us predict outcomes and challenges we can expect, and (2) realize what is actual innovation and what is a new iteration of an established practice.
Each of these three TEL formats come with benefits and noticeable limitations. The challenge is that it is hard to combine those learning formats in a manner that neutralizes limitations.
In more detail:
- Faculty-guided self-paced learning at scale (like xMOOCs) works well for experienced learners, but it is not the best solution for many learners (especially the struggling ones).
- Peer-guided learning at scale works well for informal and non-formal learning. It is usually an essential part of successful quality improvement projects. However, it does not work well with the standard school or CME/CPD curriculum (with predefined learning objectives).
- Adaptive learning systems work well for many learners, but they work well only with well-defined topics. Justin Reich uses examples of mathematics and early reading, where results can be easily standardized. Adaptive learning relies on quiz questions and applications that grade learners' assignments (autograders) – methods that cannot evaluate the quality of reasoning well. Hence, adaptive learning used to train practicing professionals in complex topics as healthcare assumes some compromises in the quality and depth of learning. However, adaptive learning programs are good preparation for standardized tests (like board exams).
Consequently, 1) TEL learning at scale was able to deliver many context-specific improvements – but not a sweeping system-wide improvement, and 2) for successful TEL at scale, we should combine technological innovations with well-planned improvements of the complex context/system.
Vjekoslav Hlede, PhD is a Senior Learning Management Specialist with the American Society of Anesthesiologists, Chicago.
Reich, J. (2020). Failure to Disrupt: Why Technology Alone Can't Transform Education: Harvard University Press.