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The “Unlearning” Dilemma in Learning and Development

Key Stakeholders: IT Managers, IT Directors, Chief Information Officers, Chief Technology Officers, Chief Digital Officers, IT Governance Managers, and IT Project and Portfolio Managers.

Top Takeaways: One critical barrier to full adoption is the poorly addressed problem of unlearning. Anytime a new piece of software achieves some goal with a set of motor behaviors that is at odds with some well-established, habitized motor program, the learner struggles, evidences frustration, and is less likely to effectively onboard. Learning scientists can remedy this problem and can help IT professionals build effective training tools.


In my lifetime I have seen amazing advances in technology. I remember the days of overhead projectors, typewriters and white out. Now our handheld “phone” can project a high-resolution image, can convert spoken word into text, and can autocorrect errors.

The corporate world is dominated by new technologies that are making our lives easier and our workplaces more effective. Old technologies are being updated regularly, and new innovative, disruptive technologies are replacing them. It is an exciting time. Even so, this fast-paced technological change requires continuous learning and unlearning and this is where we often fall short.

Despite the fact that we all have experience with new technologies that have made our lives easier, and we applaud those advances, a large proportion of us (myself included) fear the introduction of a new technology or next release of our favorite piece of software. We know that new and improved technologies generally make us more productive and make our lives easier, at least in the long-run, but at the same time, we dread that new software because the training usually “sucks”.

This is a serious problem. New and improved technology development is time-consuming and expensive. The expectation is that all users will onboard effectively and reap the benefits of the new technology together. When many users actively avoid the onboarding process (yours truly included) this leads to poor adoption, underutilization of these powerful tools, and reduced profits. I refer to this as the “adoption gap”.

Why does this “adoption gap” exist and what can we do about it?

There are two reasons for the “adoption gap” and both can be addressed if training procedures are developed that embrace learning science—the marriage of psychology and brain science.

First, all too often a software developer or someone on their or another team is tasked with developing a training manual or training tool. Although these individuals are amazing at their jobs, they are not experts in training content development and delivery and often build ineffective tools. The relevant stories that I can tell from my 25-year career as a University Professor are many. I can’t count the number of times I received an email explaining (in a paradoxically excruciating and incomprehensible detail) how a new version of an existing software has changed, or how some new technology was going to be unveiled that would replace a tool that I currently used. I was provided with a schedule of “training workshops” to attend, or a link to some unintelligible “training manual”.

Because the training materials were not easy to use and not immediately actionable, I and my colleagues did everything that we could to stick with the legacy (and currently workable solution) or to get small group training from someone who knew how to use the technology. Although this worked for us, it was highly sub-optimal from the perspective of the University and it adversely affected productivity.

When the training tool is ineffective, employees will fail to use the new technology effectively and will quickly revert back to the legacy software that works and feels comfortable. I discuss this problem in a recent blog post and I offered some specific suggestions for improving technology training and development that include surveying users, embracing microlearning, using multiple media, and incorporating knowledge checks. Even so, that blog ignores the second major cause of the “adoption gap” and obstacles to IT onboarding, unlearning.

The Importance of Unlearning

In this report I take a deeper dive and explore a problem that is poorly understood in Learning and Development. This is the central problem of unlearning. Simply put, all too often a novel technology or software release will introduce new ways of achieving a goal that are very different from, or at odds with, the old way of achieving that goal.

Consider a typical office setting in which an employee spends several hours each day using some technology (e.g., Photoshop, a word processor, some statistics package). The employee has been using this technology on a daily basis for months, possibly years and using the technology has become second nature. The employee has become so proficient with this tool that their behaviors and motor interactions with the technology have become habitized. The employee does not even have to “think” about how to cut and paste, or conduct a simple regression, or add a layer to their project. They have performed these actions so many times that they have developed “muscle memory”. The brain develops “muscle memory” and habits that reduce the working memory and attention load and leave those valuable resources for more complex problems like interpreting the outcome of a regression or visualizing the finalized Photoshop project that we have in mind.

Now suppose that the new release changes the motor program associated with cutting and pasting, the drop-down menu selections needed to complete a regression, or the button clicks to add, delete or move project layers. In this case, your habits and muscle memory are telling you one thing, but you have to do something else with the new software. This is very challenging, frustrating, and working memory and attention demanding. One has to use inhibitory control so as not to initiate the habit, and instead think really hard to initiate the new set of behaviors, and do this over and over again so that they become habitized. This takes time and effort and is working memory and attention demanding. Many (yours truly included) will abandon this process and fall back on what “works”. Unlearning habits is much more challenging than learning new behaviors.

Key Recommendations to Support Unlearning

This is an area where learning science can be leveraged. An extensive body of psychological and brain science research (much of my own) has been conducted over the past several decades that provides specific guidelines on how to solve the problem of unlearning. Here are a few suggestions for addressing this problem.

Recommendation 1: Identify Technology Changes That Impact High Frequency “Habits”. When onboarding a new software solution or when an existing software solution is upgraded, the IT team should audit IT behavior to identify high-frequency functionality and monitor users’ behavior. Users should also be encouraged to provide feedback on their interactions with the software and to identify functions that they believe have changed. Of course, IT personnel could be proactive and audit high-frequency behaviors before purchasing new software. This information could guide the purchasing process. IT professionals must understand that although the technology as a whole may be improved with each new release, there is often at least one high-frequency task that changes and requires extensive working memory and attentional resource to overcome. Every such instance is a chance for an onboarding failure.

Recommendation 2: Apply Spaced Training and Periodic Testing to Unlearn High-Frequency Habits. Once high-frequency habits that have changed are identified, unlearning procedures should be incorporated to speed the unlearning, and new learning process. Spaced training and periodic testing can be implemented to speed this process. Details can be found here, but briefly, learning (and unlearning) procedures should be developed that target these habits for change. These training modules should be introduced across training sessions spaced over time (usually hours or days apart). Each training session should be preceded by a testing protocol that identifies areas of weakness that require additional testing. This provides critical information for the learner and allows them to see objective evidence of progress. In short, habits cannot be overcome in a single training session. However, the speed of learning and unlearning can be increased when spaced training and testing procedures are introduced.

Recommendation 3: Automate High-Frequency Tasks to Avoid the Need for Unlearning. The obvious solution to the learning and unlearning problem is to minimize the number of motor procedural changes across software releases or with new technology. A straightforward method is to ask employees which tasks that they locked into “muscle memory”. Once identified, software developers and experts in UI/UX could work to automate or optimize these processes. Tools such as optimized macros, machine learning-based optimization or new functionality would be the goal. The time saved onboarding users should be significant and the number of users abandoning the process should be minimized. Although aspirational, with the amount of “big data” available to developers, and the rich psychological literature on motor behavior, this is a solvable problem. We simply need to recognize the problem that employees have been aware of for decades, and acknowledge that the problem must be solved.

By taking these recommendations into account, technology onboarding will become more efficient, technology users will become more efficient, and companies will be better positioned to extract maximum value from their investment in new and transformative technologies.

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