Apr 9th 2021

Hands-on Training: Exploring the Science of Somatic Skill-Ups


How does our brain work? Is hands-on training better than completely cognitive efforts when it comes to learning new skills? That’s the cultural consensus. Most of us are acquainted with the oft-repeated adage about teaching someone to fish: Helping them develop the skills to feed themselves offers more value than just giving them a meal.

But repetition doesn’t make reality. Let’s explore the evolving research on critical cognitive connections and somatic skills learning at scale.

By the Numbers

The hands-on training argument comes with the clear benefit of common sense. If someone tells you how to do something you’ve never done before — such as repair a complex machine or navigate a cluttered computer desktop — it’s not unreasonable to conclude that you’ll make at least a few mistakes. But if they show you and give you the opportunity to practice the skill before leaving you on your own, you should do better, faster.

Thankfully, this isn’t one of those scientific concepts that logically zigs one way and experimentally zags another. Research backs up the conclusion that hands-on skill building is better than the alternative.

Consider recent findings from the University of Chicago, which showed that when children were able to physically experience scientific concepts while learning, they displayed increased understanding and performed better on tests. Those in the hands-on learning group scored 7% higher on average.

“Those students who physically experience difficult science concepts learn them better, perform better in class and on quizzes the next day, and the effect seems to play out weeks later, as well,” says study lead Sian Beilock.

Meanwhile, according to work from the University of Washington’s Department of Biology, college students enrolled in traditional lecture-based courses were 1.5 times more likely to fail than those in active learning classes. Another study form the Canadian Center of Science and Education (CCSE) backs the statistical benefits of skill-based learning — but also posits that student preference may play a role. In the CCSE work, 91.7% of participants said they preferred activity-oriented learning to the alternative.

Let’s Connect!

Data supports the common-sense conclusion that hands-on learning outperforms other methods in both information acquisition and retention. But why?

Answering this question means learning more about how our brains work: how they process, store and retrieve information over time. As Scientific American notes, our basic understanding of brain functions came in part from Ivan Pavlov’s classic conditioning experiments, which showed that dogs could be trained to salivate at the sound of a bell. Psychologist Donald Hebb used Pavlov’s research as a jumping-off point for his own work, suggesting that when brain synapses are activated simultaneously, the connections between them grow stronger, providing a physical representation of learning in progress. Analysis of Hebb’s work proved the idea accurate and gave rise to a catchy cognitive saying: “Synapses that fire together, wire together.”

But synapse syncopation isn’t enough to spur learning in isolation. Using MRI scans, researchers found that structural changes also took place in both gray and white brain matter when subjects were exposed to new concepts. For example, work from Tel Aviv University showed that when new players completed just 16 laps in a computerized racing game, their hippocampal brain region underwent structural changes to accommodate this new information. Meanwhile, analysis of highly skilled individuals such as musicians showed more robust regions around the auditory cortex. This was originally attributed to inherent brain structures that predisposed musical proclivity, but it was later shown to be the result of sustained skill building.

Thanks for the (Muscle) Memories

Hands-on learning can take many forms. In the case of the Chicago study, researchers used a bike wheel to help students learn about angular momentum. Participants held the wheel by the axle and were told to tilt the wheel from horizontal to vertical while holding a laser pointer steady on a nearby wall, but the resulting torque made the task difficult and helped them better understand the practical application of angular momentum. Later analysis of students via MRI showed that when participants in the hands-on study group looked at animated pictures of spinning bike wheels, the sensory and motor areas of their brains activated.

While new synapse connections and new brain structures are responsible for this immediate uptick in ability, what happens over time? What if students were to come back and revisit the bike wheel task weeks or months later? Muscle memory offers potential performative persistence.

In practice, two types of muscle memory contribute to sustained skills success: functional and physical.

Functional muscle memory is familiar — it’s the old “riding a bike” truism that suggests we’re capable of performing previously learned skills with relative competency, even after an extended period of time. Anecdotal evidence bears this out. While you won’t have exactly the same facility on your long-forgotten bike at age 30 as you did at age 15, it won’t take you long to remember the basics. More rigorous research also supports this conclusion but notes that mental memory rather than muscle plays the most important role in reliable repetition.

For example, in a study published in Neuron, researchers observed patients with amnesia and found that even when significant damage to brain structures prevented the formation of new memories or the learning of new skills, patients still retained previously learned skills. In one case, a patient with severe amnesia was still able to perform “mirror drawing,” which required him to draw a simple image on paper while looking in a mirror instead of at his hand. Despite an inability to remember any previous sessions or even recognize the equipment being used, the patient had no problems with the skill.

Alternately, physical muscle memory speaks to the DNA-driven ability of muscles to remember previous growth patterns and activate them again as needed. According to research from Keele University, this ability is linked to chemical tags known as epigenetic modifications that tell genes to activate or deactivate. Analysis of more than 850,000 DNA sites revealed that previous muscle growth can influence present development. This means that muscles developed for a particular skill earlier in life through continuous use or exercise demonstrate more substantive growth when reactivated. In other words, the epigenetic memory in your muscles can help to streamline skill building, even if it’s been awhile.

Interdisciplinary Impact

So, what does all this training talk mean in practice? How can schools and businesses bolster student and staff skill-building, and how can individuals improve their own abilities?

The answer is — there’s no single answer. Much like the skill building blocks of the brain itself, effective hands-on training is the result of ongoing, interdisciplinary efforts. Consider a factory floor worker being trained on a new piece of machinery. Part of the skills-building process comes from user manuals and expert instruction, the “standard” components of learning. Next up is hands-on use, which allows staff to apply theoretical data in context. From simply turning the machine on and off to seeing exactly how it responds to user input, this in-situ skills development is critical for creating new synapses and changing brain structures. Finally, regular revisitation of these training techniques is critical to help users bolster mental and muscle memory.

When it comes to supporting skills success, how does our brain work? Research makes it clear: Somatic skills training offers substantive benefits over historic, hands-off approaches but delivers best results as part of a multifaceted mental, memory and muscle learning framework.

Check out Northrop Grumman career opportunities to see how you can participate in this fascinating time of discovery in science, technology, and engineering.