The brain is the anatomical environment where organizational learning takes root. In order to learn effectively and efficiently, people have to be able to pay attention, absorb information, store that information long-term, and recall it when necessary. But learning is more than a mechanical function. It involves a variety of less tangible factors too.

Given the number of factors that need to be taken into consideration for learning to be personalized, it is virtually impossible to design a learning experience that is perfectly personalized. Below are three of the many scientific principles that could assist in designing learning that is tailored for the individual.

Brain-based dimensions of learning

Understanding how the brain learns can be valuable to learning professionals. Many studies demonstrate that the brain learns differently with reward, punishment, play and experience. And it is also important to understand what makes people want to learn, how they learn consciously and unconsciously, and how people learn differently from one another too.

Recommendations: Use these brain-based processes to assess your personalized methodologies. For example, you might ask, “Will this case history of a man help female employees attend to the principles it demonstrates?” “Is there reward or punishment built into this learning?” These kinds of questions will help you to design and iterate on existing programs.

Ground the learning in “identity”

Pharmacists and philosophers learn from different bodies of information. Similarly, within an organization, individuals differ in their learning preferences.

Theme-based learning (e.g., “customer-centricity,” “resilience,” or “agility”) may be helpful, but these words are rarely part of anyone’s everyday vocabulary and they quickly fall on deaf ears. Few people get out of bed and declare, “Today is the day to be agile and resilient.” Studies demonstrate that for people to learn, they should be able to identify with the content.

Recommendations: Rather than grounding learning in vague terms such as “agility,” “empathy,” or “team dynamics,” which frequently and inaccurately suggest that one must always be agile, empathic or team-oriented, it may make more sense to structure the learning around specific organizational challenges that are relatable.

Individuals can choose the challenges that are relevant for them, and on this basis, they will feel more motivated too. In the case that they are not aware of their challenges, assessment tools can be a way to enhance insight.

Combine data on learning and cognitive styles

There are many instruments to measure learning styles. Honey and Mumford describe four different kinds of learners: Those who learn from experience, from reflective observation, from exploring associations and interrelationships, or from doing or trying things with practical outcomes. Felder and Silverman categorize learners in terms of being sensory or intuitive, visual or verbal, active or reflective, and sequential or global.

However, detailed reviews by Pashler and colleagues and An and Carr found that there is no credible scientific evidence (despite a multitude of studies) for the validity and usefulness of “learning styles” as a way to determine learning success.

Yang and colleagues found that personalized learning is effective when Felder and Silverman’s learning styles and cognitive styles were combined. The specific cognitive style that they researched was field independence versus field dependence (i.e., the ability of the subject to tune out the surrounding context when information is presented).

Recommendations: Avoid personalizing learning based on learning styles alone. Rather, to start, combine learning and cognitive styles, and test to see if this actually impacts performance. To do this, learning clearly defines the outcomes you are measuring.

Conclusion

Personalized learning is both an art and a science. And proper personalization will likely require constant fine-tuning to the specific challenges that people face within organizations. Psychology and brain research can contribute greatly to idea generation as learning professionals improve and iterate on their design of personalized learning.

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