Learning reinforcement: from neuroscience to application in the workplace
Throughout our life, we accumulate a continuous flow of information which is processed by the different areas of our brain and leads to complex memory processes. Let us focus on learning reinforcement.
Throughout our life, we accumulate a continuous flow of information which is processed by the different areas of our brain and leads to complex memory processes. If we take the example of our immediate memory, the information recorded every day by our brain is not entirely stored, and this is a good thing: our brain automatically sorts it and relieves us from all the information considered as “secondary” to retain only a small part.
Although in this particular context forgetting information allows us to avoid an overload, it is a more significant problem when individuals are in a learning situation and see their knowledge fade away or even vanish after a while. To better understand this phenomenon, different studies based on cognitive science have been carried out and allowed to know the mechanisms which enhance knowledge retention and gave birth to different “learning reinforcement” tools.
What neuroscience shows
In psychology, human memory is described as the ability to record, store and remember passed experiences. It is a complex system whose mechanisms are still partly unknown. In 1885, the work of Hermann Ebbinghaus, a German experimental psychologist, highlighted the hypothesis of the forgetting curve  which defines how an information is lost after a while when our brain does not look to keep it. According to this theory, every learning context (at school or at work) leads to knowledge retention but also knowledge loss.
In concrete terms, cognitive science  has demonstrated, among other things, that the most efficient methods to enhance long-term memory are:
- Spacing revisions with bigger and bigger intervals
- Answering questions rather than going through lessons or videos
- Mixing different topics in a same revision session
Reinforcing learning: how does it work?
Once we identified the good practices, the next step was to use digital to go from traditional revision to a real learning reinforcement. In the past years, reinforcement tools have progressed to provide the learning with the best experience while guaranteeing long-term memory. How it works: reminders on the topics to be reinforced are presented under the form of questions and spaced in time. Although the different tools share this philosophy, the approaches vary:
- “One day, one question”: the learners receive a reminder every day, the objective for instructors being to maintain the contact with the learner on the long term and increase their engagement. The instructors must define what topic will be reviewed each day.
- Gamification: to better engage the learners, the reinforcement questions look like games.
- Spaced repetition: in this approach, the reminders are spaced in time with bigger and bigger intervals. As an example, the Leitner system  works this way. In this approach, we look to optimize learning reinforcement according to the forgetting curve: the more learners answer reminders, the stronger their memory is.
- The use of data: to go one step further in terms of learning reinforcement optimization, the results to the questions can be computed with algorithms to personalize the reminders. The topic and frequency of the reminders depend on each learner’s ability to memorize: the learners will receive more frequent reminders on the topics they struggle to memorize, and vice-versa.
Obviously, some learning reinforcement tools combine one or more of those approaches. As regards the learner experience, these tools are now available in web and mobile versions to be suited to everyone’s habits.
What are the applications in companies?
In the context of corporate learning, learning reinforcement has soon established itself as it meets an essential HR challenge: the return on investment of learning, often referred to as the ROL (Return On Learning). Time and budgets are invested in learning and development, it is then necessary to ensure the retention of the acquired knowledge and skills. Reinforcement learning tools are integrated in existing L&D environments to consolidate learning, no matter who are the learners and what is the type of course: classroom, e-learning or blended learning; short or long learning path; course on knowledge or know-how, etc. When it comes to soft skills, reinforcement learning will be used to develop reflexes and make sure the employee can apply the skills on the field. In terms of themes, there are many use cases: management, technical skills, regulatory compliance, security, etc.
Some advice to implement reinforcement learning in your company:
- The chosen tool has to be integrated with the existing learning tool(s) to provide a smooth user experience;
- The reminders must be occasional and take into account the employee’s strengths and weaknesses: we will choose individualized and spaced repetition to keep the employee motivated and avoid any frustration;
- Learning reinforcement needs to prove that it is efficient: analytics are essential for HR and L&D managers to measure the benefits of learning reinforcement on employees’ knowledge and skills, or even on their performance.
 Source: Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving Students’ Learning With Effective Learning Techniques: Promising Directions From Cognitive and Educational Psychology. Psychological Science in the Public Interest, 14(1), 4‑58.
Our latest articles about the topics: learning, science and Domoscio's news.