The world is not static. It is dynamic and uncertain. Organisms compete and forage for scarce resources. To survive and thrive in this dynamic and uncertain environment while competing and foraging for scarce resources, we need to constantly adapt. Learning is what enables us to adapt to our environment – to succeed in uncertainty and among competition. Learning is acquiring information about the world. It involves exploring and making sense of our world. Memory is the system that retains our information about the world. Memory enhances our abilities to perform within our world (Goelet et al., 1986; Kandel et al., 2014). In other words, learning can be thought of as the process of acquiring information about the world; and memory the process of retaining that information.
Because of this dual phase process, and from a constructivist point of view, category (or concept) learning and skill learning need to establish links to one’s previous knowledge. As said, learning is a dynamic-over-time process that relies both on perceptual-short term processing and a short-to-long term establishment of learning in brain circuits. The constant retrieval and revision of learned concepts and skills, by means of review and experience, make the learnings more confident, durable and useful. Returning to the constructivist view of learning in biological terms, this means that better acquisition is achieved when links to prior knowledge networks are more abundant. In other words, connections between what’s being learned and what’s been previously learned (and is relevant to the new learning) are established (Quartz, 1999).
These ideas can be put together with the understanding that we, as humans, automatically build mental maps – maps which, in many ways, resemble ‘road maps’ at different scales (e.g. highway maps, city maps; Fourez, 2008). Distinct regions on these mental roadmaps can represent distinct concepts and skills, while intersections reflect where certain concepts and skills overlap. Overall, these mental road maps denote the connections that help us to perceive, understand and test the world. These maps serve as the frames and patterns that we – more or less consciously – rely on to make sense of the world. For example, we build a map of our best friend, in terms of all the labels (i.e. characteristics) we collect from him and all the experiences that connect and fill these labels. This larger map of our friend also includes a smaller one that connects to who we are and the meaning that this friend and their labels give to us. Even if the subject matter is the same, the maps among people can differ greatly. For example, a person coming to Barcelona from Tokyo for the first time may build a map of Barcelona with what he/she knows from tourist guidebooks with the sparse maps built around major landmarks near their planned experiences. This would be very different from the mental map of Barcelona from someone who grew up in the city and has a lifetime of experiences that not only connect to the major landmarks but also emanate from the landmarks to all the surrounding nooks and crannies of the city. The Barcelonian’s map and its roads would be well-trodden. Thus, the number of framework ‘roads’ and their ‘width’ – which resemble the neuronal circuits sustaining knowledge – between these landmarks (e.g. categories of knowledge) would bear little resemblance between the two individuals. And as these maps are sustained by both encoding (i.e. how we acquire information) and memory (i.e. how we retain it, to use it later) the usefulness of the maps would differ greatly.
Despite what many once thought memory does not only relate to memorization [1]. It is not only activated when needed to retrieve facts. Rather, our current understanding is that our memory systems hold facts, habits, skills, and thoughts – memory underlies all that we can do and think. It is critical to learning and living. We cannot learn without the involvement of our memory system (Squire & Dede, 2015). To acquire information (e.g. learn) we have to be aware of the information and store the information – learning and memory are part of the same adaptive system. A system that enhances our ability to make accurate predictions for future actions. Thus, learning requires memory. So, it is learning (and memory) that enables us to adapt to our environment. Moreover, these adaptive mechanisms that support learning [2] are shared among species. From mammals to insects such as bees (Menzel, 1990).
References
- Squire, L. R., & Dede, A. J. (2015). Conscious and unconscious memory systems. Cold Spring Harbor perspectives in biology, 7(3), a021667.
- Goelet, P., Castellucci, V. F., Schacher, S., & Kandel, E. R. (1986). The long and the short of long–term memory—a molecular framework. Nature, 322(6078), 419-422.
- Kandel, E. R., Dudai, Y., & Mayford, M. R. (2014). The molecular and systems biology of memory. Cell, 157(1), 163-186.
- Menzel, R. (1990). Learning, memory, and “cognition” in honey bees. Neurobiology of comparative cognition, 237-292.
- Devonshire, I. M., & Dommett, E. J. (2010). Neuroscience: viable applications in education?. The Neuroscientist, 16(4), 349-356.
- Quartz, S. R. (1999). The constructivist brain. Trends in Cognitive Sciences, 3(2), 48–57. doi: 10.1016/S1364-6613(98)01270-4
- Fourez, G. (2008). Cómo se elabora el conocimiento (Vol. 109). Narcea Ediciones.
- It is important to note that some terms used in this book may have different meanings for the educational community and the scientific community (Devonshire and Dommett, 2010). Our aim is to clarify the terms, prevent misconceptions, and build bridges between the communities. In this case, the educational community typically thinks of memory as being the process of individually and repeatedly memorizing some kind of content. In this book, memory refers to the biological process and cognitive function in which categorical (concept) or skill learning is established within the circuits of the brain. Importantly, the ways of acquiring and consolidating such types of learning involve much more than repeated memorization. Educational strategies such as peer learning, the use of imagery, recall practice, and/or active learning involving retrieval and elaboration of learning are emphasized. ↵
- Another paradoxical situation between the educational community and scientific community surrounds the term ‘learning’. Learning is often used to refer to the results of external or behavioral assessments that suggest that some new knowledge has been consolidated in someone. Learning can also refer to assessments both at the behavioral level, which in the lab can be typically measured with a learning curve (a curve that shows that the percentage of good trials upon learning a task increases across time), and at the internal level involving some changes to the structure and function of different brain elements such as synapses (i.e. brain connections). However, it has been challenging for the scientific community to attribute an external assessment of learning (i.e. a change in behavior) to changes at a circuit or even cellular/molecular level – this is often referred to as ‘the binding problem’. An additional definition is that learning is a naturally inborn capability that we constantly do to adapt to the world. ↵