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How do children learn about the world?

Getting an aspiration of learning through children, a cognitive-developmental approach.

As days close by of my firstborn, I got interested in how infants and children learn. After digging up some psychology articles, I would like to share some of them and also to compare them to see similarity and differences in our current AI approach.

Nurture or nature? How much we humans are affected by pre-wired from genetic inheritance and how much we are influenced by external factors through environmental exposure and life experiences?

This is not my usual post on Machine Learning but an attempt to step out from my narrow view and look at the broader picture. The post will consist of the following.

  1. Cognitive development theory
  2. Brain plasticity
  3. A Child’s brain and early experiences
  4. Case study — Feral children, Amazonian tribe the Piraha people
  5. What makes us human?

1. Cognitive development theory

Jean Piaget (1896–1980)

Jean Piaget (1936) was the first psychologist to make a systematic study of cognitive development. His contributions include a stage theory of child cognitive development, detailed observational studies of cognition in children, and a series of simple but ingenious tests to reveal different cognitive abilities.

When we talk about psychology and cognitive development Jean Piaget will definitely come into the picture. He unveils the mystery of the early stage of our development and provides us with a theory on cognitive development. Let's first look at his insides and the different stages of children cognitive development.

Adaptation process

Constructivism

Piaget was influenced by the theoretical notation called “Constructivism”. It derives from the idea that knowledge is not something fixed and stable, but rather constructed step by step. Children construct knowledge and form meaning based upon their experiences and adapting to the environment. There are three basic components of Piaget’s cognitive theory.

Schemas (A way of organizing knowledge)

Schemata (plural of schema) are basic building blocks of a mental model of the world, we could think schemas as “units” of knowledge used to relate to the aspect of the world, including objects, actions, and abstraction (e.g. theoretical concepts).

When children gain new experience through the environment they increase in numbers and complexity of the schemata.

E.g. Imagine yourself as a child and have your first attempt in ordering food. You have to build schemata (concept) of menu, money, different type of bread, etc. But why are we not confused by the different type of bread? Or a totally different type of food such as chicken rice? This is due to the adaptation process which allows us to map the new schema of chicken rice into the food category.

Schemas are like the vectors representations in machine learning.

Adaptation processes (Transition from one stage to another)

Our Intellectual growth can be understood as a process of adaptation/adjustment to the world. This allows us to update our understanding of the world, which allow our schemas to stay relevant to deal with new objects or situations. This is a process and consist of 3 stages Assimilation, Accommodation and Equilibration.

  • Assimilating causes an individual to incorporate new experiences into the old experiences. This causes the individual to develop new outlooks, rethink what were once misunderstood, and evaluate what is important, ultimately altering their perceptions.
  • Accommodation, on the other hand, is reframing the world and new experiences into the mental capacity already present. This happens when the existing schema (knowledge) does not work and needs to be changed to deal with new object or situation. Every individual conceives a particular idea in which the world operates.
  • Equilibrium is the changes in a mental state which occurs when a child’s schemas deal with most new information through assimilation. When new information arises, it causes an unpleasant state of disequilibrium when new information cannot be fitted into existing schemas (assimilation). Equilibrium drives the learning process as we do not like to be frustrated and seek to restore balance by accommodation. Once new information is mapped to a schema (new or old) we return to an equilibrium state.

Adaptation can be though as a clustering process of schemata or adding a new data point in our cluster. But the clustering algorithm will need be a form of self-organizing map as adaptation process know when to form new clusters when necessary. In the view of ML training, this will be updating our world model weights in so to create the best representation vector for objects or events. But ML lacks the capability to create new class when necessary. Our ML methods might need to learn how to form new schema when our existing ones does not capture these new experiences.

What we do not know are the dimensionality of such representation vector and the ideal way to drive learning (equilibrium process). In ML view, what drive the learning process is the optimizing function such as stochastic gradient descent (SGD), where we descent to find the global minimum. Could we human fall into local minimum where learning new concepts such as language and math is no longer possible? (Brain plasticity)

Piaget’s 4 stages of cognitive development

Piaget’s theory of cognitive development suggests that children move through 4 stages of intellectual development. His theory focuses on understanding how children acquire knowledge regarding concepts such as object permanence, number, categorization, quantity, causality and justice. The 4 stages are:

  • Sensorimotor (From birth to ages 18–24 months)

Knowing object permanence, an object exists even if hidden.

  • Preoperational (18–24 months to the age of 7)

Able to think about things symbolically. Relate a word or an object stand for something other than itself. But thinking is still egocentric, an infant has difficulty taking the viewpoint of others. This egocentric behaviour exhibits the cognitive limit of certain animals.

  • Concrete operational (Age from 7 to 11)

The major turning point in a child’s cognitive development as it marks the beginning of logical or operational thought. Children could understand different representation numbers such as age, mass and weight. But sometimes would need the assistance of using pictures and objects to solve difficult problems.

  • Formal operational (Adulthood 11 and above)

During this stage, it develops the ability to think about abstract concepts and logical test hypotheses. A child can work out things internally in their head rather than in physical form.

We often consider someone a genius if a person could work out complex problem using only internal operations without assist of physical form. E.g. like Nikola Tesla and Stephen Hawking. I believe we could train to solve complex problems in our head. But nature has the bigger role to determine how far this capability can be pushed. With that said, we will look into the effects of nurture and what happens when children have total absence of it. (4. Case study)

Each child goes through the stages in the same order, child development is determined by biological maturation (nature) and interaction with the environment (nurture). Piaget found that there are individual differences in the rate at which children progress and some individual may never attain the later stage.

2. Brain plasticity

https://www.researchgate.net/figure/Figure-Structural-and-functional-brain-imaging_fig1_323860846

Brain plasticity is the ability of the brain to modify its connections. Through modern science using functional brain imaging (image above) we now know the process of learning actually alters the structure of our brain at the cellular level. Our brain grows and changes to make room for new information.

Unlike a computer, neural pathways replicate functions so that small errors in development or temporary loss of function through damage can be easily corrected by rerouting signals along a different pathway.

Our neurons connection is at the peak during infancy, a baby will emerge from the womb with 100 billion neurons, nearly twice the size of an adult. This massive number of neurons is necessary for learning baby has to do in its first year of life. Synapse will shrink up when no longer needed, this is known as synaptic pruning.

A short explanation of brain plasticity by Hank Green

One of the obvious difference between the human brain and machine is biology has chosen to duplicate similar brain functions. Where if you were to attend any programming language course we were taught to maximise the reuse of functions. (Now you could use this as an excuse when duplicating functions 😏 )

Another different in biological brain is that the neurons grow, modify and prune when learning. On the other hand our ML architecture is fixed by design, we cannot change the design during training. Maybe this explain why dropout works by turning off some of the neurons. (You might also want to look into AutoML, model pruning)

3. A Child’s brain and early experiences

With the understanding of brain plasticity, we now know the brain of young children is very malleable, where early stimulation is important. An infant needs more than just milk, cuddles and nappy change.

Although the early stages of development are strongly affected by genetic factors; for example, genes direct newly formed neurons to their correct locations in the brain and play a role in how they interact. However, genes do not design the brain completely.

Instead, genes allow the brain to fine-tune itself according to the input it receives from the environment. For example speech sounds, stimulate activity in language-related brain regions. As the amount of input increases (if more speech is heard) synapses between neurons in that area will be activated more often.

The repeated use strengthens a synapse. Synapses that are rarely used remain weak and are more likely to be eliminated in the pruning process. Synapse strength contributes to the connectivity and efficiency of the networks that support learning, memory, and other cognitive abilities. Therefore, a child’s experiences not only determine what information enters her brain but also influence how her brain processes information.

Studies show that babies in their four months old could distinguish the sound of any language in the world but by the time they are eight months old, they will lose this ability.

Research also shows that rats raised in cages have less dendritic branching that the rats raised in an environment with climbing, hiding and tunnelling cages.

4. Case study

Feral children

Creation image of Oxana Malaya, Ukraine, 1991

A feral child is a human child who lived away from human contact from a very young age and has little or no experience of human care, love or social behaviour and crucially not learning of human language. Feral children are confined and bought up by animals, living in the wild in isolation.

Most of the feral children who have zero contact with human and have been raised by an animal from the age of 3–7, were having difficulty or unable to learn any language or human behaviour. They have missed the golden opportunity of learning language and pruning process have already started.

Oxana Malaya, Ukrain 1991

Ukrainian girl Oxana Malaya. According to Fullerton-Batten, “Oxana was found living with dogs in a kennel in 1991. She was eight years old and had lived with the dogs for six years. She ran on all fours, panted with her tongue out, bared her teeth and barked. Because of her lack of human interaction, she only knew the words ‘yes’ and ‘no’.” Oxana now lives in a clinic in Odessa, working with the hospital’s farm animals.

Amazonian tribe the Piraha people

https://www.facebook.com/piraha.people/photos/?ref=page_internal

Most people learn to count when they are children. Yet surprisingly, not all languages have words for numbers. A recent study published in the journal of Cognitive Science shows that a language lack of number words can result in people in these cultures have a difficult time performing common quantitative tasks.

The Piraha people of the Amazon are a group of about 700 semi-nomadic people living in small villages of about 10–15 adults, along the Maici River, a tributary of the Amazon. According to University of Miami (UM) anthropological linguist Caleb Everett, the Piraha are surprisingly unable to represent exact amounts. Their language contains just three imprecise words for quantities: Hòi means “small size or amount,” hoì, means “somewhat larger amount,” and baàgiso indicates to “cause to come together, or many.” Linguists refer to languages that do not have number specific words as anumeric.

From the above examples, I would like to think that our brain have fallen into a local minimum on learning to interact. Parts of the brain are pruned for preference of other functions and makes it impossibly hard to learn language or mathematics.

This also shows the importants of nurture, with total absence from it we could drastically change a person. So nature set the stage and nurture is the performance.

5. What makes us human?

We human are social animals able to communicate and pass down knowledge through language, we can think of alternative futures create abstraction in our mind and make deliberate choices accordingly. Social contact places an important role in our lives and our behaviour is practically shaped by the society we live in. Human learned to love, greed or act of violence through the interaction of others, as a child was not born with such emotions. Children are merely a mirror reflecting the society true colours and what is presented to them.

As a species, we are bound by moral responsibility. Our actions are altering this planet, we are the only species on this planet capable of foresight and ability to plan long-term future where rest of living creatures cannot. We should think harder on the impact we are leaving on this planet, not to think only in view of human but as a member of a larger family occupying this planet.

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Yiwen Lai

Yiwen Lai

🤖 AI² | NTU Computer Science Graduate | NUS M.Tech Knowledge Engineering | https://twitter.com/Niel_Lai

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