Use it or lose it? Practical considerations for how to apply principles of neural plasticity.
10
STEM Learning
Garrett Moore
STEM (science, technology, engineering, math) is the buzzword in education today. STEM learning is crucial for many lines of work in society, and STEM learning is only likely to become more relevant as technology and society continues to advance. Because of all of the different uses that a STEM education has, pressure is being put on teachers to incorporate STEM learning into the curriculum for students as young as preschoolers. However, this leads to an important question: when in development are humans best suited for STEM learning? Is there a goldilocks age for STEM learning, an age where it can be learned optimally? One argument is that STEM learning should begin in adolescence, as much cognitive development happens in the elementary years of life and educators should wait to teach STEM until children are ready for science. After all, laboratory science is complicated, and when students are introduced to complicated material at too young an age it can have detrimental rather than beneficial effects. The other argument is that early to middle childhood is the best time for STEM learning. After all, young children love hands-on learning. From this perspective, children have enough brain power to start learning, which is beneficial because if young children learned science earlier, STEM fields might have a more diverse workforce. Both perspectives have some merit, but evidence shows that children are natural born scientists, and by changing and adjusting STEM learning to be appropriate to the age of the child, it is possible to teach STEM skills to younger children. Doing so is actually likely to be more beneficial in the long run for the children who are taught STEM skills than starting later in life would be, as they gain valuable experience which may lead them to be more interested in STEM learning later on in development.
Under the argument that STEM learning should begin in adolescence, it is important to understand what traditional STEM education looks like. STEM learning typically involves hypothetical reasoning and abstraction, as well as extensive application of the scientific method. Evidence exists that older children are better able to handle these kinds of tasks then younger children, with one notable example of this being the pendulum problem. In their textbook “Cognitive Development,” Bjorklund and Causey discuss the pendulum problem, which was originally used by Barbel Inhelder and Piaget to assess scientific reasoning ability in children of different ages. In the pendulum problem, children are given a rod from which strings of different lengths can be suspended, and objects of varying weight can be attached to the strings. The children were shown how the pendulum operated, and were then asked to determine what factors were responsible for the speed with which the pendulum swung. The four possible factors were string length, weight of object, height of release, and force of push, with several levels present within each factor (e.g., three different lengths of string). The children were given time to experiment with the apparatus before they were asked to give their answer (the correct answer was string length). Arriving at the correct answer through scientific reasoning would require varying a single factor while holding all others constant, and doing this for all possible factors involved until only a single logical conclusion was left.
Children in what Piaget called the preoperational period (age 2-7 years) rarely made correct observations about the problem and did not reason scientifically, and children in what Piaget called the concrete operational period (age 7-11 years) usually got off to a good start on the problem but rarely arrived at the correct conclusion. Concrete operational children had generally accurate observations, but they usually failed to isolate relevant variables and arrived at a conclusion before exhaustively testing their hypothesis. According to Barbel Inhelder and Piaget, only formal operational children (age 11-16) can test their hypothesis correctly and arrive at the only possible, logical conclusion (in other words, only they can use the scientific method and hypothetical and abstract reasoning). Given this information, waiting until adolescence to teach STEM learning would seem not only to be an effective option, but also the only option.
However, Piaget often overestimated the amount of logical and scientific thinking that adults and adolescents engage in (Bjorklund & Causey, 2018, Chapter 5). Adolescents and adults take mental shortcuts, make estimations, and arrive at conclusions before exhausting all possibilities (Bjorklund & Causey, 2018, Chapter 5). This is demonstrated particularly in adolescents, who are prone to thinking that is anything but logical. In theory adolescents are capable of hypothetical reasoning (scientific deduction, and induction), propositional reasoning (application of rules to abstract considerations), and are able to engage in metacognitive self-reflection and regulation (Kleinknecht, 2020). In practice, adolescents frequently engage in argumentation over what is real vs. what is possible, are egocentric (self-focused), feel like they are on stage for an imaginary audience, and engage in risk taking behavior due to their personal fable, a belief in their own uniqueness and invulnerability (Kleinknecht, 2020). Such beliefs and cognitions may interfere with the logical and scientific reasoning required for STEM learning to happen.
Piaget also significantly underestimated the cognitive abilities of young children. Young children have been shown to be capable of probabilistic reasoning as well as more advanced forms of thinking then Piaget gave them credit for (Kleinknecht, 2020). In a TED talk by Laura Schulz, she discussed an experiment which demonstrated the use of logical thought in even very young babies. In the first experiment babies were shown a box containing an equal number of blue and yellow balls, three blue balls were pulled from the box and were squeezed, producing a squeaking sound. A yellow ball was then given to the baby to play with, and more often than not the baby squeezed the yellow ball. The second condition was identical to the first, except there were far fewer blue balls in the box than yellow balls. The babies in the second condition were far less likely to squeeze the yellow ball than babies in the first condition, and were more likely to do other things with it. This research demonstrates that the babies were not only capable of generalizing evidence to a broader population, but they were much more likely to generalize the evidence when it was plausibly representative of the general population than when the evidence was clearly cherry picked. Indeed, when only a single blue ball was drawn from the mostly yellow ball box, babies were much more likely to squeeze the yellow ball, as a single ball being drawn could happen by random chance.
There is also evidence to suggest that kids are natural born scientists who build their own evidence about psychology, biology and physics (Bjorklund & Causey, 2018, Chapter 6). Children across all cultures are interested in animals and biological life, although their ability to determine what is alive changes with age (Bjorklund & Causey, 2018, Chapter 6). Movement is a key component in whether children think that something is alive or not, although with increasing age children make clearer distinctions between animate and inanimate objects (Bjorklund & Causey, 2018, Chapter 6). A child’s understanding of biology becomes more adultlike with age and is affected by culture and the child’s experience with animals (Bjorklund & Causey, 2018, Chapter 6). Across all of these ideas and changes is the assumption that children possess some rudimentary intuitive theories to represent and reason about the principal domains of knowledge, and that these theories are evaluated in a probabilistic way based on experience (Bjorklund & Causey, 2018, Chapter 6). This has been seen in a number of different studies relating to young children’s understanding of the world and ability to think scientifically (Bjorklund & Causey, 2018, Chapter 6). Young children gradually acquire more advanced scientifically based reasoning throughout their development, it is not something which simply appears during adolescence.
So when is the best time for children to be taught STEM? Although STEM can be taught during adolescence, it may be more effective to start STEM learning at an earlier age. Doing so will require STEM learning to be adjusted to an appropriate level, and should show respect to children’s gradual acquisition of scientifically based reasoning. Although young children may not be able to complete the same STEM tasks as adults, and may not be able to fully employ the scientific method, some aspects of STEM can be modified and presented to younger children in a way that is understandable.
Teaching appropriate STEM skills to children could be highly beneficial, especially if young children learn STEM skills even as their own understanding of the natural world gradually expands. Gradually building on STEM knowledge alongside the children’s own development could not only allow for STEM learning to be done at a younger age, but giving them an appropriate experience with STEM early in development may get children interested in STEM related concepts so they will continue to learn them later in development. It is also worth noting that with early exposure to STEM concepts, children are accommodating schematic knowledge that they can then use later on in adolescence. When they have something to build on and can use assimilation techniques in adolescence, they might even learn more and accomplish more that they might have otherwise. Teachers could redesign the curriculum for STEM learning so that it is age-appropriate, and they can use knowledge of what young children are capable of in terms of scientific reasoning to create STEM learning opportunities for young children and adolescents alike.
References
Bjorklund, D. F., & Causey, K. B. (2018). Children’s thinking: cognitive development and individual differences (6th ed.). Los Angeles: Sage.
Kleinknecht, E. (2020). Cognitive development week 12 [PowerPoint slides]. Moodle@PacU. https://sso.pacificu.edu/cas/login?service=https%3A%2F%2Fmoodle.pacificu.edu%2Flogin%2FFinde.php
Schulz, L. (2015, March). Retrieved April 16, 2020, from https://www.ted.com/talks/laura_schulz_the_surprisingly_logical_minds_of_babies