How+New+Science+Curriculums+Affect+Brain+Research

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November 1998 || November 1998 | Volume **56** | Number **3** // Lawrence //// Lowery // Stimulated by research in cognitive science, a new view of learning draws its strength from cognitive neuroscience, cognitive psychology, and artificial intelligence. This new conception has a direct bearing on the nature how we develop curriculums and teach all subjects most effectively. This new consensus on the nature of learning helps educators understand what fosters learning and gives us ideas for improving those aspects of teaching that are ineffective or detrimental to learning. It supports the intuition of our most thoughtful teachers, and it describes how learners best move from being novices to becoming experts. We can express the new view quite simply: Learners do not simply mirror what they are told or what they read. The brain does not store a picture of an event. It does not directly record anything that is shown. What the brain does do is store a record of the neural activity that takes place in the learners' sensory and motor systems as they interact with the environment. Each record is a pattern of connections (dendrites/synapses) among brain cells (neurons) that can be reactivated to recreate the component parts of the experience. The reactivation defines the materials involved in the experience and other characteristics of the event. Thus, when learners place an image in their mind, they store its components in many different places and construct pathways among the places so that the entire system of storage and pathways can fire up as an image when learners recall the experience. Most researchers believe that all conscious and subconscious knowledge and behaviors are constructed as complex systems within the brain (Restak, 1980). For the brain to construct knowledge and behaviors, it must take in data that it can use for the construction. The only way the brain takes in data is through the sensory perceptions that enter through the windows of the body's five senses. Anything that a person does, perceives, thinks, or feels while acting in the world gets processed through complex systems of storage and pathways. If a student picks up a magnet, brings it toward another object, and feels the effect as that object is repelled or attracted by the magnet, that action is processed through the systems in the student's brain. The brain categorizes nonlanguage sensory perceptions of the world in different places. Shapes are stored in one place, color in another. Movement, sequence, and emotional states are each stored separately. Textures and aromas are stored elsewhere. Aspects of language are also stored in various parts of the brain. Nouns are separated from verbs, and phonemes are separated from words. As the brain constructs connections among brain cells, it connects the organizations of words, objects, events, and relationships in successively interwoven layers of categories. The result is that human knowledge is stored in clusters and organized within the brain into systems that people use to interpret familiar situations and to reason about new ones. When language—words and sentence structures—become part of the interweaving, the totality forms the basis for abstract thinking and problem solving (Kotulak, 1996). Because show-and-tell teaching methods, such as lectures, demonstrations, and textbook narratives, activate only a few of the many possible avenues to the brain, the National Science Foundation (NSF) has been funding multisensory laboratory-oriented science and mathematics projects: Full Option Science System (FOSS) and Science Education for Public Understanding Program (SEPUP), Lawrence Hall of Science; Science and Technology for Children (STC), National Science Resources Center; Insights, Education Development Center; and Math in Context, University of Wisconsin and the Freudenthal Institute. The enriched environments that these projects have developed involve learners in a variety of inquiries within powerful content contexts, thus increasing the likelihood that students will construct worthwhile knowledge and thinking capabilities. Although the individual constructs basic knowledge through experience, the quality of the construction depends on how well the brain organizes and stores the relationships between and among aspects in the event—how the arm and hand are positioned to hold the magnet (the relationship of the learner to the object), how the magnet can be moved and manipulated (cause and effect relationships between the learner's actions and the observed results), and how other objects behave in the presence of the magnet (cause-and-effect relationships in an interaction between objects in the environment). While making further explorations with the magnet, learners try to link new perceptions to what they have already constructed in the brain's storage systems. They use this prior knowledge to interpret the new material in terms of established knowledge. Whenever bits of information are isolated from these systems, they are forgotten and they become inaccessible to memory (Cowley & Underwood, 1998). Constructions in a student's brain depend on the interest and prior knowledge of the student and on the richness of the environment. Because students can explore, manipulate, test, and make transformations in the objects at hand, enriched environments and quality, hands-on experiences contribute significantly to piquing students' interests and linking their perceptions stored within the brain. Written formats, such as textbooks, give minimal help because symbols are not reality. They cannot be acted on or manipulated. Understanding what a symbol represents depends on prior experiential knowledge related to the symbol. For example, if you show young children a large, yellow M, that symbol will elicit memories of prior experiences at McDonald's restaurants. The power of printed words rests in the author's ability to enrich and extend the ideas already within a reader. New knowledge gained from reading is actually a rearrangement of prior knowledge into new connections. With something to work with, an author can help readers understand abstract ideas that they could never experience firsthand. But if readers have little in storage related to the content of what they read, they will gain little from reading. Because reading has such power when it follows experience, the recently developed National Science Foundation–sponsored elementary science programs provide reading materials after the students have gained some experience. Evidence is growing that such curriculum designs are improving reading, language arts, and other skills (Bredderman, 1985; Kyle, Bonnstetter, Gadsden, & Shymansky, 1988; Shymansky, Hedges, & Woodworth, 1990). The new curriculums provide good examples of how to enable learners to construct their own ideas through an exploration of relationships among materials (objects and ideas) and through the use of the reinforcement of prior knowledge. In one science investigation, students attempt to balance a cardboard cutout figure on the end of a finger. With only a simple challenge and without direct instruction, all children in a short time discover several ways to balance the figure. Imagine the many microperceptions that entered through their sensory windows. Imagine the microactions that the brain processed as it inquired, through hand and arm movements and trial-and-error tests, to locate a place on the figure where the figure would balance. As the students carry out the task, new constructions of relationships among systems in the brain are created and interwoven with the students' prior knowledge concerning balance. When students move clothespins on the cardboard figure to shift its center of gravity, they learn to balance the figure in various ways (see fig.1). The sequence of this instruction is important to move children from being novices to becoming experts. Each new challenge does two things: provides a rehearsal of prior knowledge constructions, thus making them more permanent, and provides something new that the brain can assimilate into its prior constructions, thus enriching and extending those constructions. Rehearsals reinforce what has been learned while adding something new. Each subsequent challenge is progressive: (a) the first balance; (b) second challenge includes noting changes to find relationship patterns; (c) third challenge transfers learning; (d) fourth challenge revises basic concept (added masses need not be placed on opposite sides of balance point). Subsequent challenges increase complexity and transferability. // Adapted from the FOSS Balance and Motion module for grades 1–2. Lawrence Hall of Science. // || At first, children balance the figure on its nose so that it stands straight up, then on its nose so that it balances horizontally. Children are challenged to balance it at some of the in-between positions. As the children balance and rebalance the figure, they reinforce the prior knowledge they learned about balancing while each new challenge adds a slightly different dimension that the brain incorporates into its prior systems. The result is that patterns are revealed. Such subsequent experiences are rehearsals. Rehearsals, as used in the new curriculums, are different from practice. Practice takes place when someone does the same thing over and over to improve a performance. It is useful in learning to type, play an instrument, or do multiplication tables. It enables a person to be efficient, accurate, or speedy—or all three. Practice is useful in a limited context, but it has little transferability. Rehearsal, in contrast, takes place when people do something again in a similar but not identical way to reinforce what they have learned while adding something new. New additions increase the likelihood that the knowledge they are learning is not task-specific. Non-task-specific experiences increase the likelihood that the knowledge will be transferable and useful in a variety of ways. Rehearsals strengthen the connections among the storage areas within brain systems. If connections are not strengthened, they will disengage and fade away. Thus the adage, Use it or lose it (Diamond & Hopson, 1998). As the balance activity continues, each subsequent challenge is progressive—new figures (triangles, arcs) help transfer prior learnings to new situations until students can balance their own pencils, create complex mobiles, and explain how each balance activity works. It is important to note that each challenge is consistent with a fundamental set of powerful scientific ideas that students reexperience through variations of activities that reinforce prior experiences and add aspects that improve transferability and deepen understandings. The balancing activity orchestrates each experience so that students construct knowledge on their own, in their own way. Compared with traditional textbook instruction, which covers many topics quickly and superficially (Valverde & Schmidt, 1997-1998), the new National Science Foundation–sponsored curriculums spend more time on fewer, but more powerful, topics. The curriculums then strategically advance the topics throughout subsequent grade levels, guided by research on developmental capacities and content components. Sequences begin with repertoire building, a learning capacity that begins before birth and continues through life. The curriculums then move through simple inquiries, capitalizing on comparative and organizational capacities that begin in early childhood and remain throughout life. They then introduce systematic inquiries, which require combinatorial and relational capacities that become viable around age 12. Flexible abstract reasoning is used extensively in advanced curriculums (Bruner & Kenny, 1966; Allen, 1967; Piaget, 1969; Pascual-Leone, 1970; Case, 1974; Hooper & Sipple, 1974; Wright, 1997; Lowery, 1998). The fundamental underlying strategy of new curriculums rests in the way they sequence developmentally appropriate concepts that progressively link and web together toward a grand idea. Without such a strategy, the curriculum is a pseudocurriculum, an eclectic collection of activities with weak, if any, linkages and no long-range goals or purpose. All true curriculums decide at what age or age range each component is best taught. The underlying sequential strategy gives the curriculum its integrity. No grand ideas are ever learned in one lesson or in one course of instruction. Students need years of accumulating appropriate experiences before they can understand such grand ideas as evolution, plate tectonics, the periodic table of elements, economic theories, DNA, mathematical proofs, and so on. And it is important to remember that for the new curriculums, the sequence of the learning transformations is important, not the grade levels or ages of acquisition. The new curriculums do not "speed up" the student's development or "move down" advanced concepts. Rather, their intent is to make what the student is capable of learning more useful, effective, relevant, and interesting and to enable the student to progressively build, from grade level to grade level, an understanding of the grand ideas of a subject by relating subsequent knowledge to prior knowledge. With so much explicit knowledge about how the brain works and with data so clearly supportive of the fact that students construct knowledge for themselves, it is surprising that so little real change has occurred in the way that science and math are taught. And it is even more surprising that some educators see no need to change from overusing passive-learner instructional methods, such as show-and-tell teaching, to using more thoughtful methods that enable students to construct meaning for themselves through exploring relationships and webbing those explorations to their prior knowledge. Today, thoughtful schools and school systems are engaged in systemic changes whereby new curriculums, especially in mathematics and science, are a fundamental component of those changes. And the array of quality, research-based curriculums is continuing to grow as scientists, mathematicians, and educators work together to study learning and improve the ways by which important ideas are learned. Allen, L. R. (1967). //An examination of the classificatory ability of children who have been exposed to one of the "new" elementary science programs.// Unpublished doctoral dissertation, University of California, Berkeley. Bredderman, T. (1985). Laboratory programs for elementary school science: A meta-analysis of effects on learning. //Science Education, 69//(4), 577–591. Bruner, J. S., & Kenny, M. J. (1966). //Studies in cognitive growth.// New York : Wiley. Case, R. (1974). Structures and strictures, some functional limitations on the course of cognitive growth. //Cognitive Psychology, 16,// 544–573. Cowley, G., & Underwood, A. (1998, June 15). Memory. //Newsweek, 131//(24), 48–49, 51–54. Diamond, M., & Hopson, J. (1998). //Magic trees of the mind.// New York : Dutton. Hooper, F., & Sipple, T. (1974). //A cross-sectional investigation of children's classificatory abilities.// (Tech. Rep.) Madison, WI : University of Wisconsin , Research and Development Center for Cognitive Learning. Kotulak, R. (1996). //Inside the brain: Revolutionary discoveries of how the mind works.// Kansas City, MO : Andrews & McMeel. Kyle, W. C., Jr., Bonnstetter, R. J., Gadsden, T., Jr., & Shymansky, J. A. (1988). What research says about hands-on science. //Science and Children, 25//(7), 39–40. Lowery, L. F. (1998). //The biological basis for thinking and learning.// (Monograph.) Berkeley, CA : Lawrence Hall of Science. Pascual-Leone, J. (1970). A mathematical model for the transition rule in Piaget's developmental stages. //Acta Psychologica, 63,// 301–345. Piaget, J. (1969). //Psychology of intelligence.// Totowa, NJ : Littlefield, Adams. Restak, R. M. (1980). //The brain: The last frontier.// New York : Warner. Shymansky, J., Hedges, L., & Woodworth, G. (1990). A reassessment of the effects of inquiry-based science curriculums of the 60's on student performance. //Journal of Research in Science Teaching, 27//(2), 127–144. Valverde, G., & Schmidt, W. (1997/1998, Winter). Refocusing U.S. math and science education. //Issues in Science and Technology,// 60–66. Wright, K. (1997). Babies, bonds, and brains. //Discover, 18//(10), 75–78. // Author's note: // Parts of this article originally appeared in 1997 as "The Nature of Learning" in the //FOSS Newsletter, 10,// 8–10. Copyright © 1998 by Lawrence Lowery || || ||
 * How the Brain Learns** Pages 26-30
 * How New Science Curriculums Reflect Brain Research **
 * Advances in neuroscience contribute to the development of curriculums that build on the way the brain constructs knowledge. **
 * Learners construct understanding for themselves.
 * To understand is to know relationships.
 * Knowing relationships depends on having prior knowledge.
 * Constructing Knowledge **
 * Perceiving Relationships **
 * Relationships and Prior Knowledge at Work **
 * Figure 1. Rehearsal Teaching **
 * Figure 1. Rehearsal Teaching **
 * Sequential Activities **
 * References **