Learning

The term conceptual change refers to the development of fundamentally new concepts, through restructuring elements of existing concepts, in the course of knowledge acquisition. Conceptual change is a particularly profound kind of learning–it goes beyond revising one's specific beliefs and involves restructuring the very concepts used to formulate those beliefs. Explaining how this kind of learning occurs is central to understanding the tremendous power and creativity of human thought.

The emergence of fundamentally new ideas is striking in the history of human thought, particularly in science and mathematics. Examples include the emergence of Darwin's concept of evolution by natural selection, Newton's concepts of gravity and inertia, and the mathematical concepts of zero, negative, and rational numbers. One of the challenges of education is how to transmit these complex products of human intellectual history to the next generation of students.

Although there are many unresolved issues about how concepts are mentally represented, conceptual-change researchers generally assume that explanatory concepts are defined and articulated within theory-like structures, and that conceptual change requires coordinated changes in multiple concepts within these structures. New concepts that have arisen in the history of science are clearly part of larger, explicit theories. Making an analogy between the organization of concepts in scientists and children, researchers have proposed that children may have "commonsense" theories in which their everyday explanatory concepts are embedded and play a role. These theories, although not self-consciously held, are assumed to be like scientific theories in that they consist of a set of interrelated concepts that resist change and that support inference making, problem solving, belief formation, and explanation in a given domain. The power and usefulness of this analogy is being explored in the early twenty-first century.

A challenge for conceptual-change researchers is to provide a typology of important forms of conceptual change. For example, conceptual differentiation is a form of conceptual change in which a newer (descendant) theory uses two distinct concepts where the initial (parent) theory used only one, and the undifferentiated parent concept unites elements that will subsequently be kept distinct. Examples of conceptual differentiation include: Galileo's differentiation of average and instantaneous velocity in his theory of motion, Black's differentiation of heat and temperature in his theory of thermal phenomena, and children's differentiation of weight and density in their matter theory. Conceptual differentiation is not the same as adding new subcategories to an existing category, which involves the elaboration of a conceptual structure rather than its transformation. In that case, the new subcategories fit into an existing structure, and the initial general category is still maintained. In differentiation, the parent concept is seen as incoherent from the perspective of the subsequent theory and plays no role in it. For example, an undifferentiated weight/density concept that unites the elements heavy and heavy-for-size combines two fundamentally different kinds of quantities: an extensive (total amount) quantity and an intensive (relationally defined) quantity.

Another form of conceptual change is coalescence, in which the descendant theory introduces a new concept that unites concepts previously seen to be of fundamentally different types in the parent theory. For example, Aristotle saw circular planetary and free-fall motions as natural motions that were fundamentally different from violent projectile motions. Newton coalesced circular, planetary, free-fall, and projectile motions under a new category, accelerated motion. Similarly, children initially see plants and animals as fundamentally different: animals are behaving beings that engage in self-generated movement, while plants are not. Later they come to see them as two forms of "living things" that share important biological properties. Conceptual coalescence is not the same as simply adding a more general category by abstracting properties common to more specific categories. In conceptual coalescence the initial concepts are thought to be fundamentally different, and the properties that will be central to defining the new category are not represented as essential properties of the initial concepts.

Different forms of conceptual change mutually support each other. For example, conceptual coalescences (such as uniting free-fall and projectile motion in a new concept of accelerated motion, or plants and animals in a new concept of living things) are accompanied by conceptual differentiations (such as distinguishing uniform from accelerated motion, or distinguishing dead from inanimate). These changes are also supported by additional forms of conceptual change, such as re-analysis of the core properties or underlying structure of the concept, as well as the acquisition of new specific beliefs about the relations among concepts.

Mechanisms of Conceptual Change

One reason for distinguishing conceptual change from belief revision and conceptual elaboration is that different learning mechanisms may be required. Everyday learning involves knowledge enrichment and rests on an assumed set of concepts. For example, people use existing concepts to represent new facts, formulate new beliefs, make inductive or deductive inferences, and solve problems.

What makes conceptual change so challenging to understand is that it cannot occur in this way. The concepts of a new theory are ultimately organized and stated in terms of each other, rather than the concepts of the old theory, and there is no simple one-to-one correspondence between some concepts of the old and new theories. By what learning mechanisms, then, can scientists invent, and students comprehend, a genuinely new set of concepts and come to prefer them to their initial set of concepts?

Most theorists agree that one step in conceptual change for both students and scientists is experiencing some form of cognitive dissonance–an internal state of tension that arises when an existing conceptual system fails to handle important data and problems in a satisfactory manner. Such dissonance can be created by a series of unexpected results that cannot be explained by an existing theory, by the press to solve a problem that is beyond the scope of one's current theory, or by the detection of internal inconsistencies in one's thinking. This dissonance can signal the need to step outside the normal mode of applying one's conceptual framework to a more meta-conceptual mode of questioning, examining, and evaluating one's conceptual framework.

Although experiencing dissonance can signal that there is a conceptual problem to be solved, it does not solve that problem. Another step involves active attempts to invent or construct an understanding of alternative conceptual systems by using a variety of heuristic procedures and symbolic tools. Heuristic procedures, such as analogical reasoning, imagistic reasoning, and thought experiments, may be particularly important because they allow both students and scientists to creatively extend, combine, and modify existing conceptual resources via the construction of new models. Symbolic tools, such as natural language, the algebraic and graphical representations of mathematics, and other invented notational systems, allow the explicit representation of key relations in the new system of concepts.

In analogical reasoning, knowledge of conceptual relations in better-understood domains are powerful sources of new ideas about the less-understood domain. Analogical reasoning is often supported by imagistic reasoning, wherein one creates visual depictions of core ideas using visual analogs with the same underlying relational structure. These depictions allow the visualization of unseen theoretical entities, connect the problem to the well-developed human visual-spatial inferencing system, and, because much mathematical information is implicit in such depictions, facilitate the construction of appropriate mathematical descriptions of a given domain. Thought experiments use initial knowledge of a domain to run simulations of what should happen in various idealized situations, including imagining what happens as the effects of a given variable are entirely eliminated, thus facilitating the identification of basic principles not self-evident from everyday observation.

Case studies of conceptual change in the history of science and science education reveal that new intellectual constructions develop over an extended period of time and include intermediate, bridging constructions. For example, Darwin's starting idea of evolution via directed, adaptative variation initially prevented his making an analogy between this process and artificial selection. He transformed his understanding of this process using multiple analogies (first with wedging and Malthusian population pressure, and later with artificial selection), imagistic reasoning (e.g., visualizing the jostling effects of 100,000 wedges being driven into the same spot of ground to understand the tremendous power of the unseen force in nature and its ability to produce species change in a mechanistic manner), and thought experiments (e.g., imagining how many small effects might build up over multiple generations to yield a larger effect). Each contributed different elements to his final concept of natural selection, with his initial analogies leading to the bridging idea of selection acting in concert with the process of directed adaptive variation, rather than supplanting it.

Constructing a new conceptual system is also accompanied by a process of evaluating its adequacy against known alternatives using some set of criteria. These criteria can include: the new system's ability to explain the core problematic phenomena as well as other known phenomena in the domain, its internal consistency and fit with other relevant knowledge, the extent to which it meets certain explanatory ideals, and its capacity to suggest new fruitful lines of research.

Finally, researchers have examined the personal, motivational, and social processes that support conceptual change. Personal factors include courage, confidence in one's abilities, openness to alternatives, willingness to take risks, and deep commitment to an intellectual problem. Social factors include working in groups that combine different kinds of expertise and that encourage consideration of inconsistencies in data and relevant analogies. Indeed, many science educators believe a key to promoting conceptual change in the classroom is through creating a more reflective classroom discourse. Such discourse probes for alternative student views, encourages the clarification, negotiation, and elaboration of meanings, the detection of inconsistencies, and the use of evidence and argument in deciding among or integrating alternative views.

Educational Implications

Conceptual change is difficult under any circumstances, as it requires breaking out of the self-perpetuating circle of theory-based reasoning, making coordinated changes in a number of concepts, and actively constructing an understanding of new (more abstract) conceptual systems. Students need signals that conceptual change is needed, as well as good reasons to change their current conceptions, guidance about how to integrate existing conceptual resources in order to construct new conceptions, and the motivation and time needed to make those constructions. Traditional education practice often fails to provide students with the appropriate signals, guidance, motivation, and time.

Conceptual change is a protracted process calling for a number of coordinated changes in instructional practice. First, instruction needs to be grounded in the consideration of important phenomena or problems that are central to the experts' framework–and that challenge students' initial commonsense framework. These phenomena not only motivate conceptual change, but also constrain the search for, and evaluation of, viable alternatives. Second, instruction needs to guide students in the construction of new systems of concepts for understanding these phenomena. Teachers must know what heuristic techniques, representational tools, and conceptual resources to draw upon to make new concepts intelligible to students, and also how to build these constructions in a sequenced manner.

Third, instruction needs to be supported by a classroom discourse that encourages students to identify, represent, contrast, and debate the adequacy of competing explanatory frameworks in terms of emerging classroom epistemological standards. Such discourse supports many aspects of the conceptual-change process, including making students aware of their initial conceptions, helping students construct an understanding of alternative frameworks, motivating students to examine their conceptions more critically (in part through awareness of alternatives), and promoting their ability to evaluate, and at times integrate, competing frameworks.

Finally, instruction needs to provide students with extended opportunities for applying new systems of concepts to a wide variety of problems. Repeated applications develop students' skill at applying a new framework, refine their understanding of the framework, and help students appreciate its greater power and scope.