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Session #2225

Design Learning as Conceptual Change: A framework for developing a science of design learning Wendy C. Newstetter, Mike McCracken Georgia Institute of Technology

Introduction In recent years, numerous industry–oriented and education-focused initiatives have sought to prepare designers to effectively respond to increasingly complex design problems. One such initiative has been to develop a science of 1 design. Finger and Dixon , in their review of mechanical engineering research, identified six ways in which researchers have advanced this project. They have developed: 1) descriptions of design processes 2) prescriptive models of design activity based on best practices of design found in industry 3) computer models of design processes 4) languages and representations 5) analysis to support design, and 6) design for manufacturing and life cycle. While these models and prescriptions have helped practicing designers improve design processes, it is not clear what contribution they have made to advancing our understanding of design learning. Some design educators 2 drawing on this work advocate "guided design" as a pedagogic strategy . Here students follow a set of design steps and phases that mimic those of an expert designer. Although compelling as a pedagogic strategy, no empirical research has been conducted to test whether design ability develops from rigidly following a prescriptive model of design phases and activities. This is because, at present, strong links between research into the science of design, design pedagogy and theories of design learning have yet to be forged. This paper proposes a framework for bringing these three endeavors together so as to develop a science of design learning.

Conceptual change as a framework A starting place for the proposed framework is the assertion that learning of any kind is filtered or interpreted through the learner’s lived experiences. Such experiences, sometimes school-based, sometimes not, constitute the learner’s prior knowledge. Research has shown that the development of an integrated and generative knowledge 3-5 base depends upon the learner’s prior knowledge . “A well-organized and coherent knowledge base initiates 6 inference, conceptual-ization, and the acquisition of principled understanding” . It seems a certainty that prior know- ledge is an essential variable in learning. 7 Unfortunately, however, prior knowledge is often incorrect. Variously referred to as preconceptions, naïve theories 8 9 10 , alternative frameworks and alternative theories , these incorrect notions based on experiences coalesce into knowledge structures that operate in theory-like ways. As such, they have explanatory power, inform action and often resist change even when there is repeated instructional evidence that the stored information is faulty. Following Piaget who demonstrated so clearly how children and adults differ, educational researchers in the late 1970s started to probe these learner knowledge structures, particularly in the areas of mathematics and science learning, to explain the documented difficulties students have in fully grasping scientific explanations for things like bodies in motion and electrical circuitry. Since that time numerous studies have demonstrated how such misconceptions can impede effective learning. Most agree that for learning to occur, a restructuring, possibly a demolition of the knowledge base, has to occur as well. What is not agreed upon is the meaning of restructuring or the means to accomplishing it. But before tackling the nature of or means to restructuring a base of knowledge, it is important to interrogate the structure of knowledge itself.

As stated above, a learner’s experiences often coalesce into a theory-like framework. A theory, as cognitive 11 scientists conceive of it, operates as a representational system. Johnson-Laird describes a theory as manifesting itself in three forms: 1) “propositional” representation —syntactic strings of symbolic elements (e.g. Constraint setting is a part of design) 2) “mental models”—structural analogs of real-world or imagined situations (e.g. A designer is setting constraints) 3) images—a mental model from a particular perspective (e.g. The architect is

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McCracken, M., & Newstetter, W. (2000, June), Design Learning As Conceptual Change Paper presented at 2000 Annual Conference, St. Louis, Missouri. 10.18260/1-2--8268