@misc{cogprints661, editor = {R. Lewis and P. Mendelsohn}, title = {Situated cognition: How representations are created and given meaning}, author = {William J. Clancey}, publisher = {Amsterdam, North Holland}, year = {1994}, pages = {231--242}, journal = {Lessons from Learning}, keywords = {situated cognition, transaction, developmental psychology, representations, human learning}, url = {http://cogprints.org/661/}, abstract = {Representations have been viewed as the essential concern of cognitive science, yet few studies have examined how people create, perceive, and attribute meaning to new representational forms. How does the learner relate instructions he doesn't yet understand to features on the computer screen he can't yet parse into objects and relations? Linguistic schema models assume that the world comes pre-represented, already parameterized into objective features; reasoning operates on a stream of "perceptually obvious" symbols. In such an exclusively linguistic cognitive model, inference and comprehension rests on nothing but more words--definitions, causal relationships, classifications. Although it is well-known that such models are "ungrounded," that the symbols have no meaning to the program itself, little attempt has been made to find out how people create symbolic forms. What are the non-linguistic processes that control attention, affect reconceptualization, and correlate disparate ways of seeing? I present an example of human learning that falls outside linguistic schema theories, illustrating representation creation as perceptual interaction at both interpersonal and gestural-material levels. I focus on sequences of activity in which students' interpretation of what constitutes a representational language (and what it means) changes as they construct models of what they are seeing and doing. This social-perceptual analysis complements linguistic schema theories of novice-expert differences with more detailed learning mechanisms, emphasizing especially the nature of perception. This perspective leads to new experimentation and ways of observing and understanding student interaction with today's instructional programs.} }