Graphing has long counted as one of the quintessential process skills that scientists apply independently of particular situations. However, recent expert/expert studies showed that when asked to interpret graphs culled from undergraduate courses of their own disciplines, scientists were far from perfect in providing interpretations that a course instructor would have accepted as correct. Drawing on five years of fieldwork, the present study was designed to investigate graphs and graph-related skills in scientific research. In addition to the fieldwork, a think-aloud (...) protocol was used to elicit scientists' graph interpretations both on familiar and unfamiliar graphs. The analyses show that graph-related skills such as perceiving relevant graphical detail and interpreting the source of this detail emerge in the research process and are related to the scientists' increasing familiarity with a research object, instrumentation, and their understanding of the transformation process that turns raw data into graphs. When scientists do not know the natural object represented in a graph and are unfamiliar with the details of the corresponding data collection protocol, they often focus on graphical features that do not pertain to the phenomenon represented and therefore do not arrive at the correct interpretations. Based on these data, it is proposed that graphs are not only the outcomes of scientific research but also, in important ways, constitute representations that bear metonymic relations to the research context, most importantly to instrumentation, natural phenomenon, and the mathematical transformations used to produce the graphs from the raw data. I draw on the semantics of symbolic systems for articulating competencies and breakdowns in scientists' graphing-related practices. (shrink)

This study was designed to find out what scientists and science students actually do when they are reading familiar and unfamiliar graphs. This study provides rich details of the subtle changes in the ontologies of scientists and science students as they engage in the reading tasks assigned to them. In the course of the readers’ interpretation work, initially unspecified marks on paper are turned into objects with particular topologies that are said to correspond to specific features in the world. We (...) theorize this interpretive work as a transition of graphs from things to signs that come to stand for natural objects. Especially among physicists and theoretical ecologists, graphs enter new relations and become natural objects in their own right. (shrink)

We present a general cognitive architecture that tightly integrates symbolic, spatial, and visual representations. A key means to achieving this integration is allowing cognition to move freely between these modes, using mental imagery. The specific components and their integration are motivated by results from psychology, as well as the need for developing a functional and efficient implementation. We discuss functional benefits that result from the combination of multiple content-based representations and the specialized processing units associated with them. Instantiating this theory, (...) we then discuss the architectural components and processes, and illustrate the resulting functional advantages in two spatially and visually rich domains. The theory is then compared to other prominent approaches in the area. (shrink)

This paper discusses spatial cognition in the domain of minimally invasive surgery. It draws on studies from this domain to shed light on a range of spatial cognitive processes and to consider individual differences in performance. In relation to modeling, the aim is to identify potential opportunities for characterizing the complex interplay between perception, action, and cognition, and to consider how theoretical models of the relevant processes might prove valuable for addressing applied questions about surgical performance and training.

Six characteristics of effective representational systems for conceptual learning in complex domains have been identified. Such representations should: (1) integrate levels of abstraction; (2) combine globally homogeneous with locally heterogeneous representation of concepts; (3) integrate alternative perspectives of the domain; (4) support malleable manipulation of expressions; (5) possess compact procedures; and (6) have uniform procedures. The characteristics were discovered by analysing and evaluating a novel diagrammatic representation that has been invented to support students' comprehension of electricity—AVOW diagrams (Amps, Volts, Ohms, (...) Watts). A task analysis is presented that demonstrates that problem solving using a conventional algebraic approach demands more effort than AVOW diagrams. In an experiment comparing two groups of learners using the alternative approaches, the group using AVOW diagrams learned more than the group using equations and were better able to solve complex transfer problems and questions involving multiple constraints. Analysis of verbal protocols and work scratchings showed that the AVOW diagram group, in contrast to the equations group, acquired a coherently organised network of concepts, learnt effective problem solving procedures, and experienced more positive learning events. The six principles of effective representations were proposed on the basis of these findings. AVOW diagrams are Law Encoding Diagrams, a general class of representations that have been shown to support learning in other scientific domains. (shrink)

Six characteristics of effective representational systems for conceptual learning in complex domains have been identified. Such representations should: (1) integrate levels of abstraction; (2) combine globally homogeneous with locally heterogeneous representation of concepts; (3) integrate alternative perspectives of the domain; (4) support malleable manipulation of expressions; (5) possess compact procedures; and (6) have uniform procedures. The characteristics were discovered by analysing and evaluating a novel diagrammatic representation that has been invented to support students' comprehension of electricity—AVOW diagrams (Amps, Volts, Ohms, (...) Watts). A task analysis is presented that demonstrates that problem solving using a conventional algebraic approach demands more effort than AVOW diagrams. In an experiment comparing two groups of learners using the alternative approaches, the group using AVOW diagrams learned more than the group using equations and were better able to solve complex transfer problems and questions involving multiple constraints. Analysis of verbal protocols and work scratchings showed that the AVOW diagram group, in contrast to the equations group, acquired a coherently organised network of concepts, learnt effective problem solving procedures, and experienced more positive learning events. The six principles of effective representations were proposed on the basis of these findings. AVOW diagrams are Law Encoding Diagrams, a general class of representations that have been shown to support learning in other scientific domains. (shrink)

Diagrams are a form of spatial representation that supports reasoning and problem solving. Even when diagrams are external, not to mention when there are no external representations, problem solving often calls for internal representations, that is, representations in cognition, of diagrammatic elements and internal perceptions on them. General cognitive architectures—Soar and ACT-R, to name the most prominent—do not have representations and operations to support diagrammatic reasoning. In this article, we examine some requirements for such internal representations and processes in cognitive (...) architectures. We discuss the degree to which DRS, our earlier proposal for such an internal representation for diagrams, meets these requirements. In DRS, the diagrams are not raw images, but a composition of objects that can be individuated and thus symbolized, while, unlike traditional symbols, the referent of the symbol is an object that retains its perceptual essence, namely, its spatiality. This duality provides a way to resolve what anti-imagists thought was a contradiction in mental imagery: the compositionality of mental images that seemed to be unique to symbol systems, and their support of a perceptual experience of images and some types of perception on them. We briefly review the use of DRS to augment Soar and ACT-R with a diagrammatic representation component. We identify issues for further research. (shrink)

Self‐explaining is an effective metacognitive strategy that can help learners develop deeper understanding of the material they study. This experiment explored if the format of material (i.e., text or diagrams) influences the self‐explanation effect. Twenty subjects were presented with information about the human circulatory system and prompted to self‐explain; 10 received this information in text and 10 in diagrams. Results showed that students given diagrams performed significantly better on post‐tests than students given text. Diagrams students also generated significantly more self‐explanations (...) that text students. Furthermore, the benefits of self‐explaining were much greater in the diagrams condition. To discover why diagrams can promote the self‐explanation effect, results are interpreted with reference to the multiple differences in the semantic, cognitive and affective properties of the texts and diagrams studied. (shrink)