Imagistic Simulation in Scientific Model Construction

This paper examines video taped model construction protocols from an expert to generate hypotheses concerning: the relationship between "runnable" schemas and imagery during mental simulation; and how assembling a scientific model from simpler runnable schemas can "transfer runnability" to the model. By the end of the learning episode the expert appears to have acquired something more than a new symbolic relationship. He appears to have an imageable, runnable model where the imagability and runnability have been transferred or "inherited" from a source analogue. One source of support for this finding comes from observing similar depictive hand motions as the subject thought about the analogue case and later about the developing target model. Parallel observations have also been made in student protocols.

Topics in Cognitive Science, 2009

Interest in thought experiments (TEs) derives from the paradox: ''How can findings that carry conviction result from a new experiment conducted entirely within the head?'' Historical studies have established the importance of TEs in science but have proposed disparate hypotheses concerning the source of knowledge in TEs, ranging from empiricist to rationalist accounts. This article analyzes TEs in think-aloud protocols of scientifically trained experts to examine more fine-grained information about their use. Some TEs appear powerful enough to discredit an existing theory-a disconfirmatory purpose. In addition, confirmatory and generative purposes were identified for other TEs. One can also use details in transcript data, including imagery reports and gestures, to provide evidence for a central role played by imagistic simulations in many TEs, and to suggest that these simulations can generate new knowledge using several sources, including the ''extended application'' of perceptual motor schemas, implicit prior knowledge, and spatial reasoning operations, in contrast to formal arguments. These sources suggest what it means for TEs to be grounded in embodied processes that can begin to explain the paradox above. This leads to a rationalistic view of TEs as using productive internal reasoning, but the view also acknowledges the historical role that experience with the world can play in forming certain schemas used in TEs. Understanding such processes could help provide a foundation for developing a larger model of scientific investigation processes grounded on imagistic simulation (Clement, 2008).

This article offers an interpretation of scientific concepts’ understanding in terms of mental simulation. A series of studies are reviewed, showing that mental simulation is a fundamental form of computation in the brain, underlying many cognitive skills such as mindreading, perception, memory, and language. Current investigations in cognitive neuroscience are then considered, that relate mental simulation with brain regions involved in episodic memory, future thinking and problem solving. The role of mental simulation in scientific thinking is described and a link is made with model-based reasoning in scientists and students. The simulation and linguistic systems are shown to be integrated and mutually reinforcing. The reviewed studies provide a set of ideas that are applied to science education. Finally, instructional design guidelines are proposed to facilitate the mental simulation-based process of concept understanding, together with a list of possible difficulties in concept comprehension and conceptual change.

"A successful instructional use of simulations at school and in training courses requires a careful consideration of the cognitive mechanisms of learning. The most interesting educational simulations are not so much those which want to be a copy of reality, but those which favour in the student a process of internalization of the simulated model and a process of externalization and comparison of one’s mental models. Model-based education represents a new and promising paradigm in the designing and the didactic use of simulations."

Cognitive Psychology, 1996

We investigated whether people can use analog imagery to model the behavior of a simple mechanical interaction. Subjects saw a static computer display of two touching gears that had different diameters. Their task was to determine whether marks on each gear would meet if the gears rotated inward. This task added a problem of coordination to the typical analog rotation task in that the gears had a physical interdependency; the angular velocity of one gear depended on the angular velocity of the other gear. In the first experiment, we found the linear relationship between response time and angular disparity that indicates analog imagery. In the second experiment, we found that people can also solve the problem through a non-analog, visual comparison. We also found that people of varying spatial ability could switch between analog and nonanalog solutions if instructed to do so. In the third experiment, we examined whether the elicitation of physical knowledge would influence solution strategies. To do so, we manipulated the visual realism of the gear display. Subjects who saw the most realistic gears coordinated their transformations by using the surfaces of the gears, as though they were relying on the friction connecting the surfaces. Subjects who saw more schematic displays relied on analytic strategies, such as comparing the ratios made by the angles and/or diameters of the two gears. To explain the relationship between spatial and physical knowledge found in the experiments, we constructed a computer simulation of what we call depictive modeling. In a depictive model, general spatial knowledge and context-sensitive physical knowledge have the same ontology. This is different from prior simulations in which a non-analog representation would be needed to coordinate the analog behaviors of physical objects. In our simulation, the inference that coordinates the gear motions emerges from the analog rotations themselves. We suggest that mental depictions create a bridge between imagery and mental model research by positing the referent as the primary conceptual entity.

Organizational Learning Theory, Mental Models, Model-based Learning, Modelling and Simulation, Conceptual change, Perceptual simulations, Mental simulation, Thought experiments

Proceedings of the 7th International Colloquium …, 2001

In this paper, we argue that simulation introduces a completely new quality to the process of theory development. One of the main methodological characteristics of cognitive science (compared to other disciplines studying cognition) is the extensive use of simulation models. In the first part of this paper the foundations as well as implications from the perspective of epistemology as well as of philosophy of science will be developed. It will be shown how the method of simulation becomes an integral part for the process of theory construction in cognitive science. The second part of this paper is concerned with the question of identifying the adequate level of abstraction for computational models of cognition. The strength of cognitive models with high explanatory power lies in providing mechanisms on a conceptual level; i.e., on a level of abstraction which respects the structure of underlying (physical) mechanisms, but reduces the empirical details of these mechanisms in such a way that the resulting model sufficiently approaches the behavioral functionality.

Analogies are powerful ways to understand how things work in a new domain. We think this is because analogies enable people to construct a structure-mapping that carries across the way the components in a system interact . This allows people to create new mental models that they can then run to generate predictions about what should happen in various situations in the real world . This paper shows how analogies can be used to construct models of evaporation and how two subjects used such models to reason about evaporation .

Synthese, 2018

Philosophers have recently paid more attention to the physical aspects of scientific models. The attention is motivated by the prospect that a model’s physical features strongly affect its use and that this suggests re-thinking modelling in terms of extended or distributed cognition. This paper investigates two ways in which physical features of scientific models affect their use and it asks whether modelling is an instance of extended cognition. I approach these topics with a historical case study, in which scientists kept records not only of their findings, but also of some the mental operations that generated the findings. The case study shows how scientists can employ a physical model (in this case diagrams on paper) as an external information store, which allows alternating between mental manipulations, recording the outcome externally, and then feeding the outcome back into subsequent mental manipulations. The case study also demonstrates that a models’ physical nature allows ...

Virtual Reality: Cognitive Foundations, …, 2001

The focus of this paper is the process of knowledge acquisition (KA) and which role virtuality plays in this context. We argue that there are three different modes of knowledge acquisition which can be identified both in the domains of cognition and science: the empirical, the "constructive", and the "synthetic" mode. We show that the method of constructing knowledge in the virtual domain (i.e., the synthetic mode of KA) is not only a principal mode of KA in our cognition (e.g., thought experiments, making plans, etc.). It becomes increasingly important in the field of (natural) science in the form of simulations and virtual experiments. The attempt to find an answer to the question of whether simulation can be an information source for science, and to validate the computational approach in science, leads to a new interpretation of the nature of virtual models. This new perspective renders the problem of "feature extraction" obsolete.