If the embodied/disembodied dichotomy has truly outlived its usefulness, then we are dealing with an expansive gray area where some aspects of knowledge and cognition are grounded in simulation, whereas others are not.
For example, rather than claiming that a student embodies the concept of "the water cycle," maybe instead there are discrete composite features of a model conception of the water cycle that are grounded in simulation (e.g., the movement of water between reservoir and atmosphere, condensation, and evaporation) and others that are not (e.g., transfer of solar energy to kinetic energy).
This means that although we are arguing that spatial thinking can be grounded in body-based simulation, we equally advocate a healthy skepticism throughout.
Embodied actions as we have argued may directly meet the needs of improving spatial thinking, given evidence that aspects of human knowledge and especially spatial knowledge and computation are grounded in perception and action simulation.
By testing the viability of learning environments derived from theory, we can provide real evidence about whether viewing cognition as offline body-based simulation grounded in sensorimotor experience is consequential for supporting students across the STEM spectrum.
Grounded cognition (Barsalou, 2008, p. 619) is a broad framework that posits that intellectual behavior 'is typically grounded in multiple ways, including simulations, situated action, and, on occasion, bodily states.' When the focus is on the grounding role of the body, scholars typically use the more restricted term, 'embodied cognition'.
In this paper we present an agent-based simulation model firmly grounded in disease dynamics, incorporating a detailed characterization of the natural history of infection, and 13 weeks worth of micro-contact and participant health and risk factor information gathered during the 2009 H1N1 flu pandemic.
Experiments, observations and computer simulations were grounded in scientific reflection about what should be explained in a rational manner, i.e., they largely followed the underlying scientific hypotheses.
It provides a novel process evaluation mechanism grounded in scientific principles for conducting healthcare system analysis, simulation-based drills, and workflow redesign.
Finally, the solution to the control problem in mirroring is grounded in the final common path architecture of sensorimotor cortex for both motor and simulation-based representations.
First, the impact of model accuracy on the ability to station keep (e.g. maintain X-Y position) using simulated planning and nature (ground-truth in simulation) models is studied.
