Sustainable Environments and Pro-Environmental Behavior

This thesis examines the ability of the sustainably designed building to alter occupant behaviors using LEED for New Construction and Major Renovation, Green Building Rating System™ as a standard of measure. A cross sectional survey compares the pro-environmental behaviors, intentions, environmental knowledge, and pro-environmental orientation of occupants working in a traditionally designed building and occupants working in a LEED-NC certified building located on the University of Nebraska - Lincoln Campus. While there is a visible increase in the pro-environmental variables for occupants working in the sustainable environment, data analysis indicates that these differences are not statistically significant for any of the measured variables. Significant correlations were discovered between an individual's environmental knowledge and pro-environmental behaviors as well as between an individual's pro-environmental orientation and pro-environmental intentions. These correlations support past findings of multiple research studies completed in the field of environmental psychology. Due to limitations of this research these findings must be clarified through continued study in the area of behavior influencing design.

Generalizing the dynamic field theory of spatial cognition across real and developmental time scales

Within cognitive neuroscience, computational models are designed to provide insights into the organization of behavior while adhering to neural principles. These models should provide sufficient specificity to generate novel predictions while maintaining the generality needed to capture behavior across tasks and/or time scales. This paper presents one such model, the Dynamic Field Theory (DFT) of spatial cognition, showing new simulations that provide a demonstration proof that the theory generalizes across developmental changes in performance in four tasks—the Piagetian A-not-B task, a sandbox version of the A-not-B task, a canonical spatial recall task, and a position discrimination task. Model simulations demonstrate that the DFT can accomplish both specificity—generating novel, testable predictions—and generality—spanning multiple tasks across development with a relatively simple developmental hypothesis. Critically, the DFT achieves generality across tasks and time scales with no modification to its basic structure and with a strong commitment to neural principles. The only change necessary to capture development in the model was an increase in the precision of the tuning of receptive fields as well as an increase in the precision of local excitatory interactions among neurons in the model. These small quantitative changes were sufficient to move the model through a set of quantitative and qualitative behavioral changes that span the age range from 8 months to 6 years and into adulthood. We conclude by considering how the DFT is positioned in the literature, the challenges on the horizon for our framework, and how a dynamic field approach can yield new insights into development from a computational cognitive neuroscience perspective.