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A need exists to better understand how racial/ethnic minority students' critical consciousness development in response to marginalization may be involved in their educational and career development. We therefore examined the link between critical consciousness development and career decision self‐efficacy and career outcome expectations among racial/ethnic minority community college students. Following social cognitive career theory's conceptual pillars, we developed a testable model integrating critical consciousness and social cognitive variables. This model was tested with 135 racially and ethnically diverse community college students. Data analysis included path analyses and tests of model fit using structural equation modeling. Results suggested that (a) higher critical agency is linked to higher career decision self‐efficacy and outcome expectations and (b) critical action and reflection have a bidirectional link and predict higher critical agency. Implications for research and practice aiming to close educational and career gaps among racial/ethnic minorities are discussed.

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This paper presents a novel method of procuring and processing data for the assessment of civil structures via vibration monitoring. This includes the development of a custom sensor package designed to minimize the size/weight while being fully self-sufficient (i.e., not relying on external power). The developed package is delivered to the structure utilizing a customized Unmanned Aircraft System (UAS), otherwise known as a drone. The sensor package features an electropermanent magnet for securing it to the civil structure while a second magnet is used to secure the package to the drone during flight. The novel B-Spline Impulse Response Function (BIRF) technique was utilized to extract the Dynamic Signature Response (DSR) from the data collected by the sensor package. Experimental results are presented to validate this method and show the feasibility of deploying the sensor package on structures and collecting data valuable for Structural Health Monitoring (SHM) data processing. The advantages and limitations of the proposed techniques are discussed, and recommendations for further developments are made.

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