Background – Among influential education reports, there is clear consensus that an expansive range of intrapersonal (e.g. self-regulation) and interpersonal competencies (e.g. empathy) highly influence educational and career success. Research on teaching and learning these competencies is limited in engineering education.

Purpose/Hypothesis – This dissertation study explores the impacts of a mindfulness training program on first-year engineering students and aims to understand potential impacts on the development of intrapersonal and interpersonal competencies.

Design/Method – A four-session mindfulness-based training program was designed, developed, and facilitated to cultivate intrapersonal and interpersonal competencies. This study employed a multiphase mixed method design in which quantitative and qualitative data was collected from a total of 35 different students through a post survey (n=31), 3-month follow-up survey (n=29), and interviews (n=18). t-tests were used to evaluate the statistical significance of the program and a rigorous thematic analysis process was utilized to help explain the quantitative data.

Results – The results suggest that the majority of students became more mindful, which led to improved intrapersonal competencies (i.e. self-management, critical-thinking, focus, resilience, and well-being) and interpersonal competencies (i.e. empathy, communication, teamwork, and leadership).

Discussion / Conclusions – The study provides compelling evidence that mindfulness training can support the development of intrapersonal and interpersonal skills among engineering students, which can support their overall academic experience, as well as personal and professional development. Future design and development work will be needed to evaluate the integration and scalability potential of mindfulness training within engineering programs.

This study sought the lived and told stories of Native American women working in engineering and technology so that their voices may be heard in engineering education scholarship and challenge assumptions surrounding universal understandings of what it means to be a minority woman in science, technology, engineering, and mathematics (STEM). The study was directed by two research questions: (1) What are the lived and told stories of Native women in engineering and technology who are leading initiatives to improve their Native communities and (2) How do Native women’s understandings of their identities influence their work and acts of leadership? The study employed narrative inquiry as the methodological framework and was guided by theoretical frameworks of identities as constructed, multiple, and intersectional (Crenshaw, 1989; Tajfel & Turner, 1979), hybridity, and “third spaces” (Bhabha, 2012). The inquiry was also informed by feminist theories of Native scholars (Green, 1983; Kidwell, 1978) and engineering education (Beddoes & Borrego, 2011; Riley, Pawley, Tucker, & Catalano, 2009). The narrative analysis presented three narratives, based upon interviews, field notes, observations, and documents: (1) the story of a Navajo woman working within a large technical corporation (Jaemie); (2) the story of an Akimel O’odham-Mexican woman working within a tribally-owned technical business (Mia); and (3) the story of a Navajo woman growing her own technical business (Catherine). The narratives revealed a series of impactful transitions that enabled Jaemie, Mia, and Catherine to work and lead in engineering and technology. The transitions revolved around themes of becoming professionals, encountering and overcoming hardship, seeking to connect and contribute to Natives through work, leading change for their Native communities, and advancing their professional selves and their Native communities. Across the transitions, a transformation emerged from cultural navigation to leadership for the creation of new hybrid spaces that represented innovative sites of opportunity for Native communities. The strength of the Native spaces enabled Jaemie, Mia, and Catherine to leverage their identities as Native women within the global context of engineering and technology. The narratives denote the power of story by contributing the depth and richness of lived realities in engineering and technology.

Node-link diagrams are widely used to visualize the relational structure of real world datasets. As identical data can be visualized in infinite ways by simply changing the spatial arrangement of the nodes, one of the important research topics of the graph drawing community is to visualize the data in the way that can facilitate people's comprehension. The last three decades have witnessed the growth of algorithms for automatic visualization. However, despite the popularity of node-link diagrams and the enthusiasm in improving computational efficiency, little is known about how people read these graphs and what factors (layout, size, density, etc.) have impact on their effectiveness (the usability aspect of the graph, e.g., are they easy to understand?). This thesis is comprehensive research to investigate the factors that affect people's understanding of node-link diagrams using eye-tracking methods. Three experiments were conducted, including 1) a pilot study with 22 participants to explore the layout and size effect; 2) an eye tracking experiment with 43 participants to investigate the layout, size and density effect on people's graph comprehension using abstract node-link diagram and generic tasks; and 3) an eye tracking experiment with the same participants to investigate the same effects using a real visualization analytic application. Results showed that participants' spatial reasoning ability had significant impact on people's graph reading performance. Layout, size, and density were all found to be significant effects under different task circumstances. The applicability of the eye tracking methods on visualization evaluation has been confirmed by providing detailed evidence that demonstrates the cognitive process of participants' graph reading behavior.

In this research work, a novel control system strategy for the robust control of an unmanned ground vehicle is proposed. This strategy is motivated by efforts to mitigate the problem for scenarios in which the human operator is unable to properly communicate with the vehicle. This novel control system strategy consisted of three major components: I.) Two independent intelligent controllers, II.) An intelligent navigation system, and III.) An intelligent controller tuning unit. The inner workings of the first two components are based off the Brain Emotional Learning (BEL), which is a mathematical model of the Amygdala-Orbitofrontal, a region in mammalians brain known to be responsible for emotional learning. Simulation results demonstrated the implementation of the BEL model to be very robust, efficient, and adaptable to dynamical changes in its application as controller and as a sensor fusion filter for an unmanned ground vehicle. These results were obtained with significantly less computational cost when compared to traditional methods for control and sensor fusion. For the intelligent controller tuning unit, the implementation of a human emotion recognition system was investigated. This system was utilized for the classification of driving behavior. Results from experiments showed that the affective states of the driver are accurately captured. However, the driver's affective state is not a good indicator of the driver's driving behavior. As a result, an alternative method for classifying driving behavior from the driver's brain activity was explored. This method proved to be successful at classifying the driver's behavior. It obtained results comparable to the common approach through vehicle parameters. This alternative approach has the advantage of directly classifying driving behavior from the driver, which is of particular use in UGV domain because the operator's information is readily available. The classified driving mode was used tune the controllers' performance to a desired mode of operation. Such qualities are required for a contingency control system that would allow the vehicle to operate with no operator inputs.