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Students who graduate with an advanced degree in mechanical engineering are a diverse group in their path to post-baccalaureate degree attainment. Some students choose to obtain their master’s or Ph.D. post bachelors, but before they enter the workplace. Others enter the workforce and return as full-time students or progress on their advanced degrees while maintaining part- or full-time employment. Current accreditation standards for undergraduate degree programs are part of a changing landscape of standards and professional requirements that have adapted and continue to adapt as programs prepare students to work in professional engineering fields. Advanced degrees do not have the same set of standards as accredited undergraduate programs that are modified and examined for continuous improvement of the preparation of students for professional and academic careers. Without this overall agreement, what are advanced degree programs offering students and what skills should the programs be addressing the most? This research develops an understand of what the technical, professional, and academic requirements are expected for students seeking employment or continuing to advance in their chosen careers.

<p dir="ltr">This study explores how undergraduate engineering students interacted with users, user proxies, and user information during engineering design curricular experiences at a Large Midwestern University. Such practices are essential to human-centered design, a prominent framework within engineering design curriculums. While human-centered design can help students develop more sustainable, responsive, and desirable products for those who use them, engineering design educators need a better understanding of how and why engineering students engage in human-centered design. Such an understanding can enable us to learn how best to support students’ human-centered design learning.</p><p dir="ltr">The first phase of this study examined how undergraduate engineering students experienced human-centered design according to Zoltowski et al.’s (2012) <i>Ways of Experiencing Human-Centered Design</i> framework. I developed a survey instrument with open-ended reflections and used an a priori coding approach to identify how a large sample of undergraduate engineering students (n = 135) experienced <i>human-</i>centered design (as opposed to technology-centered or service-oriented design). Over half of the students demonstrated ways of experiencing design that incorporated human-centric design practices (51%), but a critical mass (31%) emphasized technology-centered or service-oriented views in their survey reflections. This finding suggests that human-centered design is more common compared to these other forms of design among students who were enrolled in the engineering design curriculums from which I sampled. This finding is promising in light of other studies showing students’ difficulty with making human-centric engineering considerations.</p><p dir="ltr">Next, I interviewed a subset of survey respondents (n = 21) whose reflections evidenced human-centered design experiences. Through interviews, I sought to develop a better understanding of the nature of their user interactions, including what aspects of the curriculum encouraged them to interact with users. I used critical incident technique to identify critical incidents that contributed to students’ deeper understanding of user experiences as they relate to their design project. I identified 81 critical incidents that I grouped into 12 unique user interaction types, which I then grouped into five design activities (Information Gathering, Idea Generation, Feedback, Iteration, and Evaluation). Each of these user interaction types afforded students the opportunity to integrate user information into their design process or prompt a change in their valuation or appreciation of user information during their design process, which ultimately contributes to a more comprehensive design experience. Instructors can use these user interaction types to guide their development of human-centered design experiences that promote students’ deeper understanding of and application of human-centered design.</p><p dir="ltr">Finally, I created a narrative depiction of two students’ design journeys by weaving the critical incidents I extracted from their interviews into a story. These two students were selected as they demonstrated variation in user interaction types, with one student’s story focused on immersion in a community context and the other focused on how multiple different user interaction types bolstered their confidence in their design decisions throughout their design journey. Thus, the stories depict how these two students’ design journeys supported their achievement of learning outcomes pertinent to human-centered design learning. Moreover, these stories provide guidance for instructors seeking to promote their students’ personal motivations and design confidence related to design projects in engineering design curriculums that value human-centered considerations.</p><p dir="ltr">Taken together, by understanding what leads students to engage with users throughout the design process and the nature of these engagements, the findings from this study position engineering educators to develop curricula and pedagogy that theoretically promote engineering students’ holistic applications of human-centered design.</p>

Researchers find that teacher self-efficacy influences student performance and student academic interest (Anderson, Green & Loewen, 1988; Ross, 1992; Ashton & Webb, 1986; Woolfolk & Hoy, 1990; and Muijs & Reynolds, 2001) and that prior teaching and teacher preparation experiences influence teacher self-efficacy (Preito & Altmaier, 1994). Since the late 1990s, a significant number of teachers have been drafted to teach engineering content in secondary schools across America (NAE & NRC, 2009). Given that none of those teachers were specifically prepared for that task in pre-service secondary engineering teaching licensure programs, some—or perhaps even many—of these new secondary engineering educators might be experiencing low teacher self-efficacy, which research suggests would lead to relatively ineffective secondary engineering teaching. Thus, the purpose of this study was to investigate experiences/factors that might influence secondary engineering teachers' self-efficacy, to inform those who are developing new pre- and in-service secondary engineering teacher preparation programs, and educational administrators / policy-makers. The population of Project Lead the Way (PLTW) secondary engineering teachers across the U.S. was invited to participate in this study. PLTW offers the best-known secondary engineering curriculum in the U.S. It features robust linkages/articulation agreements with post-secondary engineering programs (McVearry, 2003). The data for this study were obtained by administering the Teachers' Self-Efficacy Belief System-Self (TEBS-S) instrument (Dellinger, Bobbett, Oliver, & Ellett, 2008) and a demographic instrument developed by the researcher. The following factors had a statistically significant influence on teacher self-efficacy: pre-PLTW teaching experience, PLTW teaching experience, post-secondary course hours completed, teacher licensure process, and current and past teaching schedules. Implications of these findings may be used by administrators and educators who are actively involved in recruiting, selecting and preparing secondary engineering educators. / Ph. D.

Technology and Engineering Education has deep roots in Project Based Learning, with its beginning in the Industrial Arts, and tracing its ancestry to craft apprenticeships. This constructivist philosophy supports the idea that the creation of an artifact lends itself to higher order cognitive processes. This study analyzed the content of middle school Technology and Engineering Education Rubrics for evidence that higher order cognition was being assessed. Five raters coded ninety-eight performance indicators from six rubrics for the evidence of declarative, procedural, schematic, and strategic knowledge. Gwet's AC1 and percent agreement were calculated to determine inter-rater reliability. Additionally, the performance criteria were coded for six engineering constructs. The Engineering Constructs from the performance criteria were extrapolated to the performance indicators to see which Engineering Constructs were supporting higher order cognition. Analysis included the determination of whether or not the rubrics that were analyzed supported higher order cognition as well as their performance indicators, performance criteria, and which Engineering Constructs support higher order cognitive processes. / Doctor of Philosophy / What used to be known as the shop class, or Industrial Arts, has morphed into Technology and Engineering Education. With the emphasis now on teaching engineering processes and Project Based Learning instead of manual skills, there is a lack of research on whether or not the assessments have evolved enough to assess higher levels of cognition. Higher level cognitive processes in engineering design are defined as those processes that are used to troubleshoot and create. This study analyzed middle school Technology and Engineering Education rubrics to look for evidence of assessing higher order cognition. Rubrics are a commonly used tool in Project Bases Learning as a form of assessment. Rubrics are separated into two distinct parts: performance criteria; and their performance indicators. The performance criteria were analyzed for six different Engineering Constructs, and the performance indicators were analyzed for four cognitive constructs. The analysis looked for evidence of higher-level cognitive constructs, and which Engineering Constructs supported higher level cognitive constructs.

The problems existent within the built environment are inherently complex due to the interactions between different stakeholders, structures, and systems. The reductionist approach vastly utilized by engineers is not appropriate for dealing with this complexity. Engineers need to be trained to think in systems in order to fully explore the design problem space and therefore identify appropriate design solutions. The study here presented investigates the possibility of the use of concept mapping as an intervention to prime engineering students to think in systems. In the study, 66 engineering students were given two problem framing tasks. Half of the sample received the priming intervention before each task. The control and the intervention group were compared across different metrics. The time spent on the task and length of responses were used as measures of cognitive effort. The number of systems mentioned and the semantic distance between words used in each response were the metrics used for exploration of the design space. Results of the analysis for one of the tasks were significant. The findings suggest that the participants who received the concept mapping priming intervention were able to sustain cognitive effort longer and explore a wider design problem space. / Master of Science / The problems existent within the built environment present interdependencies that need to be identified before suitable solutions can be designed. Engineers need to be able to identify and understand these complex relationships. However, engineers are instead trained and prompted to apply a reductionist approach to problem solving, which isolates parts of a system in order to reduce complexity and facilitate the design process. Concept maps, a graphical tool utilized to display the relationships between concepts and ideas in a hierarchical form, could be used to assist engineers on applying a more holistic approach to problem solving. This research investigates if concept mapping activities can affect engineering students' ability to think in systems and consider all the variables behind a design problem. Participants in the study had to identify and describe everything that could be improved about two different systems familiar to Virginia Tech students. Half of the participants were asked to draw a concept map about each system before each task. All responses were compared between the group that did the concept mapping activity and the group that did not do it. The length in time and words of the responses, the number of systems mentioned, and the originality of the words used by each participant were the metrics utilized to compare the groups. Results suggest that concept mapping can be used as a tool to assist engineering students explore the design problem space more fully.

Grand challenges in engineering are complex and require engineers to be cognizant of different systems associated with each problem. The approach to think about these systems is called systems thinking. Systems thinking provides engineers with a lens to identify relationships between multiple components which helps them develop new ideas about the problem. Concept maps are a tool that enables systems thinking by helping engineers organize ideas and the relationship between ideas, graphically. The research presented in this thesis uses concept maps, as an intervention to help engineering students think in systems and, in turn, shape how they frame their design problem. The aim of the research was to understand the neurocognitive effects of engineering students thinking in systems. The effects of systems thinking on neurocognition is not well understood. Sixty-six engineering students were randomly chosen to either draw concept maps about a design problem or not. They were then asked to develop design problem statements for two design problems. Functional near-infrared spectroscopy (fNIRS) was used to measure changes in oxy-hemoglobin (oxy-Hb) in the prefrontal cortex (PFC) of students while they developed their design problem statements. A lower average oxy-Hb was observed in the group that was first asked to develop concept maps. The lower activation was observed in their left PFC. The group of students who first developed concept maps also demonstrated lower network connections between brain regions in the prefrontal cortex, which is a proxy for functional coordination. Using concept maps changed activation in students' brains, reducing the average neuro-cognition in the left PFC and reducing the need for functional coordination between brain regions. / Master of Science / Engineering challenges require engineers to think "outside the box". Concept mapping is a tool that encourages out of the box thinking. Concept mapping is the process of representing components of the problem and the relationship between components graphically. How the process of concept mapping changes the way engineers think is not well understood. Exploring various interconnected system components and their relationships may give rise to new ideas and this may be expressed differently in the brain. The research presented in this thesis explores how concept maps change engineering students' brain behavior. Sixty-six students participated in the study. Half of the participants (the intervention group) were required to draw concept maps before developing two engineering problem statements. The other half (the control group) were given the same two tasks to develop engineering problem statements but without being asked to first develop concept maps. A neuroimaging tool, called functional near-infrared spectroscopy, was used to measure change in the engineering students' prefrontal cortex (PFC) when they were developing problem statements. The PFC is generally associated with executive functions like planning, design, and creative thinking. The results indicate that concept mapping significantly changed brain behavior when developing problem statements. It reduced brain activation in the left PFC, a region generally associated with making analytical judgments and goal-directed planning. It also reduced the network complexity in the PFC, which is a proxy for functional connectivity. These results demonstrate how concept mapping can shape brain behavior when designing and lays the groundwork for future studies to explore how other interventions similar to concept mapping can help shape design thinking.

Engineering Education is a developing field, with new research and ideas constantly emerging and contributing to the ever-evolving nature of this discipline. Textual data (such as publications, open-ended questions on student assignments, and interview transcripts) form an important means of dialogue between the various stakeholders of the engineering community. Analysis of textual data demands consumption of a lot of time and resources. As a result, researchers end up spending a lot of time and effort in analyzing such text repositories. While there is a lot to be gained through in-depth research analysis of text data, some educators or administrators could benefit from an automated system which could reveal trends and present broader overviews for given datasets in more time and resource efficient ways. Analyzing datasets using Natural Language Processing is one solution to this problem. The purpose of my doctoral research was two-pronged: first, to describe the current state of use of Natural Language Processing as it applies to the broader field of Education, and second, to demonstrate the use of Natural Language Processing techniques for two Engineering Education specific contexts of instruction and research respectively. Specifically, my research includes three manuscripts: (1) systematic review of existing publications on the use of Natural Language Processing in education research, (2) automated classification system for open-ended student responses to gauge metacognition levels in engineering classrooms, and (3) using insights from Natural Language Processing techniques to facilitate exploratory analysis of a large interview dataset led by a novice researcher. A common theme across the three tasks was to explore the use of Natural Language Processing techniques to enable the computer to extract meaningful information from textual data for Engineering Education related contexts. Results from my first manuscript suggested that researchers in the broader fields of Education used Natural Language Processing for a wide range of tasks, primarily serving to automate instruction in terms of creating content for examinations, automated grading or intelligent tutoring purposes. In manuscripts two and three I implemented some of the Natural Language Processing techniques such as Part-of-Speech tagging and tf-idf (text frequency-inverse document frequency) that were found (through my systematic review) to be used by researchers, to (a) develop an automated classification system for student responses to gauge their metacognitive levels and (b) conduct an exploratory novice led analysis of excerpts from interviews of students on career preparedness, respectively. Overall results of my research studies indicate that although the use of Natural Language Processing techniques in Engineering Education is not widespread, although such research endeavors could facilitate research and practice in our field. Particularly, this type of approach to textual data could be of use to practitioners in large engineering classrooms who are unable to devote large amounts of time to data analysis but would benefit from algorithmic systems that could quickly present a summary based on information processed from available text data. / Ph. D.

This study of cooperative learning in post-secondary engineering education investigated achievement of engineering students enrolled in two intact sections of a computer-aided drafting (CAD) course. Quasi-experimental and qualitative methods were employed in comparing student achievement resulting from out-of-class cooperative and individualistic learning structures. The research design was a counterbalanced, repeated measures, nonequivalent control group design. During the first half of the semester, one course section served as the experimental group (cooperative learning) and the other section served as the control group (individualistic learning). During the second half of the semester, the treatment and control conditions were switched to the other section. Data collection involved a pretest, a mid-term exam, a final exam, weekly homework drawing grades, an introductory demographic survey, weekly peer reviews, and interviews. The data analyses showed that the differences between the treatment and control group means on the mid-term and final exams were not significant. However, the treatment group means on the weekly homework drawings were significantly higher than those for the control group in each half of the semester. The data revealed main effects of race, prior experience, time of achievement test administration, and prerequisite grade. A post-hoc analysis did not show significant differences among the various levels of prerequisite grade. Also, there were first-order interactions for gender-by-time, experience-by-time, method-by-time for the year as engineering major demographic variable, and method-by-academic year. Qualitative data revealed that most participants had positive group experiences, more participants preferred working in cooperative groups during more difficult activities than introductory material, academically stronger participants might have "carried" weaker participants in the cooperative groups, and there were times identified for cooperative group work during which groups did not work cooperatively. Based upon the findings in this study, one might reasonably conclude that cooperative and individualistic learning structures result in approximately equal student achievement. Thus, when deciding on the use of one learning structure over the other, instructors might focus on which approach seems more appropriate/practical for a particular instructional activity. / Ph. D.

The UTeach Observation Protocol (UTOP) is designed to capture what occurs in a classroom. The UTOP was developed for use in the nationally recognized UTeach program (uteach.utexas.edu) and has been validated nationally in the Gates Foundation Measures of Effective Teaching. (http://www.metproject.org/downloads/Preliminary_Findings-Research_Paper.pdf) Currently the UTOP has been used in both science and math classrooms and is being developed for use in English language arts and social studies classrooms as well. This report serves to begin the modification of the UTOP for use in an engineering classroom to evaluate engineering specific content. The UTOP has been described as a lens for reflection on teaching practices and the goal of this report is to help focus that lens more clearly on the engineering classroom. This tool was created for utilization in both educator and administrator roles. Teachers can use the UTOP to self-assess their own teaching practices as well as in observing other teachers and identify classroom best practices. Administrators and other classroom visitors can use the UTOP to understand and evaluate what occurs in a classroom for a multitude of outcomes. The methodology chosen in this report to create the engineering specific examples used real lessons that have been implemented in engineering classrooms and vetted in actual practice. Using both initial lessons from the teachers and their feedback along with language taken from the Next Generation Science Standard Framework and the UTeachEngineering Engineering Design Protocol, the examples were developed to show how to score each indicator on a scale of 1 to 5, with 1 being the lowest and 5 being the highest score, in a secondary engineering classroom. The next steps recommended for this work are to pilot the examples created in this report and test the usefulness of the examples created. This can be accomplished by field-testing it in UTOP training with teachers and modifying the information based on the feedback that they provide. The work described in this paper was made possible by a grant from the National Science Foundation (Award DUE-0831811). / text