VTechWorks Repository :: Browsing by Author "Katz, Andrew Scott"

Browsing by Author "Katz, Andrew Scott"

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Can Engineers Be Primed to Think in Systems? An Empirical Study Showing the Effects of Concept Mapping on Engineering Students' Ability to Explore the Design Space.
Dias Ignacio Junior, Paulo (Virginia Tech, 2022-01-21)
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.
The Effects of Concept Mapping on Design Neurocognition: An Empirical Study Measuring Changes in the Brain when Defining Design Problems
Manandhar, Ushma (Virginia Tech, 2022-06-27)
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.
An Exploration of Students' Interests in Pursuing Careers in Environmental Sustainability
Griesinger, Tina Marie (Virginia Tech, 2023-11-29)
Although more people are transitioning into environmental sustainability careers, there is still a demand. This presents an opportunity for undergraduate engineering students to satisfy the demand for environmental sustainability professionals. The purpose of this qualitative exploratory study was to explore environmental sustainability learning experiences, from small in-class experiences to internships, and future career choices. By utilizing the social cognitive theory (SCCT) as a theoretical lens, this study explored participants' environmental sustainability interests, learning experiences related to environmental sustainability and their interest in pursuing a future career in environmental sustainability. This research addresses a gap in the existing literature by exploring how undergraduate engineering students' environmental sustainability learning experiences impact their decisions to pursue careers in this field, framed by the SCCT. The perspectives of twenty-five undergraduate engineering students in various engineering disciplines at Virginia Tech, an R1 public university in Blacksburg, Virginia. The participants were enrolled in ENGR3124, Introduction to Green Engineering, during the Fall 2022 semester and were interviewed for the study. Semi-structured online interviews were conducted via Zoom, allowing students to provide detailed information about their learning experiences and future career plans. Data was analyzed to (1) identify students' interest in pursuing a career in environmental sustainability (2) determine if students' interests have changed since they began their undergraduate studies (3) explore how learning experiences have impacted the students' future career choice. The findings discover that exposure to environmental sustainability learning experiences plays a meaningful role in impacting students' interests in pursuing careers in sustainability. Results reveal that factors such as personal values and salary considerations inspire career choices. Outcomes from this research suggest that promoting a connection between engineering education and environmental sustainability can inspire future engineers to actively pursue environmental sustainability careers and find solutions to sustainability issues. This underscores the significance of integrating sustainability experiences, such as a current events discussion in class or projects with an environmental sustainability element, into undergraduate engineering education. This research contributes to addressing the growing demand for people to address environmental sustainability issues, highlighting the role of learning experiences in shaping students' career interests. Further research in this area will be necessary for further developing strategies to encourage students to pursue sustainability-related careers and contribute to environmental sustainability initiatives.
Exploring Cyber Ranges in Cybersecurity Education
Beauchamp, Cheryl Lynn (Virginia Tech, 2022-04-01)
According to a report from McAfee, the global cost of cybercrime for 2020 was over one trillion dollars (Smith, Z. et al., 2020). Cybersecurity breaches and attacks have not only cost businesses and organizations millions of dollars but have also threatened national security and critical infrastructure. Examples include the Ransomware attack in May of 2021 on the largest fuel pipeline in the United States and the February 2021 remote access system breach of a Florida water treatment facility which raised sodium hydroxide to a lethal level. Improving cybersecurity requires a skilled workforce with relevant knowledge and skills. Academic degree programs, boot camps, and various certification programs provide education and training to assist this need. Cyber ranges are a more recent development to provide hands-on skill training. These ranges, often virtual, provide a safe and accessible environment to improve practical skills and experience through hands-on application. They provide a training environment to identify threats, apply countermeasures, and secure data from risks separately from the organization's actual network. More and more academic programs utilize cyber ranges due to the perceived benefit of integrating them into their cybersecurity-related programs. Academic cyber ranges offer virtualized environments that support cybersecurity educators' needs to provide students with a safe, separated, and engaging environment. The purpose of my research has two components: 1) to understand who the educators are using academic-facing cyber ranges and how they are using them to support their cybersecurity education efforts, and 2) to understand how cybersecurity educators and students are motivated by using them. Specifically, my research is comprised of three manuscripts: (1) a mixed-method exploratory study of who are the educators using cyber ranges for cybersecurity education and how they are using them to create significant cybersecurity learning experiences, (2) a mixed-method study exploring the motivation of educators using a cyber range for cybersecurity education, and (3) a mixed-method study exploring student motivation participating in cybersecurity CTF competitions. The three manuscripts contribute to understanding cyber ranges in cybersecurity education. The results from my research provided insight from the users of these cyber ranges, cybersecurity educators and students. Results from my first manuscript suggested that high school cybersecurity educators are the primary users. These educators have less formal cybersecurity education and experience compared to cybersecurity educators in higher education. The data also showed that cybersecurity educators primarily used cyber ranges for teaching and learning to meet learning goals and objectives. Results from my second manuscript suggested that educators were motivated mainly by the importance of using a cyber range for cybersecurity education and for the interest-enjoyment their students experience from cyber range usage. Educators found using the cyber range made their class more engaging and relevant to their students.These educators were also confident they could use a cyber range and learn how to use it. However, those without prior experience in cybersecurity or previous experience using a cyber range shared they needed instructor-facing resources, professional development opportunities, and time to learn. Results from my third manuscript suggested that students were motivated by the importance of participating in a cybersecurity CTF competition. Many reported that participating was useful for developing professional skills and readiness. Although CTF competitions were considered difficult and stressful, students did not consider the difficulty pejorative. Many shared that challenging CTFs contributed towards the enjoyment of participating, making them a rewarding and worthwhile experience. However, students also shared that academic and team support contributed towards their confidence in competing. In contrast, those who did not report confidence, stated they lacked a team strategy or support from their academic institution. Additionally, they did not know what to expect to prepare before the competition event. Overall, the results of this dissertation highlight the importance of prior preparation for educators and student CTF participants. For educators, this prior preparation includes curriculum supporting resources such as content mapping to learning objectives and professional development opportunities that do not assume any prior knowledge or experience. For students, prior preparation includes understanding what to expect and recommendations for academic and team support.
Exploring Engineering Faculty Experiences and Networks in Integrating Ethics Education: Insights from a University-Wide Curriculum Reform
Snyder, Samuel Aaron (Virginia Tech, 2024-06-04)
In today's globalized and technology-driven landscape, engineers wield unprecedented influence. As a response to calls from engineering accrediting and professional organizations, engineering educators have begun to further emphasize the importance of ethical decision-making within the curriculum. However, despite numerous attempts to integrate ethics, there remains a lack of consensus on effective strategies, particularly for larger-scale initiatives. This research, utilizing Lattuca and Stark's (2009) Academic Plan model, explores the Pathways curriculum reform at Virginia Tech, a university-wide initiative aimed at integrating intercultural awareness and ethical reasoning across general education courses. Through a case study methodology, semi-structured interviews were conducted with 12 faculty in the College of Engineering. Participants shared insights on the barriers encountered, resources utilized, and perceptions of ethical culture within their various academic environments. Additionally, participants described their network interactions within and beyond the curriculum reform initiative. Findings suggest faculty leverage existing networks during curriculum reform, with identified barriers categorized as influence-driven and resource-driven. Integrating these insights into the Academic Plan model offers a nuanced, process-oriented understanding of curricular change.
Exploring Instructors' Classroom Test Beliefs and Behaviors in Fundamental Engineering Courses: A Qualitative Multi-Case Study
Chew, Kai Jun (Virginia Tech, 2022-08-23)
Classroom tests are a common and default form of assessments in concept-heavy, fundamental engineering courses. Tests have benefits to learning, such as the testing effect that helps with the retrieval of knowledge, but there are also disadvantages, like discouraging deep learning approaches and decreasing motivation to learn, that warrant examining and questioning why tests are common, which engineering education literature lacks. Furthermore, the advancement of assessment research has led to alternative assessments that can diversify types of assessments and promote intentionality in test usage in these courses, supporting the need for scholarship on understanding test usage. My research began to address this by studying fundamental engineering course instructors' test beliefs and behaviors because engineering instructors have shown to have autonomy in making course decisions and barriers to adopting scholarship-based assessment practices among these engineering instructors persist. This dissertation study, grounded in the Situated Expectancy Value Theory (SEVT), explored, uncovered, and articulated seven fundamental engineering course instructors' test beliefs and behaviors from mechanical engineering and engineering science departments in a public, land-grant, Research 1 institution. Leveraging the case study research methodology from a pragmatic perspective, my multi-case study, with each participant being defined as a case, answered an overarching research question and five sub-research questions that yielded findings on five test aspects: test usage, design, administration, cheating, and fairness. Eight collected data sources in the form of qualitative interviews, course, department, and institution documents became the database to answer the questions. Analyses of these data involved coding and content analysis, and subsequent thematic analysis. The outcome of these analyses shaped the individual case profiles for cross-case analysis to understand belief and behavior patterns at a higher level. My research has found three groups of test usage beliefs. These are enthusiastic test users, default test users, and skeptical test users. All participants featured tests heavily in their courses and justified with learning outcomes and some non-course-content factors like large class sizes for grading conveniences. However, those in default and skeptical test user groups also acknowledged some non-course-content factors, like inertia and peer pressure, that influenced their test usage beliefs and behaviors. All participants acknowledged some disadvantages with tests, but those who are skeptical with test usage presented stronger beliefs about test disadvantages, arguing for the need to move away from tests when necessary. Some participants also presented conflicting beliefs and behaviors regarding their test usage. My study has also found all participants using problem-solving questions, emphasizing the need to curb cheating especially during the Covid-19 pandemic, preferring in-person test administration, and defining test fairness with reasonable completion time and adequate content coverage. These findings contribute to addressing identified research gaps in the literature and have implications for future research on tests with assessment philosophies, classroom practices on diversifying assessments and intentional test usage, and future research on possible assessment roles in addressing systemic inequity in engineering.
Innovating the Study of Self-Regulated Learning: An Exploration through NLP, Generative AI, and LLMs
Gamieldien, Yasir (Virginia Tech, 2023-09-12)
This dissertation explores the use of natural language processing (NLP) and large language models (LLMs) to analyze student self-regulated learning (SRL) strategies in response to exam wrappers. Exam wrappers are structured reflection activities that prompt students to practice SRL after they get their graded exams back. The dissertation consists of three manuscripts that compare traditional qualitative analysis with NLP-assisted approaches using transformer-based models including GPT-3.5, a state-of-the-art LLM. The data set comprises 3,800 student responses from an engineering physics course. The first manuscript develops two NLP-assisted codebooks for identifying learning strategies related to SRL in exam wrapper responses and evaluates the agreement between them and traditional qualitative analysis. The second manuscript applies a novel NLP technique called zero-shot learning (ZSL) to classify student responses into the codes developed in the first manuscript and assesses the accuracy of this method by evaluating a subset of the full dataset. The third manuscript identifies the distribution and differences of learning strategies and SRL constructs among students of different exam performance profiles using the results from the second manuscript. The dissertation demonstrates the potential of NLP and LLMs to enhance qualitative research by providing scalable, robust, and efficient methods for analyzing large corpora of textual data. The dissertation also contributes to the understanding of SRL in engineering education by revealing the common learning strategies, impediments, and SRL constructs that students report they use while preparing for exams in a first-year engineering physics course. The dissertation suggests implications, limitations, and directions for future research on NLP, LLMs, and SRL.
A Novel Method for Thematically Analyzing Student Responses to Open-ended Case Scenarios
Shakir, Umair (Virginia Tech, 2023-12-06)
My dissertation is about how engineering educators can use natural language processing (NLP) in implementing open-ended assessments in undergraduate engineering degree programs. Engineering students need to develop an ability to exercise judgment about better and worse outcomes of their decisions. One important consideration for improving engineering students' judgment involves creating sound educational assessments. Currently, engineering educators face a trad-off in selecting between open- and closed-ended assessments. Closed-ended assessments are easy to administer and score but are limited in what they measure given students are required, in many instances, to choose from a priori list. Conversely, open-ended assessments allow students to write their answers in any way they choose in their own words. However, open-ended assessments are likely to take more personal hours and lack consistency for both inter-grader and intra-grader grading. The solution to this challenge is the use of NLP. The working principles of the existing NLP models is the tallying of words, keyword matching, or syntactic similarity of words, which have often proved too brittle in capturing the language diversity that students could write. Therefore, the problem that motivated the present study is how to assess student responses based on underlying concepts and meanings instead of morphological characteristics or grammatical structure in sentences. Some of this problem can be addressed by developing NLP-assisted grading tools based on transformer-based large language models (TLLMs) such as BERT, MPNet, GPT-4. This is because TLLMs are trained on billions of words and have billions of parameters, thereby providing capacity to capture richer semantic representations of input text. Given the availability of TLLMs in the last five years, there is a significant lack of research related to integrating TLLMs in the assessment of open-ended engineering case studies. My dissertation study aims to fill this research gap. I developed and evaluated four NLP approaches based on TLLMs for thematic analysis of student responses to eight question prompts of engineering ethics and systems thinking case scenarios. The study's research design comprised the following steps. First, I developed an example bank for each question prompt with two procedures: (a) human-in-the-loop natural language processing (HILNLP) and (b) traditional qualitative coding. Second, I assigned labels using the example banks to unlabeled student responses with the two NLP techniques: (i) k-Nearest Neighbors (kNN), and (ii) Zero-Shot Classification (ZSC). Further, I utilized the following configurations of these NLP techniques: (i) kNN (when k=1), (ii) kNN (when k=3), (iii) ZSC (multi-labels=false), and (iv) ZSC (multi-labels=true). The kNN approach took input of both sentences and their labels from the example banks. On the other hand, the ZSC approach only took input of labels from the example bank. Third, I read each sentence or phrase along with the model's suggested label(s) to evaluate whether the assigned label represented the idea described in the sentence and assigned the following numerical ratings: accurate (1), neutral (0), and inaccurate (-1). Lastly, I used those numerical evaluation ratings to calculate accuracy of the NLP approaches. The results of my study showed moderate accuracy in thematically analyzing students' open-ended responses to two different engineering case scenarios. This is because no single method among the four NLP methods performed consistently better than the other methods across all question prompts. The highest accuracy rate varied between 53% and 92%, depending upon the question prompts and NLP methods. Despite these mixed results, this study accomplishes multiple goals. My dissertation demonstrates to community members that TLLMs have potential for positive impacts on improving classroom practices in engineering education. In doing so, my dissertation study takes up one aspect of instructional design: assessment of students' learning outcomes in engineering ethics and systems thinking skills. Further, my study derived important implications for practice in engineering education. First, I gave important lessons and guidelines for educators interested in incorporating NLP into their educational assessment. Second, the open-source code is uploaded to a GitHub repository, thereby making it more accessible to a larger group of users. Third, I gave suggestions for qualitative researchers on conducting NLP-assisted qualitative analysis of textual data. Overall, my study introduced state-of-the-art TLLM-based NLP approaches to a research field where it holds potential yet remains underutilized. This study can encourage engineering education researchers to utilize these NLP methods that may be helpful in analyzing the vast textual data generated in engineering education, thereby reducing the number of missed opportunities to glean information for actors and agents in engineering education.
Relationship Building and Pre-Disaster Planning: Effective Strategies for Rural Resilience Following the 2016 West Virginia Floods
Poling, Kase Scott (Virginia Tech, 2023-12-21)
Extreme weather events are becoming more commonplace in the United States and across the globe. Infrastructure cannot be built to completely withstand damage from these extreme events, thus communities must prepare themselves to recover quickly and efficiently to limit disruption to community members' livelihoods. Non-coastal, rural communities in the Appalachian region are affected by many of the same barriers to recovery as more populated suburban and urban communities, however, they can also face unique circumstances due to heightened vulnerability caused by depressed socioeconomics, reduced access to public services, and nominal capabilities of small, rural town governments. Rural communities face challenges to disaster recovery, but they can also benefit from increased social capital and population homogeneity that reduces cultural and language barriers and has the potential to improve coordination and collaboration. Financial and coordination barriers, such as the late or slow allocation of funding and limited management capacity of local governments during disaster recovery, are prevalent in rural Appalachian communities. Legal and socio-cultural barriers to rural disaster recovery include historical development patterns in and around floodplains, higher percentages of vulnerable populations, and difficulty navigating the federal disaster aid application process. Collaborative planning efforts and capacity building through the cultivation of relationships among disaster recovery stakeholders are necessary to provide an efficient and effective recovery. Additional funding, and more timely funding, are often proposed to solve a variety of challenges, but money alone will not be enough to overcome many prominent barriers. By adopting planning and cross-sector collaborative practices, local governments can better leverage available resources and facilitate the recovery process for the benefit of the affected communities. The 2016 West Virginia floods served as a case study and recovery strategies used following this event provide lessons learned to mitigate disaster recovery barriers in the future. Semi-structured interviews were conducted with 25 people from 15 organizations ranging from state cabinet secretaries and mayors to engineers and nonprofit workers. Interviews were transcribed and coded using qualitative data analysis software. Site visits accompanied interviews and thematic content analysis was used to analyze interview transcripts and supporting documentation. Codes were validated by an independent, third-party coder.
Tasks, Skills, and Jobs in the Green Economy
Cheng, Yang (Virginia Tech, 2024-05-29)
The Inflation Reduction Act has allocated over $369 billion to expedite the transition from fossil fuels to renewable energy. Along with these incentives, the funds support job training initiatives, like the recently introduced American Climate Corps. The transition to new energy forms will result in structural changes in the labor market and the demand for new and emerging skills, tasks, and jobs. A challenge, however, is that there are no existing definitions of what constitutes green jobs and skills, and thus, no clear consensus on the training workers will need for these jobs. This dissertation employs a data-driven approach using the Occupational Information Network to define and characterize green tasks, skills, and jobs. Using Natural Language Processing, we develop a method to quantify the "greenness'' of tasks and occupations. Utilizing this index, we explore the significant role of green skills during economic transitions. Our findings offer a comprehensive roadmap for understanding the evolution of green jobs and skills over the next decade. This dissertation comprises three chapters analyzing the tasks, skills, and jobs in the green economy. The first chapter investigates what constitutes green jobs and their characteristics. We construct "Task Greenness Scores" and "Occupational Green Potential" indices using Natural Language Processing and machine learning techniques to assess the greenness of tasks and overall occupations. Clustering methods categorize occupations based on task attributes -- green potential, frequency, importance, and relevance, identifying five distinct groups. This classification reveals significant variability in job greenness; although many jobs incorporate green tasks, only 113 occupations are definitively categorized as green. These are further divided into "High Green Intensity-Task Focus" and "High Green Intensity-Use Focus" groups, with the latter typically requiring less formal education and emphasizing manual skills over analytical or interactive skills. Our analysis also indicates a modest overall unconditional green wage premium of 3% for 2019 and 2020. The second chapter delineates green skills and maps their prevalence across the U.S., focusing on coal-mining communities in Appalachia. We sort a variety of skills into categories reflecting task and skill differences between green and non-green occupations, identified through O*NET. Principal Component Analysis helps categorize these into broader green skill groups such as "Technical Skills", "Management Skills", "Science Knowledge", and "Integrated Knowledge". The prevalence of green skills is notable in production-related occupations, suggesting essential technical expertise for the green economy. Interestingly, sectors traditionally viewed as energy-intensive also show a foundation conducive to green practices. Our findings highlight the necessity of tailored training programs that cater to diverse educational backgrounds, particularly emphasizing the lack of green skills in Appalachian regions, which may exacerbate inequalities during the economic transition. The third chapter examines the mediating role of green skills in local labor markets amidst the transition to a sustainable and energy-efficient economy. This chapter informs policy debates on large-scale green fiscal plans of the 2009 American Recovery and Reinvestment Act. We discover that regions well-prepared for environmental regulations or new energy development benefit from a robust stock of green skills. However, our analysis suggests that green ARRA investments are negatively correlated with wages and job creation, contrasting with positive correlations found in non-green ARRA investments. This chapter concludes that green skills significantly influence labor market outcomes, particularly in the manufacturing sector, and highlights the spillover effects of green stimulus on neighboring labor markets.
Through the Lenses of Pedagogical Content Knowledge and Instructor Beliefs: Understanding Engineering Instructors' Enacted Practice
Espera Jr, Alejandro Hanginon (Virginia Tech, 2022-04-28)
Education research has investigated teaching practices and uncovered a potential disconnect between instructors' knowledge and beliefs about teaching and their actual teaching practices. While experts of the subject matter, their understanding of teaching and their awareness of their own teaching capability significantly impact their enacted practices. However, there is a dearth of research in engineering on this aspect, particularly in electrical engineering (EE) education. EE as an applied science comprises many abstract concepts among other engineering disciplines that require strategic teaching practices to facilitate student learning. The intangible nature of these concepts, such as the foundational circuits concepts, raises the likelihood of acquiring issues in teaching among engineering instructors that can impact the construction of contextual knowledge and skills among engineering students. In this qualitative case study, the primary aim was to study the Electrical and Computer Engineering (ECE) faculty who taught the first and second-year ECE courses at Virginia Tech. Answers were sought through the overarching research question how do engineering instructors' knowledge and beliefs about engineering teaching influence their enacted practice in teaching introductory electric circuits? using a synthesized framework of pedagogical content knowledge (PCK), instructor beliefs and Watkins and Marsick's Continuous Learning Model (WMCLM). The significant findings from the analysis of interviews, class recordings, and Canvas course materials suggested that the ECE instructors' formed PCK and held beliefs can have an affirmative influence on enacted practice, meaning, their knowledge and beliefs about engineering teaching reinforced their enacted practice. This influence was apparent in their various student-centric approaches to contextualizing the ECE concepts using their combined experiences. In contrast, constructive influence captured the potential causes of "disconnect" between their formed "knowledge and beliefs" and their enacted practice. This influence was rooted in how the abstract fundamental ECE concepts, in most cases, required contexts outside of the instructors' core experiences. The attempt to use multiple strategies to attain the course goals had created oversight tendencies on their implementation magnified by the online and hybrid modality, especially with the team-teaching design of the base ECE courses. Such relevant issues needed time-constraining solutions from the course instructor to the administrative level. This work can further advance the instructional methods in EE education after understanding the influences of instructors' beliefs and knowledge on their enacted practices to teach foundational concepts in ECE. More broadly, this work will have implications for educators, curriculum designers, and researchers who seek to improve engineering instruction and address the current issues in teaching engineering. The outcomes provide research opportunities to interrogate how we can use instructional practices to design methodologies that can elucidate and solve issues on instructors' enacted practices constructively. More importantly, the results of this study can be utilized to design professional development programs for engineering teaching faculty by having a framework to continuously examine instructors' beliefs and knowledge to support their teaching practice.
Understanding Faculty Decision-Making in Engineering Education for Sustainable Development
Menon, Maya (Virginia Tech, 2023-09-05)
Engineering education for sustainable development (EESD) has emerged as a significant focus since the early 1990s, driven by the broader integration of sustainable development (SD) across education. SD has gained global attention and support from governments, businesses, and organizations. Still, education for sustainable development is emergent in engineering, and varies globally. Scandinavian countries, for example, have made significant progress in EESD with research and growth in courses and curricula, while the United States has seen more localized efforts. Prior research on EESD has focused heavily on course content and student learning, with far less attention to faculty attitudes and experiences. To advance global integration efforts, this study provides a deeper understanding of faculty engagement with EESD. Drawing on Lattuca and Pollard's (2016) model of faculty decision-making to engage in curricular change, this study compares the perspectives of faculty at two universities, one in the U.S. and one in Denmark, to explore the influences that shape engineering faculty choices to engage in EESD. To operationalize EESD, the study focuses on faculty who incorporate the U.N.'s Sustainable Development Goals (SDGs) in their courses. Denmark and the U.S. were selected because of the wide divergence in national policies and practices relative to SD. The two institutions, however, are similar in engineering program size, research orientation (both very high research), and scope of engineering programs. The research used a case study approach and included interviews with five to seven engineering faculty and two to three key informants at each site, along with available texts such as university mission statements, program descriptions, course syllabi provided by interviewees, and national policies or declarations. Lattuca and Pollard's model posits three levels of influence: external (outside the institution), internal (within the institution and the department), and individual (within the person) Findings suggest that all three categories of influence are present in each case, but the salience of each category, the specific factors within each category, and the interactions across categories differ markedly. Where the Denmark case had a more consistent alignment across the three levels of influence, with a largely top-down direction of influence, engagement in EESD in the US case was largely an individual, bottom-up phenomenon with some alignment to, but limited drivers from the external and internal levels. This study captures the importance of strong external and internal influences in shaping faculty engagement in EESD and underscores the limitations of relying solely on individual influences. The findings highlight the role of national policies and cultural norms in creating a supportive environment for faculty to integrate sustainability into their teaching. Where external influences are limited, institutions need to actively align their vision, culture, and resources with the principles of sustainable development to foster a widespread and consistent practice of EESD. While individual faculty have been shown to act as change agents in the absence of strong external and internal influences, their efforts alone are limited in their impact on the practice of EESD.
Understanding STEM Students' Perceptions of Support
Taimoory, Hamidreza (Virginia Tech, 2024-09-30)
Efforts to increase enrollment in engineering and enhance the participation and proficiency of engineers have long been priorities, as emphasized by the National Academy of Science and the National Academy of Engineering. This imperative underscores the need for both a greater quantity and a higher caliber of engineers—colleges and universities are charged with helping students successfully progress through their programs to earn a degree. Existing research predominantly focuses on specific academic interventions or discrete support factors in attempts to understand how to best support academic success. My work, on the other hand, takes a comprehensive examination that quantifies students' perceptions of support across a wide range of sources and explores the relationship between these perceptions and student engagement in different activities. Utilizing student support data collected from undergraduate students in Engineering, Science, and Mathematics at nine institutions during the spring of 2019, the study embarks on a multifaceted exploration that unfolds in three interconnected parts. The first part employs multiple comparison analyses to unveil distinct differences in perceptions of support among different student subpopulations. The second part delves into the relational dynamics between support perceptions and students' participation in co-curricular activities using binomial regression. The third part, employing multiple linear regression, scrutinizes this relationship from a reverse perspective, acknowledging the potential bidirectional nature by examining how the level of student engagement in a range of co-curricular activities relates to their perceptions of support. The findings continue to establish further validity evidence for the newly developed STEM-SPSI tool. It also has the potential to offer valuable insights for educators, administrators, and policymakers intent on enhancing the inclusivity and efficacy of their programs. This study's potential implications underscore the importance of targeted support factors in fostering a more enriching and equitable co-curricular experience for undergraduate students. Embracing a more integrated perspective, this research contributes to evidence-based practices aimed at fostering the success and retention of students in STEM fields.

Browsing by Author "Katz, Andrew Scott"

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