Lab Director | Dr. David Knight
The vision of the Virginia Tech Data Enlightened Educational Practice (DEEP) Lab is to serve as one of the world’s leading research shops for promoting a systems view of engineering education with an explicit mission to improve the efficiency, effectiveness, and inclusiveness of the field. Aligned with Virginia Tech’s Data Analytics and Decision Sciences Destination Area, the VT DEEP Lab uses large-scale quantitative data to diagnose problems, identify opportunities and solutions, and enact organizational change by connecting research to policy and practice. Adopting this macro-scale, systems perspective to inform organizational decision-making has helped our team serve as active organizational change agents through collaborative projects locally, nationally, and internationally.
David Knight is an Assistant Professor in the Department of Engineering Education at Virginia Tech and affiliate faculty member with the Higher Education Program, Center for Human-Computer Interaction, and Human-Centered Design Program. At Virginia Tech, Knight manages the VT DEEP Lab - Data Enlightened Educational Practice - which is comprised of a collaborative team of Engineering Education doctoral students who work in interdisciplinary ways across the university. The group's research focuses on student learning outcomes in undergraduate engineering, learning analytics approaches to improve educational practices and policies, interdisciplinary teaching and learning, organizational change in colleges and universities, and international issues in higher education. Knight also directs Virginia Tech's Rising Sophomore Abroad Program, which is a collaborative effort between Virginia Tech and North Carolina A&T that incorporates a semester-long, on-campus learning experience with an international component in Europe to help students develop an awareness of the global nature of engineering. Knight earned a Ph.D. in Higher Education from Penn State University, two Master's degrees (Environmental Sciences with a concentration in Atmospheric Sciences and Urban and Environmental Planning), and a bachelor's of science in Environmental Sciences from the University of Virginia. He also worked as a research assistant in the University of Michigan's Center for the Study of Higher and Postsecondary Education and as a postdoctoral fellow in Engineering Education in the University of Queensland's School of Civil Engineering in Brisbane, Australia. Knight currently serves as PI on the NSF project Understanding and diversifying transfer student pathways to engineering degrees and PI for the VT portion of the NSF project Collaborative research: Variation in the awarding and effectiveness of STEM graduate student funding across teaching and research assistantships, fellowships, and traineeships,
Dr. David Knight - Director
David Reeping - PhD Student
Timothy Kinoshita - PhD Candidate
Kirsten Davis - PhD Student
Liz Spingola - PhD Student
DEEP Lab Alumni
Dissertation: Learning Analylitics: Understanding First-year Engineering students through Connected Student Centered data
Affiliation: Assistant Professor and Director of the First-Year Engineering program at Youngstown State University
Dissertation: Investigating Shared Leadership in Undergraduate Capstone Design Project
Affiliation: Assistant Professor at the United States Military Academy
Dissertation: Preparing Students for Professional Work Environments Through University- Industry Partnerships: A Single Case Study of the Co-op Development Program
Dissertation: Understanding Transfer Student Pathways to Engineering Degrees: A Multi-Institutional Study Based in Texas
The Virginia Tech Network for Engineering Transfer Students (VT-NETS) is a collaborative effort between Virginia Tech, Virginia Western Community College, and Northern Virginia Community College. This S-STEM project will establish stronger networks between Virginia Tech and the Virginia Community College System to increase the success of engineering transfer students following the community college-to-bachelor's degree pathway. The total number of scholarships awarded across all three institutions is 336 over five years. Community colleges are cost-effective gateways to four-year universities for academically talented, low-income students. The creation of a strong partnership, including early and frequent interaction between the student and the four-year institution, will enhance the potential for successful student transfer and timely completion of a baccalaureate degree. VT-NETS creates this partnership and serves as a research-based model for future collaboration between community colleges and four-year institutions.
The goal of this project is to design, implement, and empirically test curricular and co-curricular activities that support the transfer of students following the community college-to-bachelor's degree pathway to an engineering degree. Aligned with the mission of the NSF S-STEM program, the research team will use an embedded case study approach organized around the transfer student capital framework to advance understanding of how various factors affect the success, retention, transfer, and graduation in engineering for low-income students. The results of this project will help educators develop new interventions and fine-tune current efforts (e.g., making them more sustainable, efficient, and effective) to add value to existing strategies. Such integration with current student support practices will more broadly increase the success of transfer students in engineering nationwide. VT-NETS will illuminate and prioritize the human, financial, and physical resources dedicated towards these efforts and will enhance the infrastructure at the partner institutions for supporting all transfer students in engineering.
This is a collaborative proposal among the National Society of Black Engineers (NSBE), Virginia Tech, and Purdue University, submitted to the Successful Project Expansion and Dissemination strand of the Innovative Technology Experiences for Students and Teachers (ITEST) program. It aims to expand the implementation of a NSBE-supported program, "Summer Engineering Experiences for Kids", from 14 sites in 2016, to 31 by 2019; from 3,825 3rd-5th grade African American, Hispanic, and female students in 2015, to cumulatively 27,000 across the nation over the three-year duration of the project. By 2019, a total of 42,000 students will have been impacted by the program since its inception in 2007. The project will advance efforts of the ITEST program to better understand and promote practices that increase students' motivations and capacities to pursue careers in the fields of science, technology, engineering, or mathematics (STEM) by engaging them in a summer program through hands-on, team-based engineering design projects led by collegiate mentor-teachers. The project will use "A World in Motion"--an engineering curriculum for elementary and middle school children developed by the Society of Automotive Engineers, in addition to other STEM curricula to be incorporated across sites. Participants will experience applied engineering and computer programming learning opportunities, including engineering principles and related mathematics and science concepts and practices through selected activities. While expanding the program, researchers in the partnership will investigate the contextual factors that facilitate or constrain its implementation in order to develop a prototype with a potential to be used in various learning environments. Thus, the overall hypothesis of the work will be that organizational contexts enable, inhibit, and shape the experiences that students have, and consequently influence their outcomes.
Researchers at the University of Texas at Austin and Virginia Polytechnic Institute and State University will conduct a mixed methods research project to better understand how various mechanisms of funding - fellowships, research assistantships, teaching assistantships, etc. - influence students' pursuit of doctorates in STEM and subsequent employment. The project will produce empirical evidence and a conceptual framework to inform the improvement of graduate student funding policies and interventions by addressing the differences in the types of funding that are offered to diverse student populations. The researchers will investigate the qualitative questions using national data from the Survey of Earned Doctorates (SED) and then use that data to inform questions for further investigation within the study sites for data collection via interviews with graduate students, administrators and faculty members across eight STEM disciplines and seven NSF-funded centers at eight institutions.
The researchers will use socialization theory to guide the research. Hypothesizing that funding mechanisms are important drivers of socialization, the researchers will investigate the following research questions:(1) How do graduate students? funding mechanisms vary across their incoming characteristics (i.e. demographics and bachelor's or master's institutional type, location, or affiliation) and STEM discipline? (2) What is the relationship between graduate students' funding mechanisms and their post-doctoral outcomes? (3) How does the relationship between graduate students' funding mechanisms and their post-doctoral outcomes vary across their incoming characteristic and STEM discipline? (4) What do STEM graduate students, faculty members, and administrators perceive to be the benefits and drawbacks of various graduate student funding mechanisms? How does each group make decisions about offering or accepting offers of different funding mechanisms?(5) How does funding mechanism impact STEM graduate students? experiences, socialization, identity formation, and other factors previously shown to contribute to overall success? The analysis will provide insight about the difference socialization opportunities may have for certain groups of students but not others. In addition, the research results will inform interventions for broadening participation in STEM.
The project is supported by the ECR program that emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce development. ECR supports the accumulation of robust evidence to inform efforts to understand, build theory to explain, and suggest intervention and innovations to address persistent challenges in STEM interest, education, learning and participation.
This IRES program will offer water engineering research experiences to civil and environmental engineering students who are making the transition from undergraduate-to-graduate study. Participants will conduct research within one of the leading water engineering units in the world, in some of the finest labs globally, and within extremely complex environments. They will tackle one of three environmental fluid mechanics project areas using field measurements, physical modeling, and numerical methods: 1) Coastal hazard mitigation ecosystem services; 2) Contaminant remediation; and 3) River bed destruction. Each of these areas connect to ongoing research at the University of Queensland sponsored by major government, nonprofit, and industry agencies.
As the strain on water resources and ecosystems intensifies, it is becoming increasingly important to educate engineers to be ready to face complex issues related to water monitoring and management that stretch across national boundaries. The field of water engineering requires a broader educational approach beyond traditional curricula, as today's water engineers face challenging and interdisciplinary issues that combine concepts and methods beyond existing theories and data and instead require a research focus. In addition to the water engineering research component, this IRES program will make important contributions to water engineering education more broadly, as it will produce research focused on how to enhance the education of water engineers and how and why students develop in these kinds of international research experiences.
This mixed methods research is developing a clearer understanding of transfer student pathways as a means to increase engineering degree production and broaden participation in engineering careers, especially for Hispanic students. The study sites are 4 of the top 10 producers of U.S. Hispanic engineers: The University of Texas at El Paso, Texas A&M University, The University of Texas at Austin, and The University of Texas-Pan American. The investigators are surveying 5,200 students in 7 cohorts who transferred to 4-year institutions. Staff at the 4 institutions are matching survey responses to GPAs and engineering degree attainment so that statistical models can link educational experiences to outcomes. The team is also interviewing a sample of 40 engineering transfer students (50% Hispanic) about their transfer experiences.
Hispanics continue to be an untapped pool of prospective STEM talent in United States. Since 2005, Hispanics have exceeded more than 20 percent of students enrolled in the K-12 education system, yet they earned only 10 percent of the engineering degrees awarded in 2007. The state of Texas has uniquely seen rapid economic (GDP) and population growth in the past few years, coupled with a high minority population, making it an important setting for studying transfer student pathways and ultimately broadening participation in engineering. By partnering with the top 4 producers of Hispanic engineers in Texas and 4 of their feeder community colleges (Austin Community College, Blinn College, El Paso Community College, and South Texas College), this project has the potential to dramatically increase the numbers of both Hispanic and non-Hispanic students earning engineering degrees through transfer mechanisms. Project advisory board members have strong professional networks for disseminating the findings to policymakers and educational practitioners who can put the findings into action.
A diverse and highly skilled engineering workforce plays a critical role in maintaining economic competitiveness and protecting national security. To achieve these aims, engineering programs in higher education must guarantee that curricula are both rigorous and equitable. As demand for engineering majors increases, so too do section sizes for foundational engineering courses. There is growing evidence that such courses represent significant barriers to student success and that the penalties associated with large classes can disproportionately affect women and underrepresented groups. Further, these educational environments make it challenging to implement evidence-based teaching practices known to be better for student learning. This project will build a learning organization ecosystem -- a grassroots effort involving engagement between faculty and departmental and institutional support structures to collaboratively identify problems and continuously, systematically improve the quality and equitability of the engineering curricula. During this project, sixteen instructors responsible for teaching approximately 4800 undergraduate engineering students in large foundational courses will be impacted. Beyond the instructors and the students directly impacted, research findings and project outcomes will be shared broadly so that other faculty and administrators might similarly improve their educational enterprise.
This project responds to national calls for undergraduate engineering to become more data-driven by exploring how existing, diverse data sources can be leveraged to enhance educational environments. Early efforts will focus on creating intelligent feedback loops, robust streams of existing institutional data (e.g., historical transcript data, student evaluations), existing instructor-level data (e.g., past exams), and newly collected data (e.g., surveys about how students spend time pre/post high-stakes tests). Such data sources will be triangulated and analyzed in a way that can be used by the instructors and the research team. Summer workshops will also be conducted to engage faculty and administrators in a participatory design process: (1) to build individual instructor action plans and (2) to construct an institutional change action plan collectively. Research efforts center at the intersection of learning analytics and faculty change to inform how others might productively leverage institutional data to improve the STEM undergraduate education system. The research team consists of educational researchers, engineering faculty, and administrative leaders from the college of engineering, institutional effectiveness, and learning sciences. Thus, the team is well-poised to not only lead this effort programmatically and from a research perspective, but also institutionalize project-developed strategies and outcomes.
Leveraging Data to Create Personalized Learning Environments. Knight, D.B. (PI). $19,950 over one year from 4-VA, Technology-enhanced Learning and Online Strategies, Virginia Tech. 2015–2016, awarded December 2014.
Exploring Engagement and Learner Agency in Large Undergraduate Mechanics Courses. Grohs, J. (PI), Knight, D.B. (Co-PI). $23,000 over one year from 4-VA, Technology-enhanced Learning and Online Strategies, Virginia Tech. 2015–2016, awarded December 2014.
Data-Illustrated Analytics for a Learning Engagement Dashboard promoting Interaction (DIALED-IN). Knight, D.B., & Abel, T. (Co-PIs). $18,793 over one year from Institute for Creativity, Arts, and Technology, Virginia Tech, 2014 – 2015, awarded May 2014.
Leveraging Data to Create Personalized Learning Environments: Uncovering and visualizing data streams for an engaging dashboard. Knight, D.B., & Abel, T. (Co-PIs). $6,060 over one summer from Center for Human-Computer Interaction, Virginia Tech, 2014, awarded May 2014.
Knight, D.B., & Novoselich, B.J. (2017). Curricular and co-curricular influences on undergraduate engineering student leadership. Journal of Engineering Education, 106(1), 44-70.
Knight, D.B., Brozina, C., & Novoselich, B.J. (2016). An investigation of first-year engineering student and instructor perspectives of learning analytics approaches. Journal of Learning Analytics, 3(3).
Ogilvie, A., Knight, D.B., Borrego, M., Nava, P., Fuentes, A., & Taylor, V. (2017, June). Understanding and diversifying transfer student pathways to engineering degrees: A summary of project findings. Proceedings of the 124th Annual Conference of the American Society for Engineering Education, Columbus, OH.
Young, G., & Knight, D.B. (2016, February). Reflections of engineering professionals: Relating senior level skills to current employment. Proceedings of the 2016 Conference for Industry and Education Collaboration, Austin, TX.
Knight, D.B., Davis, K.A., Kinoshita, T.J., Soledad, M., & Grohs, J.R. (2017, June). Assessing students’ global and contextual competencies: Three categories of methods used to assess a program with coursework and international modules. Proceedings of the 124th Annual Conference of the American Society for Engineering Education, Columbus, OH.
For more information about the VT DEEP Lab, email David Knight.