About

Sara Lego is a faculty member in Penn State's Department of Aerospace Engineering, which has a distinguished record of research excellence and scholarship. Her research spans traditional disciplines associated with aeronautics and astronautics, with particular strengths in rotorcraft and aero-acoustics. The department is also expanding into new areas driven by increasing computational power for design, analysis, on-board autonomy, sustainable aviation, and space systems. The faculty, including Sara Lego, are involved in leading research efforts such as the Vertical Lift and Rotorcraft Center of Excellence and participate in large, multidisciplinary projects with significant funding. Many faculty members, including those like Sara Lego, have received prestigious awards and honors, such as NSF CAREER, DoD Young Investigator awards, and society fellowships, reflecting their contributions to aerospace research and education.

Research topics

• Medical education
• Medicine
• Psychology
• Engineering
• Political Science
• Engineering management
• Computer Science
• Engineering ethics
• Marketing
• Management
• Mechanical engineering
• Mathematics education
• Business

Selected publications

• Design, Build, Code, Fly: Aerospace Autonomy Capstone at the Pennsylvania State University

  2025-01-03

  article1st authorCorresponding

  This paper summarizes the curriculum design and development, as well as lessons learned, of one of the senior-level undergraduate capstone courses at the Department of Aerospace Engineering, Pennsylvania State University, called "Autonomy Capstone". This effort started in the Fall of 2019 as a special topic focusing on autonomous aerial systems in undergraduate aerospace education, then was approved to integrate into the department curriculum in the Fall of 2024. The ultimate goal is to equip undergraduate students with knowledge of advanced autonomy algorithms in aerospace, including sensing, state estimation/navigation, planning/guidance, and control. Due to their importance in aerospace, automotive, and embedded system industries, the course also aims to incorporate hands-on, low-level coding and simulation skills into the traditional design-build-fly (DBF) framework, termed design-build-code-fly (DBCF).

  PublisherDOI

• Assessing Student Perceptions of Peer Review Methods’ Efficacy in a Team-Based, Senior Undergraduate Capstone Course Setting

  2024

  1st authorCorresponding
  • Computer Science
  • Medical education
  • Psychology

  Within Penn State, the Aerospace Engineering department has historically used the Comprehensive Assessment of Team Member Effectiveness (CATME) online tool hosted by Purdue University to conduct its peer reviews within four of its capstone courses, which are yearlong offerings running fall to spring.While the tool is research-backed and widely used within capstone courses across the country, recent feedback at Penn State has revealed a perception among students that the tool's "five teamwork dimensions" are overly complex, unclear, and do not allow students to accurately represent true team dynamics and individual behaviors when using the tool to generate peer review scores.In response to this feedback, the Aerospace Engineering capstone course instructors have developed a new peer review method called Participation and Professional Engineering Skills Assessments (PEPSA), which combines a Participation Factor (PF) approach with a simplified, custom peer review survey generated in Qualtrics that uses a Likert scale and measures the degree to which students agree or disagree with statements related to each team member's performance and professional skills demonstration.This paper describes both the new peer review tool as well as results from a study conducted in the 2022/2023 academic year to evaluate student perceptions of PEPSA against the prior CATME baseline using two identical study questionnaires.

  PublisherOA PDFDOI

• Work In Progress: Implementation of a Skills Based Approach to Diversity, Equity, and Inclusion in Senior Undergraduate Aerospace Capstones

  2024 · 1 citations

  1st authorCorresponding
  • Political Science
  • Engineering management
  • Medical education

  Abstract In 2019, the Accreditation Board for Engineering and Technology (ABET) updated their student outcome accreditation standards to specifically address team collaboration, leadership, and inclusivity. While Penn State's 2016-2020 University-wide Strategic Plan clearly highlights diversity as one of its core foundations, the College of Engineering 2020-2025 Strategic Plan reaffirmed and clarified this commitment by making one of its unit objectives the integration of ethics, inclusivity, and sustainability into undergraduate programs throughout the college. In the Aerospace Engineering Department, senior undergraduate capstone courses offer ideal conditions for exploring Diversity, Equity, and Inclusion (DEI) issues since these classes are team-based experiential learning environments intended to mirror the engineering workplace. While Penn State's year-long Aerospace Engineering capstone courses have historically included a unit on DEI presented at the beginning of the Fall semester, these concepts were introduced in a lecture-based format and embedded within the broader context of professional behavior and team dynamics. With the addition of 2-3 team peer review surveys throughout the Fall and Spring semesters to assess team communication, collaboration, and student perceptions of team productivity, this approach satisfies the ABET student outcome accreditation criteria. However, a wealth of research into DEI training over the last decade has indicated that lecture-based approaches are the least effective pedagogical method for ensuring concept retention, changes in empathetic thinking, and recognition of personal implicit biases. In addition, the majority of senior engineering undergraduates have limited experience navigating professional norms, team conflict, and diverse team environments. The combination of these factors created a capstone environment in which students were aware of DEI in the context of professional behavior, but lacked the deeper appreciation of DEI issues resulting from workplace/team culture and other barriers to STEM equity and inclusivity within teams. Furthermore, even when students recognized these issues, they were unfamiliar with methods to mitigate them. To bridge this knowledge gap, the Penn State Aerospace Engineering Department has implemented a skills-based approach to its DEI learning modules within all capstone courses. This approach combines a variety of pedagogical techniques including interactive video-based bystander training; self reflections on microaggressions and implicit bias; and in-class team exercises and discussions on the intersection of power dynamics, team interactions, and discrimination, as well as strengthening empathy though a recognition of societal privilege and economics factors. Throughout these trainings, activities, and discussions, an emphasis is placed on development of concrete actions that students can take within their current and future teams to promote an inclusive, collaborative, and psychologically safe environment for all members. As implementation of these active learning techniques to DEI concepts within the senior undergraduate aerospace capstones is a relatively new update to the curriculum, development of metrics to gauge effectiveness is ongoing. Planned assessment options include in-class and senior exit surveys, as well as CATME-based or customized evaluation models containing questions related to psychological safety, communication, collaboration, productivity, team climate, and team interdependence.

  PublisherOA PDFDOI

• The Penn state lunar lion: A university mission to explore the moon

  Acta Astronautica · 2013-11-22 · 3 citations

  article
  PublisherDOI

• Preference Construction, Sequential Decision Making, and Trade Space Exploration

  2013-08-04 · 25 citations

  article

  This paper develops and explores the interface between two related concepts in design decision making. First, design decision making is a process of simultaneously constructing one’s preferences while satisfying them. Second, design using computational models (e.g., simulation-based design and model-based design) is a sequential process that starts with low fidelity models for initial trades and progresses through models of increasing detail. Thus, decision making during design should be treated as a sequential decision process rather than as a single decision problem. This premise is supported by research from the domains of behavioral economics, psychology, judgment and decision making, neuroeconomics, marketing, and engineering design as reviewed herein. The premise is also substantiated by our own experience in conducting trade studies for numerous customers across engineering domains. The paper surveys the pertinent literature, presents supporting case studies and identifies use cases from our experiences, synthesizes a preliminary model of the sequential process, presents ongoing research in this area, and provides suggestions for future efforts.

  PublisherDOI

• Trade space exploration: New Visual Steering features

  2010-03-01 · 3 citations

  article1st authorCorresponding

  The Applied Research Laboratory at Penn State University has a long history of developing software tools to support decision-making within the conceptual stage of complex systems design. Previous research introduced a new approach to trade space exploration called Visual Steering. This approach combines exercising a design model and analyzing the results into a tightly coupled loop that lets decision makers rapidly explore the trade space in real time while simultaneously forming preferences so that the ¿best¿ design based on evolving preferences can be chosen. This paper expands upon previous work in Visual Steering by introducing new features that ARL has added to its ARL Trade Space Visualizer (ATSV) Exploration Engine, the interface software that facilitates the coupled loop between design and analysis critical for realizing the Visual Steering concept. Specifically, new wizards that facilitate easy linking between models and the ATSV Exploration Engine are described, and example models showing the wizards in use are presented.

  PublisherDOI

• Visual Steering Commands for Trade Space Exploration: User-Guided Sampling With Example

  Journal of Computing and Information Science in Engineering · 2009-11-02 · 106 citations

  article

  Recent advancements in computing power and speed provide opportunities to revolutionize trade space exploration, particularly for the design of complex systems such as automobiles, aircraft, and spacecraft. In this paper, we introduce three visual steering commands to support trade space exploration and demonstrate their use within a powerful data visualization tool that allows designers to explore multidimensional trade spaces using glyph, 1D and 2D histograms, 2D scatter, scatter matrix, and parallel coordinate plots, linked views, brushing, preference shading, and Pareto frontier display. In particular, we define three user-guided samplers that enable designers to explore (1) the entire design space, (2) near a point of interest, or (3) within a region of high preference. We illustrate these three samplers with a vehicle configuration model that evaluates the technical feasibility of new vehicle concepts. Future research is also discussed.

  PublisherDOI

• Visual Steering Commands for Trade Space Exploration: User-Guided Sampling With Example

  2007-01-01 · 25 citations

  article

  Recent advancements in computing power and speed provide opportunities to revolutionize trade space exploration, particularly for the design of complex systems such as automobiles, aircraft, and spacecraft. In this paper, we introduce three Visual Steering Commands to support trade space exploration and demonstrate their use within a powerful data visualization tool that allows designers to explore multidimensional trade spaces using glyph, 1-D and 2-D histogram, 2-D scatter, scatter matrix, and parallel coordinate plots; linked views; brushing; preference shading and Pareto frontier display. In particular, we define three user-guided samplers that enable designers to explore (1) the entire design space, (2) near a point of interest, or (3) within a region of high preference. We illustrate these three samplers with a vehicle configuration model that evaluates the technical feasibility of new vehicle concepts. Future research is also discussed.

  PublisherDOI

• Visual Steering and Trade Space Exploration

  2007-01-01 · 12 citations

  articleSenior author

  The assumptions at the beginning of a trade space exploration are that the decision makers have a model of some complex engineered system that relates design variables to performance and cost metrics, they know what the inputs and outputs to the model are, and they know they will be forming a preference over some subset of the inputs and outputs. What they do not know is the relationship between the inputs and outputs (in exact or an intuitive sense), the feasible range of inputs and outputs, the subset of inputs and outputs they will form their preference on, or the exact form of the preference. These assumptions probably form the least informative starting point for trades. To conduct the trade study the model is tied to an exploration engine, which initially randomly exercises the model, creating different system concepts. A user simultaneously visually explores the trade space in real time as it emerges using multi-dimensional data visualization tools and then visually steers further model runs to desired trade space regions of interest by specifying attractors in the trade space, such as desired inputs, outputs, preference functions, Pareto frontier. To ground the presentation, the paper uses a satellite design model, which relates design and performance variables to form a multi-dimensional trade space for satellite configurations. The trade space is discontinuous and complex, and presents a suitable test case.

  PublisherDOI

Frequent coauthors

• Gary Stump

  Applied Research (United States)

  8 shared

• Lorri Bennett

  4 shared

• Michael A. Yukish

  4 shared

• Mike Yukish

  Pennsylvania State University

  4 shared

• Timothy W. Simpson

  Centraal Bureau voor de Statistiek

  4 shared

• Simon W. Miller

  Pennsylvania State University

  2 shared

• Joseph Donndelinger

  Baylor School

  2 shared

• Cara Exten

  Pennsylvania State University

  1 shared

Labs

• Aerospace Engineering Research at Penn StatePI

Awards & honors

• AIAA Aero Acoustics Award (3)
• AIAA Sperry Award (2)
• AIAA Applied Aerodynamics Award
• Am Astronautical Society Brouwer Award
• AIAA de Florez Award in Flight Simulation