skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Online Model-based Systems Engineering (MBSE) Bootcamp: A Report on Two Day Workforce Development Workshop
Academia or workforce development workshops can both increase the plausibility of a streamlined transition from a document-centric approach to MBSE frameworks, and aid the integration of Model-Based Systems Engineering (MBSE) within the current industry and the challenges faced, introducing MBSE concepts, tools, and languages. This paper reports on an online model-based system engineering Bootcamp conducted in collaboration with The University of Texas Rio Grande Valley and The University of Texas at El Paso. The importance of MBSE is emphasized throughout the online Bootcamp to a diverse group of audience i.e., students, faculty, and industry professionals unfamiliar with systems engineering. A set of predefined questions through pre and post Bootcamp surveys aided in determining the perceptions of MBSE and the effectiveness of the Bootcamp in increasing the knowledge of MBSE amongst participants. A positive knowledge gain was observed on the importance of systems modeling and MBSE across students, faculty, and industry personnel participants indicating the effectiveness of the online Bootcamp. A set of open-ended questions were targeted specifically for industry professionals from manufacturing, aerospace, healthcare, transportation, and software domains attending the Bootcamp for capturing the perceived challenges and obstacles according to them for implementing Model-Based Systems Engineering in their organizations.  more » « less
Award ID(s):
1952634
PAR ID:
10330129
Author(s) / Creator(s):
; ; ; ; ;
Date Published:
Journal Name:
2022 IEEE International Systems Conference (SysCon)
Page Range / eLocation ID:
1 to 6
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; (, Systems Engineering)
    Abstract Model‐based systems engineering (MBSE) is rapidly gaining popularity among U.S. industries. Though industry practitioners and academic researchers have identified several advantages in transitioning to MBSE, several adoption challenges of MBSE in industries, such as insufficient tool knowledge, lack of skilled personnel, and resistance in organizations toward a shift to MBSE, are observed. Attesting to the challenges in industry adoption of MBSE, a previous research study by the authors characterized the adoption challenges as tools‐based, knowledge‐based, cultural, political, and cost‐related, and customer understanding and acceptance of MBSE practices. This study is motivated to explore further and address the challenge of low MBSE tool knowledge and lack of skilled personnel with MBSE knowledge for industry adoption. This paper presents a two‐phased research approach framed by an overarching question of the extent to which the MBSE academic curriculum is aligned with industry workforce requirements. In Phase 1 of the study, we survey industry professionals from Defense, Aerospace, Automotive, and other industry clusters to identify MBSE tools, languages, and concepts preferred by industry professionals in a candidate for hire. This is followed by Phase 2 of the survey targeted at academic institutions with Systems and MBSE programs to analyze the extent to which MBSE curricula reflect industry workforce hiring requirements. Further, we also identify the challenges reported in academic institutions in training the Workforce on MBSE. The contributions of this paper are two‐fold: providing a pathway for academic institutions to align their curricula to MBSE industry workforce requirements and triggering discussion in the broader MBSE community to identify strategies for addressing MBSE adoption challenges and training future model‐based systems engineers. 
    more » « less
  2. ; ; ; (, 2022 IEEE International Systems Conference (SysCon))
    Model-Based Systems Engineering (MBSE) supports the development of complex systems through capturing, communicating, and managing system specifications with an emphasis on the use of modeling languages, tools, and methods. It is a well-known fact that varying levels of effort are required to implement MBSE in industries based on the complexity of the systems a given industry is associated with. This paper shares the results of a survey to industry professionals from Defense, Aerospace, Automotive, Consultancy, Software, and IT industry clusters. The research goal is to understand the current state of perception on what MBSE is and the use of MBSE among different industry clusters. The survey analysis includes a comparison of how MBSE is defined, advantages on the use of MBSE, project types, specific life cycle stage when MBSE is applied, and adoption challenges, as reported by the survey participants. The researchers also aim to trigger discussions in the MBSE community for identifying strategies to address MBSE related challenges tailored to a specific industry type. 
    more » « less
  3. ; ; ; (, Systems)
    Model-based systems engineering (MBSE) is being rapidly adopted in U.S. industries across various sectors. While practitioners and academics recognize many benefits of adopting MBSE, industries also report challenges such as limited tool expertise and a shortage of skilled personnel. Highlighting the difficulties in industry adoption of MBSE, prior research by the authors identified challenges such as tool limitations, knowledge gaps, cultural and political barriers, costs, and the level of customer understanding and acceptance of MBSE practices. Additionally, another study by the authors points out a gap between industry demands for MBSE skills in new hires and the current academic training programs. To further assess the MBSE industry’s workforce needs, this paper introduces a two-phase method for the Structured Extraction of MBSE competencies using large language models based on current workforce demands from LinkedIn job postings. Phase 1 involved extracting 1960 job descriptions from LinkedIn using the term “model-based systems engineer.” In phase 2, large language models (LLMs) employing deep transformer architectures were used to transform unstructured text into structured data. An AI agent was used as an autonomous software layer to manage every interaction between the raw dataset from Phase 1 and the LLM. Supported by the analyzed data, a competency framework is proposed that summarizes the tools, technical skills, and soft skills expected of a model-based systems engineer by the industry. The framework is designed to include core competencies shared across all MBSE roles, with specific competencies tailored for aerospace & defense, manufacturing and automotive, and software and IT sectors. 
    more » « less
  4. ; ; ; (, ASEE Conferences)
    Traditional PhD training in STEM fields places a strong emphasis on developing doctoral students' academic skills, encompassing research, academic writing, as well as sharing of knowledge through publications and conference presentations, etc. However, with the ever evolving expectations of graduate training, particularly in applied fields, the demand for PhD has transcended the confines of academia. For instance, nearly 90% of engineering PhDs will not enter academia, which underscores the discrepancy between the current PhD training programs and the preparation of students for future careers. To better support doctoral students especially for those who intend to pursue positions in industry including corporate R&D labs, national labs, defense organizations, healthcare institutes, etc., Lehigh University launched an innovative program called Pasteur Partners PhD (P3) specifically for the training of such doctoral students. It is a student-centered doctoral training program based on use-inspired research in partnership with industry. A preliminary evaluation of the P3 program, which was developed with support from NSF’s IGE program, revealed that students benefited significantly from gaining practical skills through industry involvement such as co-advising, resulting in a clearer understanding of how the industry operates, which, in turn, enhanced their employability in the industry [1]. The University administration also provided significant support for the program. However, a broader implementation of P3 encountered challenges and hesitancy from faculty members. Mostly the senior faculty who already had preexisting connections with industry and junior faculty from certain departments were more receptive to joining the P3 program than others. Could this be a result of the prevailing emphasis of the graduate education system on research output (publications) rather than the training of students for their subsequent careers? What other reasons could there be for the faculty’s lack of enthusiasm for the training of their PhD students following P3 track? To answer above questions and examine the challenges and obstacles that the faculty members feel for student centered doctoral training from an institutional and system perspective, we are conducting a survey specifically targeting faculty members in STEM fields. It seeks to comprehensively understand faculty members’ perspective on the primary objectives of doctoral training within different STEM fields. By exploring these objectives, the survey aims to uncover how they vary across disciplines and what faculty members perceive as the most significant goals in their areas of expertise. Moreover, the survey is designed to shed light on the challenges and hurdles faced by faculty members in their pursuit of these training objectives. Faculty participants are encouraged to identify and articulate the specific obstacles they encounter, whether they pertain to institutional constraints, resource limitations, demands of perceived professional success or other factors that impede the realization of these goals. In addition, the survey takes a close look at the resources that faculty members believe would be beneficial in addressing these challenges and improving the effectiveness of doctoral training. This insight is essential for designing support systems that can empower faculty to contribute to the training of doctoral workforce for the benefit of society at large. The survey seeks to gain valuable perspectives on the qualities and skills considered essential for the success of PhD students. These insights will inform curriculum development and help prepare students better for a wider range of career paths. The results of the survey, currently underway, are presented. 
    more » « less
  5. ; ; ; ; (, ASEE Conferences)
    Texas State University received an NSF S-STEM award to support two cohorts of talented, low-income engineering majors, with the first cohort starting their freshman year in Fall 2024. In addition to the scholarships awarded, this program aims to increase students’ engineering design self-efficacy, engineering identity, and improve persistence to graduation. The program includes unique strategies for achieving these goals, emphasizing mentoring and building a sense of community among participants. The SEED scholars were paired with a faculty mentor in their engineering major prior to their arrival on campus for their freshman year. This early contact was intended to open lines of communication with a faculty member, so the students felt they had a trustworthy source of information from someone who cared about them. As Texas State University has a high number of first-generation college students, there was an expectation that this program would likely attract a fair number of first-generation students. Without another family member’s experience about how to be a college student, having this faculty mentor gave these students a person who could help them answer questions and navigate the process leading to their first semester on campus. For instance, mentors were able to talk with students about dorm selection, mathematics course placement (including strategies for placing into a higher-level mathematics course), and what to expect in their engineering coursework. Student participation in an Engineering Living Learning Community (LLC) is another unique program feature to enhance community among the SEED scholars. A general description of the program and preliminary results from the students’ self-reported sense of belonging in engineering, engineering design self-efficacy, and engineering identity are presented in this paper. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email