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Seismology Skill Building Workshop (SSBW)

    Course Information

    The Course

    The Seismology Skill Building Workshop (SSBW) is a free online course designed to enhance scientific computing skills in seismology, tailored to undergraduate students and recent graduates in disciplines such as computer science, geophysics, geology, mathematics, physics, and engineering. The workshop accommodates anyone worldwide wishing to enhance their seismological computing skills, though it is introductory-level.

    Fill out this special interest form to receive an email alerting you when registration opens for 2025!

    Workshop Overview:

    • Duration: Approximately 70 hours, delivered over 12 weeks, so ~5-7 hours per week.
    • Format: Online-hybrid, with semi-self-paced, weekly webinars and assignments.
    • Primary Audience: Undergraduate students/recent graduates (especially those starting graduate school).
    • Secondary Audience: Graduate students and others seeking computing skills in seismology.
    • Prerequisites: No strict requirements, but at least one semester of math and physics is beneficial.
    • Technical Requirements: A PC/Mac with stable internet; SLACK is required for communication.

    Course Content and Structure:

    The 12-week online workshop includes:

    • Weekly live webinar  introductions of content (~1 hour)
    • 36 hands-on assignments
    • Slack discussions and peer engagement
    • Biweekly learning modules (each with 5-8 tutorials)

    Participants progress at their own pace but must adhere to assignment deadlines. Webinars are recorded for flexible access. A learning management system provides real-time feedback and opportunities for partial credit on reattempts. Supplemental resources, including research papers and webinars, are available for extended learning.

    Learning Objectives

    By the end of the workshop, participants will:

    • Develop proficiency in scientific computing tools for seismological research.
    • Analyze seismic data to study earthquake patterns, subsurface structures, seismic waveforms, and noise.
    • Explain seismological concepts and how seismic data provides insights into Earth’s dynamics.
    • Build professional skills to strengthen graduate school, internship, and job applications.

    Core Topics Covered

    The course consists of six core modules, plus a bonus module on GNSS data analysis:

    • Linux & GMT – Introduction to Linux command line, shell scripting, and basic plot generation with GMT to explore earthquake patterns in space, time, and magnitude, and Earth’s internal structure based on seismic wave travel times.
    • SAC – Introduction to Seismic Analysis Code (SAC) for viewing seismograms as waveforms and spectrograms, conducting time-series analysis, filtering, and component rotation to detect, characterize, and interpret seismic wave patterns.
    • IRIS Data Tools – Use of various IRIS waveform, metadata, and earthquake catalog request tools (e.g., web services, earthquake browser, Wilbur, MUSTANG, etc.) to check data availability and explore relationships between earthquakes, plate boundaries, frequency, and magnitude.
    • Waveform Visualization & Modeling – Visualization of seismic waveforms for a given earthquake and software for forward modeling and inversion to estimate subsurface velocity structures, earthquake hypocenters, and fault plane solutions.
    • Python & ObsPy – Introduction to Python and libraries (e.g., NumPy, Matplotlib, Pandas, and ObsPy) for retrieving, processing, and plotting seismic data tables and time series to enable rapid scientific analysis of earthquake catalogs and waveforms.
    • Jupyter Notebooks – Use and creation of Jupyter Notebooks with Python to explain and share code for advanced seismogram processing, including removing instrument responses, calculating spectrograms, and estimating temporal changes in cultural noise.
    • (Bonus) GNSS Data Analysis – Accessing and analyzing GNSS data, interpreting plots, creating station motion plots over time, removing linear trends, examining residuals, and exploring GNSS time series for signals of Earth processes.

    Optional Final Assignment

    Participants will have the opportunity to:

    • Select seismic recordings from anywhere in the world.
    • Create a Jupyter Notebook to request and process the data.
    • Annotate their process, detailing station selection, data processing steps, and findings.
    • Generate plots to illustrate conclusions and support their analysis.

    Additional Skills Covered:

    • Seismic Network Processing: Data flow and operations within seismic networks.
    • Research Methodologies: Best practices in scientific literature, coding habits, and mentorship.
    • Transferable Data Scientist Skills: Seismology content knowledge, quantitative literacy, graphical literacy, computational thinking, critical thinking, and computer programming.

    Assessment and Certification:

    Participants’ progress is evaluated through a series of assignments and projects designed to apply the concepts learned. At the end of the workshop, participants will receive a performance report certificate via email indicating the content of each module, the number of assignments completed for each module, whether the assignments were completed by the deadline, and the average score on each module.

    Instructors:

    Mike Brudzinski, Miami University

    Gillian Haberli, EarthScope Engagement (primary contact: Gillian.Haberli@earthscope.org)

    Michael Hubenthal, EarthScope Engagement

    Graduate Teaching Assistants

    History of the Seismology Skill Building Workshop:

    The Seismology Skill Building Workshop (SSBW) was established in 2020 by the Incorporated Research Institutions for Seismology (IRIS) in collaboration with Miami University. This initiative was a direct response to the COVID-19 pandemic, which led to the suspension of numerous summer research opportunities for STEM students, including the IRIS Undergraduate Internship Program. The SSBW aimed to fill this void by offering a free, fully online course designed to enhance undergraduates’ knowledge and skills in observational seismology and scientific computing.

    The inaugural workshop in 2020 attracted 760 undergraduate participants from 60 countries, with 59% identifying as women and 29% from groups traditionally underrepresented in the geosciences. The curriculum was structured into seven bi-weekly modules, each comprising interactive, self-paced assignments delivered through a learning management system.

    Building upon the success of the initial offering, the SSBW has continued annually, eventually opening up to include graduate students and other professionals. The program is committed to running through at least the summer of 2025. The primary objectives of the workshop are to increase students’ interest and proficiency in seismology and scientific computing, boost their confidence in handling seismic data, and enhance their competitiveness for graduate school, internships, or professional positions.

    The SSBW’s inclusive and accessible design has made it a valuable resource for a diverse population of students worldwide, providing essential skills and knowledge in the field of seismology.

    Collaborations with Miami University:

    Miami University is  a significant collaborator in the SSBW initiative. The university has provided the learning management system for the course for 2020 to 2024, Prof. Brudzinski has led the development of the assignments, and a number of Miami students and postdocs have been involved in the course as teaching assistants or as researchers investigating the impacts of the SSBW. These collaborations have expanded the workshop’s reach and provided additional resources to participants.

    SSBW Research

    Research into the Seismology Skill Building Workshop

    A funded NSF IUSE:EHR project aims to serve the national interest by improving computational thinking and scientific computing skills of advanced undergraduate students. Additionally, through its research efforts, the project also intends to increase understanding about how diverse groups of students engage with and benefit from the tutorial-based active e-learning approach. By identifying workshop features that attract diverse audiences and promote retention, learning, and satisfaction, the project can also define a framework that other STEM communities can use to develop similar technical training efforts.

    This project will investigate the resulting research questions, which are important within and beyond seismology: 

    1) To what extent does this online scientific computing training model enhance participant learning and behavior? 

    2) What are the key influences on retention and performance for advanced undergraduates in the online scientific computing training model and can new interventions improve efficacy? 

    3) To what degree do the elements of the tutorial-based active e-learning approach contribute to learning? 

    4) How can the value of the Seismology Skill Building Workshop and its positioning within the seismology learning ecosystem be optimized to ensure sustainability? 

    These questions will be addressed through a multi-year, mixed methods research investigation that includes development of instruments for summative assessment of computational thinking and programming within a disciplinary context, improved characterization of assignment question types to examine performance trends, and correlation analysis of participant activity and performance data. Expert reviews of the curriculum and community focus groups will be conducted to ensure sustainability of the Seismology Skill Building Workshop. The NSF IUSE:EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. This project is in the Engaged Student Learning track, through which the IUSE program supports the creation, exploration, and implementation of promising practices and tools.

    The NSF award pages can be found here:
    https://www.nsf.gov/awardsearch/showAward?AWD_ID=2121342&HistoricalAwards=false  https://www.nsf.gov/awardsearch/showAward?AWD_ID=2121503&HistoricalAwards=false

    Relevant Presentations and Publications:

    Publications:
    The SSBW has been the subject of several peer-reviewed publications that discuss its design, implementation, and outcomes:

    Presentations:
    The SSBW has also been the subject of numerous presentations that have discussed its impact and collected feedback from the scientific community:

    • Ventura-Valentin, W. A.*, M. R. Brudzinski, Haberli, G., Hubenthal, M (2024), The Large-Enrollment Seismology Skill Building Workshop as a Geoscience Recruiting Tool, Abstract presented at AGU Fall Meeting, Washington, DC, 9–13 Dec.
    • Haberli, G.*, Brudzinski, M., Hubenthal, M., & Meyer, E. (2024). Enhancing student learning in a Large-Enrollment, Scientific Computing Workshop in Seismology. Abstract presented at AGU Fall Meeting, Washington, DC, 9–13 Dec.
    • Meyer, E.*, Hubenthal, M., Haberli, G., Brudzinski, M. R., (2024), Developing an understanding of the Seismology Learning Ecosystem and its connection to the Seismology Skill Building Workshop: What are students learning in introductory seismology classes and how are they learning it?, Abstract presented at AGU Fall Meeting, Washington, DC, 9–13 Dec.
    • Ventura-Valentin, W. A.*, M. R. Brudzinski, Haberli, G., Hubenthal, M (2024), The Large-Enrollment Seismology Skill Building Workshop as a Geoscience Recruiting Tool, Abstract presented at GSA Connects, Anaheim, CA, 22–25 Sept.
    • Haberli, G.*, Brudzinski, M. & Hubenthal, M. (2024), Advancing Scientific Computing Skills and Diversity in the Geosciences Through Asynchronous Learning at the Margins of Higher Education. Presented at the 2024 Earth Educators’ Rendezvous, Philadelphia, PA, 15-19 July.
    • Kalmer, M., M. Brudzinski*, D. Gossett, M. Hubenthal, G. Haberli, Relationships between Attrition and Student Performance in a Large-Enrollment Online Skill Training. Presented at the 2024 Earth Educators’ Rendezvous, Philadelphia, PA, 15-19 July.
    • Haberli, G., Brudzinski, M.* & Hubenthal, M. (2024), Using Learning Analytics to Evaluate the Instructional Design and Student Performance in a Large-Enrollment Scientific Computing Workshop. Presented at the 2024 SSA Annual Meeting, Anchorage, AK, 1-3 May.
    • Goldhagen, G., Brudzinski M. R.*, Hubenthal, M. (2023), Evaluating the instructional design of a large-enrollment scientific computing workshop designed to broaden access to geophysics, Abstract presented at AGU Fall Meeting, San Francisco, 12-16 Dec.
    • Brudzinski, M.* & Hubenthal, M. (2023), Evaluating the Instructional Design of a Large-Enrollment Scientific Computing Workshop Designed to Broaden Access to Geophysics (Invited) [ED43B-03]. Presented at 2023 Fall Meeting of the American Geophysical Union, San Francisco, CA.
    • Brudzinski M. R.*, Goldhagen, G., Hubenthal, M. (2023), Evaluating the instructional design of a large-enrollment scientific computing workshop designed to broaden access to geophysics, Abstract presented at GSA Annual Meeting, Pittsburgh, PA, 15-18 Oct.
    • Goldhagen, G.*, Brudzinski M. R., Hubenthal, M. (2023), In-Depth Assessment of a Large-Enrollment Scientific Computing Workshop to Evaluate Instructional Design and Foster an Online Experiential Learning Cycle, Abstract presented at Earth Educator Rendezvous, Pasadena, CA, 10-14 July.
    • Brudzinski M. R.*, Hubenthal, M. (2021), Expectancy and Value as Drivers for Participation and Persistence in an Open-access Online Scientific Computing Training in Seismology, Online, Abstract presented at Earth Educators Rendezvous, Online, 12-16 July.
    • Brudzinski M. R.*, Hubenthal, M., Fasola, S., Schnorr, E. (2021), Learning in a Crisis: Online Skill Building Workshop Addresses Immediate Pandemic Needs and Offers Possibilities for More Inclusive Trainings, Abstract presented at SSA Annual Meeting, Online, 19-23 April.

    Funding

    This workshop and the associated research initiatives is supported by the National Science Foundation (NSF) through funding from DUE 2121503 & 2121342, and The National Science Foundation’s Seismological Facility for the Advancement of Geoscience (SAGE) Award, EAR-1724509.