United States

The University of Maryland’s First-Year Innovation &amp; Research Experience (FIRE) is a 3-semester gen-ed program with a first-semester enrollment of more than 600 undergraduates. FIRE provides faculty-mentored research experience and career-readiness with more than 15 diverse research streams available to its students in their second and third semesters. In 2019, I launched a FIRE stream called “Simulating Particle Detection” (SPD), to introduce undergraduate students to the field of experimental high energy particle physics. The research concentrates on computing and data analysis using simulations of novel detectors, specifically, the upgrade calorimeters of the CMS experiment at CERN. While high energy physics experiments are at the forefront of large collaborative research, large-size, university-wide, course-based research experiences are not as common. There are challenges to be addressed to serve about thirty undergraduates every year, such as adaptation of a high-level research topic into a course curriculum, physical and digital research setting logistics, and mentoring of students from different disciplines. I will share my experiences from SPD so far, highlighting not only research but also pedagogical methods and outcomes concerning the above challenges.

AAPT SM 20

Particle Physics Research within UMD’s FIRE Program

course-based research

undergraduate research

particle physics

physics education

The annual UI conference has grown from a meeting to a community of more than 6,000 researchers, program officers, evaluators, program directors, training faculty, and others within STEM, and now operates with a mission to mutually inform scholarship and practice, develop and enhance the community interested in educational interventions, and provide professional development for all STEM persons. UI held its first Virtual conference in December of 2020 in response to Covid-19 restrictions that forced the cancellation of the original March 2020 in person meeting. Born out of necessity, the virtual conference introduced a format that provided pre conference availability of symposia, Deeper Dives and Poster presentations. The 13th Annual Understanding Interventions Conference will continue with that design and we foresee future conferences adopting aspects of that format in reaching a virtual audience as well as those who attend the conferences in-person.

Attendees will experience plenaries, workshops, symposia, and poster presentations on hypothesis-based research on interventions and initiatives that broaden participation in STEM careers. The conference will continue to facilitate the dialogue among education, behavioral, and social science researchers, evaluators, and faculty in STEM fields who participate in intervention programs. Graduate students in these fields are strongly encouraged to attend. Workshops, sessions, and posters will communicate effective strategies from successful STEM intervention programs, present results from empirical research studies, and synthesize the translation of research findings into practice on STEM learning, undergraduate research, graduate education, and student retention.

The cost to attend the conference is $150. There are special rates for post-doctoral fellows and graduate students, as well as conference grants that can be provided for those with need. Registration for the conference is open, with additional information to come.

13th Conference on Understanding Interventions 2021

The annual UI conference has grown from a meeting to a community of more than 6,000 researchers, program officers, evaluators, program directors, training faculty, and others within STEM, and now operates with a mission to mutually inform scholarship and practice, develop and enhance the community interested in educational interventions, and provide professional development for all STEM persons. 

The University of Maryland’s First-Year Innovation & Research Experience (FIRE) is a 3-semester gen-ed program with a first-semester enrollment of more than 600 undergraduates. FIRE provides faculty-mentored research experience and career-readiness with more than 15 diverse research streams available to its students in their second and third semesters. In 2019, I launched a FIRE stream called “Simulating Particle Detection” (SPD), to introduce undergraduate students to the field of experimental high energy particle physics. The research concentrates on computing and data analysis using simulations of novel detectors, specifically, the upgrade calorimeters of the CMS experiment at CERN. While high energy physics experiments are at the forefront of large collaborative research, large-size, university-wide, course-based research experiences are not as common. There are challenges to be addressed to serve about thirty undergraduates every year, such as adaptation of a high-level research topic into a course curriculum, physical and digital research setting logistics, and mentoring of students from different disciplines. I will share my experiences from SPD so far, highlighting not only research but also pedagogical methods and outcomes concerning the above challenges.

poster

The 2020 AAPT Virtual Summer Meeting brought together physics educators from around the globe to learn about the latest in physics theory, research methodology and education from leaders in their field. The program featured plenary speakers, sessions, workshops and many special activities.

For more information please visit the 2020 AAPT Virtual Summer Meeting page at: https://www.aapt.org/Conferences/SM2020/index.cfm.


The 2020 AAPT Virtual Summer Meeting brought together physics educators from around the globe to learn about the latest in physics theory, research methodology and education from leaders in their field. 

Simple epidemiological models are introduced using finite difference methods in Excel. The SIR model explains the initial exponential growth of COVID-19, the effects of social distancing in the US during early April 2020 and successfully predicts the continued spread of the virus during late April and May 2020. The SIR model is the origin of the basic reproduction number R0 and herd immunity. It also predicts what will happen if social distancing is lifted prematurely. A wide range of student research projects are possible for modeling and making predictions based on real data for US states and other countries. See http://circle4.com/biophysics for free sample chapters and videos.

Birds, Bats, & Lego Limbs: Modeling the Variable Moment of Inertia During Locomotion in a Lab for IPLS Students

A surface seiche is a regular oscillation of the surface of an enclosed body of water such as a lake or bay. This project examines the formation of a seiche in a small circular above-ground pool. Analyzing observations from an ultrasonic range sensor, we determine the initial amplitude, period and decay constant of the seiche to be 6.2 cm, 1.975 s and 340 s, respectively. Since the decay time constant is much larger than the period, frictional effects should have a relatively small impact on the period of the seiche. We use a finite difference scheme to solve the wave equation in cylindrical coordinates for the surface height. We find that the theoretical period agrees with the observations if a wave speed consistent with the pool dimensions is used instead of the wave speed provided by the shallow wave approximation.

Premium content

Next from AAPT SM 20

Birds, Bats, & Lego Limbs: Modeling the Variable Moment of Inertia During Locomotion in a Lab for IPLS Students

Similar lecture

Supporting STEM students through remote interdisciplinary collaboration in undergraduate research