Applied Physics BS Data Science
Program Purpose
The new BS in Applied Physics: Data Science major provides students experience with the fundamentals of scientific modeling and data science from an underlying foundation in physics. Students gain an understanding of physical laws and how models provide predictive and explanatory descriptions of complex physical and astronomical processes. Complementing this model building perspective for students, experimental lab courses give hands-on experience with designing physical experiments, collecting data, and determining measurement uncertainty. All courses help students build intuition about uncertainty and bias in measurements that inform physics-based approaches to data science.
Students complete mentored research projects in data science on campus or through external internships. Each student completes sufficient research to write a senior thesis or capstone report. This experiential learning is the culminating experience for majors in the Department of Physics and Astronomy and is a crucial part of their preparation for graduate studies or to successfully begin their careers on graduation.
Alignment with BYU Aims and Mission
Intellectually enlarging
Physics students gain a broad education in the principal theories that describe the physical world. They learn to approach complex problems in science and technology, and to conduct scientific research.
Spiritually strengthening and character-building
Students are strengthened in character and faith through faculty instruction and mentoring. These interactions provide opportunities for faculty to demonstrate commitment to both spiritual and intellectual pursuits in their personal and professional lives, and to help students adopt spiritual and professional perspectives and practices consistent with the Gospel. Students learn ethical scientific behavior.
Promotes life-long service
The broad scientific background provided enables students to be informed participants in solving community issues. Students are given opportunities to participate in educational outreach and tutoring through undergraduate activities sponsored by student leaders and the department.
Career Preparation
Update
Curricular Structure
Freshman and sophomore courses include 1) a three-or four course mathematics sequence 2) a four-course introductory physics sequence, including modern physics covering the primary theories described below 3) a four-course experimental laboratory sequence, 4) a first course in scientific computing with a symbolic manipulation program and 5) an introduction to research and careers in physics. The upper division curriculum treats some of the same topics at an advanced level through courses in mathematical physics, classical mechanics, electrostatics, optics/electrodynamics, and scientific computing with technical programming tools.
The culminating experience is mentored research and writing for the capstone project report, which ideally combines work in physics and their chosen emphasis. A writing and presentation course is also offered for those who have completed their capstone project research.
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Learning Outcomes
Physics Theory and Application
Apply principles to model and solve representative problems analytically and computationally at an introductory level from the primary physical theories (classical mechanics, quantum mechanics, special relativity, thermodynamics, electromagnetism, and optics) and at an advanced level in classical mechanics, electrostatics, statistical mechanics, thermodynamics, and optics/electrodynamics.
Apply principles of data science to model physical systems, address physical and astronomical problems, and evaluate the uncertainty, sensitivity, and fidelity of the models.
Communicate professionally to a technical audience both orally and in writing. Be able to understand scientific ideas by reading books and journal articles.
Understand scientific ethical practices, and demonstrate them in the conduct of scientific research.
Conduct experimental, theoretical, or computational research related to data science under the direction of a mentor to contribute to the generation of new knowledge or technologies and prepare to do this professionally.
Design and conduct experiments, build scientific equipment, write scientific programs to simulate physical systems, and analyze data.
Evidence of Learning
Indirect Measures
Senior exit surveys and alumni surveys are monitored to assess student achievement of learning outcomes.
Direct Measures
1. Student mastery of the primary physical theories and analytic, computational and experimental skills will be assessed by requiring graduating students to take the nationally-normed Physics Major Field Test provided each year by ETS.
2. Experimental design and data analysis skills will be assessed by the student's research mentor and undergraduate research committee.
3. Communication skills will be assessed by the student's research advisor and undergraduate research committee.
4. Adherence of ethical principles will be assessed by the student's research advisor and undergraduate research committee.
5. Professional preparation will be assessed by the student's research advisor and undergraduate research committee.
Learning and Teaching Assessment and Improvement
Learning and teaching assessment improvement is watched over by the department learning outcomes assessment committee under the direction of the department chair. This committee looks at the direct and indirect measures of learning in the department and reports to the faculty once a year on trends and possibilities for improvement. The faculty then votes, as needed, and actions are taken. The faculty and the chair also monitor student ratings and peer reviews of teaching to find things that need to be improved in individual classes and in the performance of faculty members, but the review of program learning outcomes is primarily the responsibility of the department learning outcomes assessment committee.
Department Learning Outcomes Assessment Committee Members
Currently being updated.