Course Syllabus
Course: MUSC 2126
Division: Fine Arts, Comm, and New MediaDepartment: Music
Title: Badger Pep Band II
Semester Approved: Spring 2018
Five-Year Review Semester: Spring 2023
End Semester: Spring 2024
Catalog Description: This course involves participation in ensemble performances supporting Snow College athletic events. This course is repeatable for credit.
Semesters Offered: Fall, Spring
Credit/Time Requirement: Credit: 1; Lecture: 1; Lab: 0
Repeatable: Yes.
Justification: Students in this ensemble help provide the Snow College student body with a collegiate experience by contributing to the celebratory atmosphere of college athletic events. Most institutions in Utah offer students a pep band experience. This group serves all students who wish to play, regardless of technical facility. Snow College ensemble credit will likely transfers to two and four-year institutions.
Student Learning Outcomes:
Students will demonstrate an understanding of the literature selected by the instructor through accurate and expressive performance. This outcome will be assessed by the conductor in sectionals, rehearsals and performances, and through the administration of playing tests.
Students will provide service to the campus community through performances at athletic events. This outcome will be assessed by the bands presence at athletic events.
Music majors will demonstrate the ability to conduct and manage athletic bands. This outcome will be assessed by assigning music majors conducting and management responsibilities and observing the result.
Content:
Appropriate pep band music will be studied, arranged, and performed.
Key Performance Indicators:
Satisfactory participation in sectional and full ensemble rehearsal: 30 to 40%
Satisfactory participation in each ensemble performance: 30 to 40%
Periodic playing tests: 20 to 30%
Pedagogy Statement:
This course will be delivered via lecture, class discussion, sectional rehearsals, student led rehearsals, and performances.
Instructional Mediums:
Lecture/Lab
Internship
Maximum Class Size: 100
Optimum Class Size: 100