DAW 3701 04: DAW Applied Lesson 3701

DAW 3701 - Digital Audio Workstation Applied Lesson 3701

Fall 2026 Syllabus, Section 04, CRN 44273,

Credit hours: 2

Course Meeting Times

Log in to view more

Instructor

Dennis Giotta

Email: dpgiotta@ysu.edu

Public Instructor Information

Professor:  Dennis Giotta

Professional Qualifications:

Ph.D. in Music Education, Case Western Reserve University, Cleveland, OH, 2019 - Dissertation in Progress

Master of Arts in Music Education, Case Western Reserve University, Cleveland, OH, 2013-2015

Bachelor of Music/Double Major in Music Education and Euphonium Performance, University of Cincinnati College-Conservatory of Music, Cincinnati, OH, 2005-2009

Office: Bliss Hall, Room 3004

Phone: (330) 941-3636 

Email: dpgiotta@ysu.edu

Private Instructor Information

Log in to view more

Course Description

3701. Digital Audio Workstation Applied Lesson 3701. Digital Audio Workstation applied lessons offer students the ability to produce, design, and perform a diverse array of original and derivative electronic-based music and multimedia works using analog and digital technology as both a tool and an instrument. Applied musicianship, technical, and creative skills will include composing, improvising, performing, programming, and producing using digital audio workstation (DAW) music software, new interfaces for musical expression (NIME) hardware, digital musical instruments (DMI), and amplification devices in a variety of production and performance environments. Students will foster the functional and virtuosic skills needed to be a performer and producer using DAW technology for artistic and vocational future endeavors. Prereq.: Completion of DAW 2602 with a grade of "C" or better. 2 s.h.

Course Readings

Group Title Author ISBN
No readings

The course readings are subject to change in the event of extenuating circumstances, research developments, current events, and/or to ensure better learning.  

Additional Course Materials

Log in to view more

Course Learning Outcomes/Objectives/Goals

Log in to view more

How to Succeed in This Course

Log in to view more

Attendance Expectations

Log in to view more

Late Work Submission Policy

Log in to view more

Additional Course Expectations

Log in to view more

Artificial Intelligence Policy Statement

Log in to view more

Assignments/Assessments

Log in to view more

Grading and Grading Scale

Log in to view more

University Policies

Log in to view more

Schedule of Topics and Assignments

Week of Proposed Topic Due/To Prepare for Class
8/24 Varies per student Varies per student
8/31 Varies per student Varies per student
9/7 Varies per student Varies per student
9/14 Varies per student Varies per student
9/21 Varies per student Project 1
9/28 Varies per student Varies per student
10/5 Varies per student Varies per student
10/12 Varies per student Varies per student
10/19 Varies per student Varies per student
10/26 Varies per student Varies per student
11/2 Varies per student Project 2
11/9 Varies per student Varies per student
11/16 Varies per student Varies per student
11/23 Varies per student Project 3
11/30 Varies per student Jury portfolio due
12/7 Jury portfolio presentation

The course schedule, policies, procedures, and assignments in this course are subject to change in the event of extenuating circumstances, by mutual agreement, and/or to ensure better learning. 

Additional Information

Log in to view more