COMM 1080 AI Storytelling for Good

This is a one-credit pass/fail course. This course is a collaborative exploration into the rapidly evolving landscape of Generative AI and its transformative impact on the art of storytelling. Students will be part of a creative R& D team headquartered in the BC Communication Department's Creative Communications Lab. We will work as a team of curious learners to identify, evaluate, and experiment with a wide range of ever-proliferating AI-powered creative tools. This course employs a hands-on, project-based approach where students will apply GenAI tools to create digital audio and video stories - rooted in the fundamentals and science of effective storytelling. Along with learning traditional digital storytelling tools, we will explore new GenAI tools and put them into the service of storytelling. As we do so, we will also critically examine the ethical, social, and economic implications of Generative AI in media communications, and consider how these powerful tools can be used to produce positive stories that serve humanity.

Course overview

Department
Communication
School
MCAS
Credits
1
Level
Undergraduate
Offered
Annually

Course evaluations

Response-weighted averages from Boston College’s official course evaluations (Avalanche/Blue).

Course rating
4.78 / 5 · Excellent
21 responses
Instructor rating
4.93 / 5 · Excellent
21 responses
Terms evaluated
1
Most recent: Spring 2026

Scales: overall ratings run from 1 (poor) to 5 (excellent); agreement questions from 1 (strongly disagree) to 5 (strongly agree); weekly effort from 1 (up to 1 hour) to 5 (10 or more hours).

Evaluations by term and instructor
TermInstructorCourse overallInstructor overallWell organizedClear learning objectivesIntellectually challengingHelpful assignmentsApplicable beyond courseAttendance necessaryWeekly effortResponses
Spring 2026Paul Reynolds4.84.94.84.74.34.74.74.41–3 hrs/week21 of 28

Data freshness

Course and evaluation data last updated 2026-10-09. Source details and limitations are documented in Data Sources and Methodology.

Instructors

  • Paul Reynolds
    Spring 2027, Fall 2026, Spring 2026 · Official rating 4.93/5

Sections

  • Section 01
    Spring 2027 · Paul Reynolds · Lyons Hall 207 W 04:30PM-05:30PM · Offered
  • Section 02
    Spring 2027 · Paul Reynolds · Lyons Hall 207 W 05:30PM-06:30PM · Offered
  • Section 01
    Fall 2026 · Paul Reynolds · Lyons Hall 207 W 04:30PM-05:30PM · Offered