Mas.961 Special Topics Seminar on Deep Engagement:
an exploration into principles, creative methods and techniques for evaluation
|Units 0 9 0|
|Thursday 2:30pm - 3:30pm; E15-335|
|Instructors: Cynthia Breazeal, Glorianna Davenport|
|Guest lecturers: Dan Arieli, Chris Csikszentmihalyi, Judith Donath, Hiroshi Ishii, Tod Machover, John Maeda, Pattie Maes, Joe Paradiso, Roz Picard, Mitch Resnick.|
Innovation in expression -- as realized in media, tangible objects, and performance, and more -- generates new questions and new potentials for human engagement. When and how does expression engage us deeply? While "deep engagement" seems fundamental to the human psyche, it is hard to define, difficult to reliably design for, and hard to critically measure or assess. Are there principles we can articulate? Are there evaluation metrics we can use to insure quality of experience? Many personal stories confirm the hypothesis that once we experience deep engagement, it is a state we long for, remember, and want to repeat. We need to better understand these principles and innovate methods that can insure higher-quality products (artifacts, experiences, environments, performances, etc.) that appeal to a broad audience and that have lasting value over the long term.
This course explores such issues of deep engagement through lecture, class assignments, lively discussion and critique of course readings, and a final student project. Guest lecturers drawn from the ML faculty will present diverse perspectives on this topic representing domains such as music, art, design, film, interactive technologies, learning, environments, and more. For example: How can we structure compelling stories that evolve and are adaptive? How can we build machine-driven characters into stories and games that bond with and develop interesting relationships with the human audience? What relationship does a young musician have with a musical instrument? How can we design interactive spaces that are viscerally engaging? What are optimal conditions for interactive learning? And how can we measure deep engagement at a physiological level?