teaching

Links to Syllabi:


Teaching Statement

From Pinhole to Pixel: Cultural Contexts and Technological Evolution

In my Computational Photography course, students begin by piercing blackout drapes with pins and projecting images of the world on their hands. From there they build dark boxes and try to capture those fleet images with iron and silver. This is how they begin to experience fundamental properties of light and image technology. The journey from pinhole to pixel exemplifies my broader pedagogical approach: creating embodied encounters with technological evolution that reveal how different forms of mediation shape our understanding of the world.

Over more than five years of teaching at Scripps College, I have developed this approach to teaching technology through embodied experience. The liberal arts emphasis on interdisciplinary thinking provides an ideal environment for exploring how technologies mediate our relationship to the world. In my classrooms, students begin by encountering fundamental principles through direct physical engagement - projecting images through pinhole cameras, exploring sound through torn speakers, or transmitting signals through handmade mechanisms. As they progress to more complex digital tools and systems, this foundation of tangible understanding helps them grasp abstract concepts and approach new technologies with confidence and creativity.

The introductory semester of Computational Photography begins with students crafting their own cameras and experimenting with nineteenth-century processes - coating paper with silver nitrate to create cyanotypes and working with direct positive film. In the advanced semester, they reconstruct pivotal moments in imaging technology: reproducing the first digital camera, using OpenCV to manipulate image matrices, and reconstructing Prokudin-Gorsky's revolutionary three-color plates. Each advancement reveals not just new technical capabilities, but different ways of seeing and representing the world.

This exploration of how technology shapes perception extends into Fuzzbox Physics, where students encounter sound through multiple modalities. They begin by exploring distortion and reverb through natural echoes, discovering how architecture and materials shape our sonic experience. As they progress to manipulating analog signals by modifying speakers and building transistor amplifiers, they learn to hear both the mathematical transformations and the aesthetic qualities of different forms of distortion - from the classic Fuzzface to the octave-shifting Octavia.

In Tangible Media, students synthesize these understandings of visual and sonic mediation to create interactive systems. A signature project challenges each student to create a machine that transmits a simple message to their neighbor's device within a precise timeframe. The message travels from project to project around the classroom, finally triggering a celebratory release of confetti - a moment that transforms individual technical understanding into collective achievement and reveals how different forms of communication can build shared experience.

In Machine Learning for Artists, students encounter contemporary technological mediation through hands-on engagement with artificial intelligence. By studying and remaking works by artists like Mario Klingemann and Anna Ridler, students develop both technical understanding and critical perspective. They begin with simple image classification before advancing to complex generative systems, maintaining the same emphasis on embodied learning. When training models on their own datasets or creating real-time interactive installations, students discover how ML systems mediate between data and interpretation, between input and output, between human and machine ways of seeing.

This sequence continues to evolve as I develop Data Structures in Place: From Linked Lists to Songlines, a course that explicitly examines how different cultures encode and transmit knowledge. While previous courses explore how technology mediates our relationship with physical phenomena like light and sound, or how AI mediates between data and interpretation, this new course reveals how various knowledge systems - from computational data structures to Indigenous ways of knowing - shape our understanding of place and memory. The course grows from a successful exercise teaching linked list concepts through Indigenous ways of knowing, demonstrating how different approaches to representing information can illuminate and enrich each other.

My assessment approach reflects and reinforces these core pedagogical principles. By emphasizing process over perfection, I create space for students to take creative risks. When a Computational Photography student's handmade camera produces unexpected aberrations, or a Fuzzbox Physics circuit generates surprising sounds, these "failures" become valuable learning opportunities documented in project portfolios.

From pinhole cameras to Indigenous data structures, this progression helps students develop a technological literacy that spans technical competency, cultural understanding, and historical awareness. Through structured peer critique and hands-on exploration, students learn to articulate their technical choices and understand how their work relates to broader conversations about technology's role in society. Most importantly, they discover that there are many ways of knowing and representing the world. Whether working with nineteenth-century photographic processes or contemporary data structures, students learn to recognize technology as one of many systems that shape how we understand and interact with the world around us.