MIT’s Caitlin Morris: Combining Tech, Education, and Human Connection to Enhance Online Learning
Caitlin Morris, a MIT Morningside Academy for Design (MAD) Fellow and an expert in the fields of architecture, art, research, and education, is dedicated to revolutionizing digital learning platforms. With a background in psychology and a passion for self-taught coding skills through online learning tools, Morris integrates technology, education, and human connection to create more effective and engaging online educational experiences. Her work focuses on understanding how people interact with and respond to their environments, leveraging these insights to enhance digital learning.
Growing up in rural upstate New York, Morris developed a hands-on approach to learning from a young age, mastering skills such as sewing, cooking, and woodworking. This practical background instilled in her a deep appreciation for project-based learning, which she later utilized to teach herself coding and other technical skills.
“For me, that was this huge, wake-up moment of feeling like there was a path to expression that was not a traditional computer-science classroom,” she says. “I think that’s partly why I feel so passionate about what I’m doing now. That was the big transformation: having that community available in this really personal, project-based way.”
Morris’s involvement in community-based learning extends to her role as a co-organizer of the MIT Media Lab’s Festival of Learning and her leadership in creative coding community meetups. She is also an active member of the open-source software community, further demonstrating her commitment to collaborative and accessible learning environments.
“My years of organizing learning and making communities — both in person and online — have shown me firsthand how powerful social interaction can be for motivation and curiosity,” Morris said. “My research is really about identifying which elements of that social magic are most essential, so we can design digital environments that better support those dynamics.”
Morris has contributed to numerous large-scale art installations that blend movement, sound, imagery, and lighting to create immersive experiences. These installations, often evoking elements of nature, aim to captivate and calm viewers by focusing their senses and attention.
Before joining MIT, Morris earned a BS in psychology and a BS in architectural building sciences from Rensselaer Polytechnic Institute, followed by an MFA in design and technology from the Parsons School of Design at The New School. Her diverse educational background informs her holistic approach to improving learning environments.
Morris realized early on that traditional classroom settings were not effective for all students. This realization fueled her passion for creating alternative learning methods that cater to diverse learning styles.
“I think what kind of got me hooked on teaching was that the way I learned as a child was not the same as in the classroom,” Morris explains. “And I later saw this in many of my students. I got the feeling that the normal way of learning things was not working for them. And they thought it was their fault. They just didn’t really feel welcome within the traditional education model.”
Morris’s doctoral work with the MIT Media Lab’s Fluid Interfaces Group focuses on the personal space and emotional gaps associated with online and AI-assisted learning. Her research aims to integrate AI-driven behavioral analysis with human expert assessment to understand how social interaction patterns influence curiosity and motivation in learning.
“I’m developing a framework that combines AI-driven behavioral analysis with human expert assessment to study social learning dynamics,” she says. “My research investigates how social interaction patterns influence curiosity development and intrinsic motivation in learning, with particular focus on understanding how these dynamics differ between real peers and AI-supported environments.”
Her research seeks to identify the elements of social interaction that cannot be replaced by AI and to develop prototype platforms for experiential learning. By tracking observable behaviors and capturing learners’ subjective experiences, Morris aims to bridge the gap between the efficiency of digital platforms and the rich social interaction of in-person learning.
Morris’s research and goals align perfectly with the MIT MAD Fellowship, which emphasizes creativity, critical thinking, and collaboration to prepare students for complex, real-world challenges. She plans to address the challenges posed by the increasing integration of AI in education and to explore the balance between physical and virtual learning spaces.
