Lysten: an intelligent feedback system for the online education environment
Lysten was conceived as a final project for the w210 capstone course of the UC Berkeley MIDS program, as a tool to enable conversation between students and professors during the course of the semester, trimester, or quarter.
Virtual classrooms pose a unique social problem: It is critical to collect constant feedback to ensure the course design and materials are at their best. However, students and professors don’t have the same kind of relationship that face-to-face physical classes can foster. This lack of personal relationship can make the feedback loop difficult to facilitate.
Students are often given only limited options to provide formal feedback (in the form of mid- and end-term surveys). Even this small amount of data can be difficult to manage, without a way to automatically pull out patterns from the feedback. Many Professors in online programs have roles in industry, and don't have the time to spend on fully manual review.
Lysten offers a solution: a system by which students and professors can have an interactive conversation throughout the semester, even when a physical space isn’t available. The Lysa chatbot provides a venue for students to air their concerns anytime throughout the semester in a friendly, informal, and interactive environment. The Lysten system then uses machine learning and natural language processing to sift through the feedback, presenting it to instructors and administrators in a clear, concise, and ultimately actionable format.
The result is an enhanced experience for all involved.