Our client was in search of innovative ways to use technology to address a number of educational and behavioral areas of opportunity for teachers and students.
Our goals for this project were to:
Leverage the existing technology at the school; figure out how best to monitor student engagement during technology use; utilize predictive modeling to make data-based learning decisions for student users; make the overall user-experience friendly and exciting for students
We split the program up into quarterly deliverables to ensure proper time for testing, implementation, review, and revision. Our first steps were to take inventory of the technology provided, both hardware and software, to understand where to start. We then collaborated with Hapara, a chrome-based monitoring software that allows for easy integration with Google Classroom, which we also set up for the school. We also configured an early AI model to interact with purely numerical data from student usage including time logged on each assignment, time navigated away, transition lengths, and more, to predict which students would be more likely to pass a given assignment than not. We also worked with various teachers at the school to adopt these tools to test our findings across diverse age ranges and experiences.
The outcome of the project was the long-term implementation of the Early Identification Protocol, which leveraged the innovations that Kailearn put in place, including a new LMS, Hapara integration, Massive Online Open Course configuration, and an AI Model, to not only provide students a new and engaging way to do their work in key classes, but also a way for educators to identify which students require more help before taking a test, in order to provide them with the proper early support.