Booth Id:
SOFT022
Category:
Systems Software
Year:
2020
Finalist Names:
Kim, Sunho (School: Homeschool)
Abstract:
When realizing extensive reading curriculum, instructors had to take demanding tasks to set up an appropriate infrastructure, and students were faced by so many unfamiliar words that they avoided memorizing them manually. Gorani Reader improve this situation by providing an electronic environment where teachers can manage and monitor student’s learning effortlessly. It also supports less stressful vocabulary memorization that utilizes incidental vocabulary learning. By conducting time-dependent knowledge tracing using dictionary usage data over time, Gorani Reader traces student's vocabulary. And then, Gorani Reader recommends right-level short texts that contain academically important words that are predicted to be forgotten. As I can get real time metrics regarding student's learning from dictionary usage data and activity data, I can easily evaluate the effectiveness of this recommendation approach and experiment with various recommendation systems cost efficiently.