Affiliation:
1. Indian Institute of Technology Guwahati, Guwahati, India
Abstract
In improving the teaching and learning experience in a classroom environment, it is crucial for a teacher to have a fair idea about the students who need help during a lecture. However, teachers of large classes usually face difficulties in identifying the students who are in a critical state. The current methods for classroom visualization are limited in showing both the status and location of a large number of students in a limited display area. Additionally, comprehension of the states adds cognitive load on the teacher working in a time-constrained classroom environment. In this article, we propose a two-level visualizer for large classrooms to address the challenges. In the first level, the visualizer generates a colored matrix representation of the classroom. The colored matrix is a quantitative illustration of the status of the class in terms of student clusters. We use three colors: red, yellow, and green, indicating the most critical, less critical, and the normal cluster on the screen, respectively. With tap/click on the first level, detailed information for a cluster is visualized as the second level. We conducted extensive studies for our visualizer in a simulated classroom with 12 tasks and 27 teacher participants. The results show that the visualizer is efficient and usable.
Publisher
Association for Computing Machinery (ACM)
Subject
Artificial Intelligence,Human-Computer Interaction
Cited by
7 articles.
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