A Voice-Based Mobile System for Generating Stallings-Type Class Observations

Abstract

Classroom observation is an important tool for improving quality of education. Observations allow teacher trainers to monitor, assess, and provide feedback to teachers about their teaching techniques and class management practices. The current approach to class observation consists of an observer visiting a classroom once or twice a year. This is both costly in terms of time and resources, insufficient in terms of capturing the true state of the classroom, and in providing accurate feedback. This paper presents the design and implementation of a mobile-based system that automates the class observation process using data mining techniques. The system allows teachers to record audio snapshots during the class session, and receive Stallings-type analysis results for their class on a daily basis.