Using EGRA Data to Automatically Generate Teaching and Training Advice for Teachers in Developing Countries

Abstract

Inter-class and within-class grouping has been used extensively to deal with student diversity. This paper presents a method that uses Rasch Modelling and K-means to automatically create ability-based groups or prototypes of students that can be utilized to provide customized lesson plans and advice to teachers. A second-order clustering is used to create groups of teachers to help deliver more effective continuous professional development for teachers. A case study of applying the method to a deployment of Early Grade Reading Assessment (EGRA) in two rural and semi-rural Districts in Pakistan is presented. Data from 99 schools and 717 students is considered. The results are that approach produces developmentally interesting prototypes or groups of students in addition to creating key insights on how to organize professional development activities for teachers.