From Hello to Bye-Bye: Churn Prediction in English Language Learning App

Abstract

Mobile phones and apps have changed the landscape of e-learning and have revolutionised the way people learn a second language by facilitating anytime-anywhere learning, game-based resources and socially interactive learning activities. Despite these features and affordances, these language learning apps suffer a fate of high churn rates. In this paper, we examined the churning behaviour of learners in the context of a language learning app called Hello English. We applied descriptive analytics to analyse the behavioural differences between churners and non-churners and studied their interaction with the app to early-predict churning behaviour. Our findings indicate that non-churners interact with the mobile app more frequently compared to churners. Also, the trained machine learning classifiers can predict learner churning behaviour with a high recall value (0.824) and F1 (0.778). This churn detection will enable the app developers to provide intervention for learner retention.