A content analysis of community discourse regarding Duolingo Max

Abstract

Using the content analysis method, this bachelor’s thesis investigates Reddit discussions about the popular language learning app Duolingo. The aim is on summarizing the views of the community towards a new subscription tier called Duolingo Max by categorizing comments according to their contents and sentiment. Lexical analysis and breakdowns of example comments demonstrate how the writer’s attitude can be detected from the text and provides a better understanding of the tone of conversation in the data. The results of topic categorization presented in the tables in the “coding scheme” section indicate that common topics include comparison of Duolingo Max to other features of Duolingo, criticism on the pricing of the subscription, and doubts about the usefulness of the feature for a language learner. Duolingo Max relies largely on AI technology and because of this, it is also one of the most discussed topics in the data. The results are analyzed in the light of the technology acceptance model (TAM) introduced by Davis in 1989, which underlines the perceptions of usefulness and ease of use as predictors of the degree of use when a new technology is introduced. Example comments are presented to illustrate how Davis’s theory manifests in the data. To provide an understanding of the themes discussed in this thesis, the first sections give an overview of previous literature on Duolingo, AI-assisted language learning, ChatGPT and attitudes towards AI, as well as a summary of TAM.