Exploring the Design and Application of an Intelligent French Dictation Platform

Abstract

Dictation is considered an efficient exercise for testing French as a foreign language (FFL) learners’ language proficiency. However, the traditional class-based approach to dictation is constrained by the inherent complexity of the exercise’s design, materialisation, and delivery. In this research, we adopted a design-based research approach to design, develop, and apply an intelligent French dictation platform, which we tested on 50 undergraduate FFL learners. By examining their feedback, we identified certain advantages of the platform, such as time–space flexibility, instant correction, and the opportunity to repeat exercises, but also some disadvantages, such as inconvenient text entry, the inability to question a teacher, and the absence of collective learning and supervision. Crucially, this study constitutes an encouraging step forward in classifying frequent errors made by Chinese learners. The results provide a starting point for developing more advanced dictation platforms that will be capable of automatised error classification in the future.

Keywords

• French dictation
• design approach
• learner autonomy
• instant correction
• error analysis
• computer-assisted language learning