Speaking and writing fluency in interactions with chatbots
(2025) The 34th Conference of the European Second Language Association (EuroSLA 2025) — Location: Tromsø, Norway (25.June.2025)
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- Abstract
- Utterance fluency, particularly in speaking, has been demonstrated to be a robust indicator of L2 proficiency (Tavakoli et al., 2020), strongly linked to automaticity (Suzuki & Révész, 2023) and, as such, an advantageous aspect of performance to assess (de Jong, 2018). Recently, studies have also looked at writing fluency to determine how much it relates to performance (Aldridge & Fontaine, 2019) and proficiency (Révész et al., 2022). The present study attempts to compare speaking and writing fluency based on conversational interactions with automated agents or chatbots to determine how speaking and writing-based fluency measures correlate or diverge from each other and how they predict—or not—proficiency. To the best of our knowledge, this will be the first study to look at L2 writing fluency in the context of spontaneous, immediate conversational tasks in the context of synchronous computer-mediated communication (SCMC), as all previous studies on L2 writing fluency have been focused on relatively long, non-interactional forms of writing (Suzuki & Révész, 2023). We collected spontaneous speech and written performance from N=215 teenage learners of French through a computer-assisted language learning (CALL) game constructed around guided conversations with characters. The speaking performance was a computer-delivered interview consisting of 27 items (short questions). We computed most speaking fluency metrics known to be good predictors of L2 proficiency, such as speech and articulation rate, length of runs in syllables and duration, silent pausing rate, etc. (Suzuki & Révész, 2023; Segalowitz et al., 2017). We also obtained a proxy of L2 proficiency for the participants through a vocabulary size test (Peters et al., 2019). In parallel, we collected keystroke logs of the written conversational interactions of 81 participants in the CALL game. The keylogs allow us to compute a series of writing fluency metrics, particularly speed and pausing, such as length of P-bursts in characters, characters over time, pause number per minute and median pause length (see also Révész et al., 2022). We will report how results from the same participants correlate across modes and across aspects of utterance fluency and how much they can predict, separately and jointly, L2 proficiency.
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Bibauw, S. (2025). Speaking and writing fluency in interactions with chatbots. The 34th Conference of the European Second Language Association (EuroSLA 2025), Tromsø, Norway. https://hdl.handle.net/2078.5/274568