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Cited by 1EFL/ESL Teaching and LearningPhonetics and Phonology ResearchSecond Language Acquisition and Learning

The impact of L1 speaking style, task mode, and L2 proficiency on L2 fluency: A within-subject study of monologic and dialogic speech

Open access
Peltonen, Pauliina, Götz, Sandra, Lintunen, Pekka·2025·Studies in Second Language Acquisition
DOI 10.1017/s0272263125101289
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Abstract

Fluency is an essential aspect of second language (L2) oral proficiency. Recent studies have demonstrated that L1 individual speaking style is connected to L2 fluency, suggesting that L2 speech fluency does not solely represent L2-specific skills. Furthermore, task mode (monologue vs. dialogue) has been shown to influence fluency. The present study examines the extent to which these two factors (L1 speaking style and task mode) can predict L2 speech fluency, and how such connections are modified by the learners’ L2 proficiency level. The data consist of monologic and dialogic speech samples from 50 advanced students of English in their L1 (Finnish) and L2 (English). The samples were analyzed for speed, breakdown, repair, and composite fluency. The results of multiple linear regressions demonstrated high predictive power for speed, breakdown, and composite fluency dimensions, while the model for repair fluency showed weak predictive power. The results have implications for L2 fluency research.

AI snapshot

Written from the paper’s full text.

TL;DR

This within-subject study of 50 advanced Finnish learners of English examined whether L2 fluency can be predicted from L1 fluency, task mode, and L2 proficiency. L1 fluency was the strongest predictor across speed, breakdown, and composite dimensions, while task mode affected some dimensions and proficiency only interacted for mean silent pause length.

Key findings

  • L1 fluency predicted equivalent L2 measures: articulation rate β = 0.50, p < .001; silent pauses per minute (logged) β = 0.63, p < .001; mean silent pause length β = −1.62, p = .021; speech rate β = 0.47, p < .001; self-repetitions β = 0.34, p = .03.
  • Final models explained 54% of variance for L2 articulation rate, 45% for silent pauses per minute, 61% for mean silent pause length, 50% for speech rate, but only 8% for self-repetitions.
  • Task mode mattered for some dimensions: monologue was associated with slower articulation rate (β = −7.18, p = .045), more silent pauses per minute (β = 0.15, p = .008, roughly 16% more), and slower speech rate (β = −10.58, p = .020); it was not significant for mean silent pause length or repair fluency.
  • L2 proficiency (LexTALE) was significant only for mean silent pause length, interacting with L1 pause length (β = 0.03, p < .001), with the L1–L2 link stronger at C1/C2 than B2.

Methods

  • Participants were 50 university students of English with Finnish as L1, advanced overall (LexTALE M = 86.4%, SD = 8.06; 74% C1/C2, 26% B2; mean age 21.9 years).
  • Data included monologic picture-description and dialogic problem-solving tasks completed in both L1 Finnish and L2 English; speech was analyzed for speed (articulation rate), breakdown (silent pause frequency and mean length), repair (self-repetitions), and composite fluency (speech rate).
  • Multiple linear regressions in R used each L2 fluency measure as the dependent variable, with corresponding L1 measures, task mode, LexTALE score, and two-way interactions as predictors, followed by downward hierarchical model selection.

Limitations

  • Stated: the sample included only advanced Finnish learners of English, limiting generalizability; future research should include other L1s, other language pairs, lower-proficiency learners, and other task prompts.
  • Stated: including between-turn pauses in the dialogic measures may have impacted the results; future studies should compare measures that include and exclude between-turn pauses.
  • Evident: proficiency effects may be constrained by the sample’s high proficiency and relative homogeneity (74% C1/C2), and the repair fluency model explained only 8% of variance, making repair findings less robust.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1017/s0272263125101289

Cites

50 of 50 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

10 of 67 cited sources checked · 8 supported · 0 flagged · accuracy not yet measured

  • Premisecitation

    L2 speech fluency research generally points to higher fluency for higher proficiency level participants.

    “results generally pointing to higher fluency for higher proficiency level participants (e.g., Kormos & Dénes, 2004;Tavakoli et al., 2020; for a meta-analysis, see Yan et al., 2025).”
    Quote in the paperSubstantial claim1 of 3 sources checked
    • cites Kormos & Dénes, 2004 source
    • cites Tavakoli et al., 2020 source
    • cites Yan et al., 2025 source
  • Premisecitation

    In Duran-Karaoz and Tavakoli (2020), partial correlations controlling for proficiency level did not substantially influence the strength of the associations.

    “yet, partial correlations controlling for proficiency level did not substantially influence the strength of the associations (Duran-Karaoz & Tavakoli, 2020).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Duran-Karaoz & Tavakoli, 2020 source
  • Findingown data

    Participants' proficiency level was estimated at C1/C2 on average based on LexTALE scores.

    “Their proficiency level was estimated at C1/C2 level in the CEFR on average, based on the LexTALE receptive vocabulary test scores (M = 86.4%,SD = 8.06; scores over 80% indicate level C1/C2, Lemhöfer & Broersma, 2012).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Lemhöfer & Broersma, 2012 source
  • Premisecitation

    The interlocutor can assist the speaker in maintaining fluency during problem-solving sequences, such as word searches.

    “the interlocutor can assist the speaker in maintaining fluency during problem-solving sequences, such as word searches”
    Quote in the paperSubstantial claim1 of 3 sources checked
    • cites McCarthy, 2010 source

      In “Fluency in pedagogic contexts” (page unavailable), the paper says other participants can intervene during a communication problem to fill silence and maintain the flow. The “Turn-taking” section likewise describes fluency as a shared responsibility. Our copy does not specifically discuss assistance during word searches. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
    • cites Peltonen, 2017 source
    • cites Peltonen & Lintunen, 2024 source
  • Findingown data

    The study's multiple linear regressions showed high predictive power for speed, breakdown, and composite fluency dimensions.

    “The results of multiple linear regressions demonstrated high predictive power for speed, breakdown, and composite fluency dimensions, while the model for repair fluency showed weak predictive power.”
    Quote in the paperSubstantial claim
  • Classified as probably not a substantial claim. 29
  • May combine two claims. 34

  • Classified as probably not a substantial claim.

    Premisecitation

    Fluency in an interactive setting differs from fluency in monologic settings.

    “Both of these studies suggest that, conceptually, fluency in an interactive setting differs from fluency in monologic settings.”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites Sato, 2014 source
    • cites Van Os et al., 2020 source

  • May combine two claims.

    Premisecitation

    Peltonen and Lintunen (2022) demonstrated strongest correlations between L1 Finnish and L2 English for Group 1, while correlations for Group 2 were overall moderate to strong across different language pairs.

    “demonstrated the strongest correlations between L1 Finnish and L2 English for Group 1, while the correlations for Group 2 were, overall, moderate to strong across the different language pairs (Peltonen & Lintunen, 2022).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Peltonen & Lintunen, 2022 source

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Suzuki and Kormos (2024) found significant moderating effects of cognitive fluency on the L1-L2 fluency relationship for speed fluency, but not for breakdown or repair dimensions.

    “Suzuki and Kormos (2024) explored the moderating effect of cognitive fluency (linguistic resources and processing speed) on the L1-L2 fluency relationship, demonstrating significant effects for the dimension of speed fluency, but not for breakdown or repair dimensions.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Suzuki and Kormos (2024) source

  • Classified as probably not a substantial claim.

    Premisecitation

    Duran-Karaoz and Tavakoli (2020) found statistically significant moderate to strong correlations between L1 and L2 especially for breakdown and repair fluency measures.

    “statistically significant moderate to strong correlations between L1 and L2 were found especially for breakdown and repair fluency measures”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Duran-Karaoz & Tavakoli, 2020 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation

    The fluency measures presented in Table 1 were chosen based on previous studies on monologic and dialogic fluency.

    “The fluency measures presented in Table 1 were chosen based on previous studies on monologic and dialogic fluency (see, e.g., De Jong, 2018;Peltonen, 2017Peltonen, , 2020;;Tavakoli, 2016;Witton-Davies, 2014).”
    Quote in the paperNot a substantial claim1 of 3 sources checked
    • cites De Jong, 2018 source
    • cites Peltonen, 2017 source
    • cites Tavakoli, 2016 source

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    LexTALE is a widely used, validated vocabulary test in SLA research, having demonstrated substantial correlations with overall proficiency in English.

    “LexTALE is a widely used, validated vocabulary test in SLA research, having demonstrated substantial correlations with overall proficiency in English (see Lemhöfer & Broersma, 2012).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Lemhöfer & Broersma, 2012 source

      The Abstract reports that LexTALE predicted English vocabulary knowledge and correlated substantially with a measure of general English proficiency in Dutch and Korean L2 speakers. The Discussion’s summary calls it a valid assessment tool, but another Discussion passage says the authors hoped LexTALE *would become* widely used; this paper does not establish that it was already widely used in SLA research. (LLM, conf=0.89)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Findingown data

    The final model predicting mean length of L2 SPs was highly significant and explained 61% of the variance (multiple R2=.62, adjusted R2=.61, F(3,88)=47.72).

    “The model was highly significant (p < .0001)and performed very well by explaining 61% of the variance in the data (multiple R 2 = .62,adjusted R 2 = .61,F(3, 88) = 47.72).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Performances were, on average, somewhat more fluent in the L1 Finnish data regarding articulation rate (AR) and speech rate (SR), while the patterns are less clear for the breakdown and repair dimensions.

    “As can be seen from Table 2, the performances were, on average, somewhat more fluent in the L1 Finnish data regarding articulation rate (AR) and SR (speed and composite dimensions), while the patterns are less clear for the breakdown (the two SP measures) and repair dimensions.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    In total, 74% of participants represented the C1/C2 level, with the remaining 26% representing the lower B2 level.

    “In total, 74% of the participants represented the C1/C2 level (scores above 80%), with the remaining 26% representing the lower B2 level (scores between 60% and 80%).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Task mode was not a significant predictor for the final model predicting mean SP length in L2 and was therefore not included in the final model.

    “Note that this time, task mode was not a significant predictor for the final model predicting mean SP length in the L2 and was therefore not included in the final model.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The final model for L2 SPs per minute included two main effects without an interaction: L1 SPs per minute and task mode.

    “The final model consisted of two main effects without an interaction between the two, the main effects being the number of SPs per minute in the L1 and the task mode, as summarized in Table 4 and illustrated in Figure 2.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Task mode did not show impact on SP duration or the repair fluency dimension.

    “The findings regarding task mode effects are somewhat more complex, as task mode showed the most prominent impact on the speed and composite dimensions, along with the SP frequency aspect of the breakdown fluency dimension, but not SP duration or the repair fluency dimension.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    L2 proficiency had a weaker effect than expected, only playing an interacting role in predicting the mean SP length in the L2.

    “In addition, L2 proficiency turned out to have a weaker effect than we had expected, only playing an interacting role in predicting the mean SP length in the L2.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Performing in the monologic task mode was associated with a significant decrease in L2 SR compared to the dialogic task mode (β=-10.58, SE=4.45, t=-2.38, p=.020); participants' L2 SR in the monologic task was predicted to be on average 10.58 syllables lower than in the dialogic task mode.

    “In contrast, performing in the monologic task mode was associated with a significant decrease in the outcome compared to the reference level (β = -10.58,SE = 4.45, t = -2.38,p = .020).”
    • Also stated in: § Composite fluency (SR) · hedged
      “This suggests that the participants' L2 SR in the monologic task was predicted to be, on average, 10.58 syllables lower than that in the dialogic task mode”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    L1 SR had a significant positive effect on L2 SR (β=0.47, SE=0.05, t=9.00, p<.001); for each one-syllable increase in L1 SR, L2 SR increased by approximately 0.47 syllables per minute of total time, holding all else constant.

    “The model revealed a significant positive effect of the L1 SR (β = 0.47, SE = 0.05, t = 9.00, p < .001)”
    • Also stated in: § Composite fluency (SR) · plain
      “for each one-syllable increase in the L1 SR, the L2 SR increased by approximately 0.47 syllables per minute of total time, holding all else constant”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    There was a significant interaction between L1 pause length and L2 proficiency on mean length of L2 SPs, with the positive connection between L1 mean SP length and LexTALE scores becoming stronger as LexTALE scores increased (β=0.03, SE=0.01, t=3.43, p<.001).

    “as well as a significant interaction between the two (β = 0.03, p < .001)”
    • Also stated in: § Breakdown fluency (SPs per minute and the mean length of SPs) · hedged
      “Figure 3 illustrates that the connection between the L1 mean length of SPs and LT scores was generally positive for all learners, but it becomes much stronger with the learners' increasing LT scores (β = 0.03, SE = 0.01, t = 3.43, p < .001).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Task mode had a significant effect on L2 SP frequency (β=0.15, SE=0.06, t=2.72, p=.008); participants produced on average 0.15 logged units more L2 SPs per minute (roughly 16% more) in the monologic condition than in the dialogic condition.

    “Task mode also had a significant effect on L2 SP frequency (β = 0.15, SE = 0.06, t = 2.72, p = .008).”
    • Also stated in: § Breakdown fluency (SPs per minute and the mean length of SPs) · plain
      “Participants produced, on average, 0.15 (logged) units more L2 SPs per minute (which roughly transforms to 16% more) in the monologic condition than in the dialogic condition.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The final model for L2 AR included two main effects, but the interaction between the two factors was not significant and was deleted from the model.

    “It included two main effects, but the interaction between the two factors was not significant and therefore deleted from the model.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The final model predicting L2 AR was highly significant (p < .0001) and explained 54% of the variance (multiple R2 = .55, adjusted R2 = .54, F(2, 82) = 54.24).

    “The final model that predicted L2 AR in syllables per minute of speaking time was highly significant (p < .0001)and explained 54% of the variance of the data (multiple R 2 = .55,adjusted R 2 = .54,F(2, 82) = 54.24).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Task mode was not a significant predictor of L2 repair fluency and was deleted during model selection.

    “Note that the task mode was not a significant predictor of L2 repair fluency and had to be deleted during the model selection process.”
    • Also stated in: § Discussion · plain
      “task mode had comparatively weaker effects and was also excluded from the final model for L2 self-repetitions.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The final model predicting L2 SPs per minute was highly significant and explained 45% of the variance (multiple R2=.47, adjusted R2=.45, F(2,89)=38.96).

    “The final model was highly significant (p < .0001)and performed very well by explaining 45% of the variance in the data (multiple R 2 =.47, adjusted R 2 = .45,F(2, 89) = 38.96).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    L1 SPs per minute had a significant positive effect on L2 SPs per minute (β=0.63, SE=0.08, t=7.62, p<.001); a one-unit increase in logged L1 SPs was associated with a 0.63-unit increase in logged L2 SPs.

    “there was a significant positive effect of L1 SPs (β = 0.63, SE = 0.08, t = 7.62, p < .001).”
    • Also stated in: § Breakdown fluency (SPs per minute and the mean length of SPs) · hedged
      “This indicates that individuals who produced more SPs in their L1 were also predicted to produce more in their L2.”
    • Also stated in: § Breakdown fluency (SPs per minute and the mean length of SPs) · hedged
      “Specifically, a one-unit increase in the number of SPs in the L1 (logged) was associated with a 0.63 unit increase in the L2 (logged), suggesting a strong within-speaker correlation in pause behavior across the two languages.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The final model predicting L2 SR was highly significant and explained 50% of the variance (multiple R2=.51, adjusted R2=.50, F(2,89)=46.57).

    “The final model to predict L2 SR was also highly significant (p < .0001)and reached a comparatively high explanatory power with 50% (multiple R 2 = .51,adjusted R 2 = .50,F(2, 89) = 46.57).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Kahng (2020) found moderate to strong correlations between the majority of examined L1 and L2 fluency measures, strongest for mean silent pause duration r = .57.

    “She found moderate to strong correlations between the majority of the examined L1 and L2 fluency measures (strongest correlation found for mean silent pause duration, r = .57)”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Kahng (2020) source

  • Probably not a substantial claim: may not pass S1 (asserted).

    Premisecitation

    Dialogic contexts might facilitate fluent speech production.

    “While some previous studies exploring task mode effects on L2 speech fluency have suggested that dialogic contexts might facilitate fluent speech production (e.g., Tavakoli, 2016;Witton-Davies, 2014)”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Tavakoli, 2016 source
    • cites Witton-Davies, 2014

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Premisecitation

    Pérez Castillejo and Urzua-Parra (2023) replicated Huensch and Tracy-Ventura's findings for speed and repair fluency measures, as well as silent pause duration, but results concerning silent and filled pause frequency were different.

    “Huensch and Tracy-Ventura's (2017) findings were replicated for speed and repair fluency measures, as well as silent pause duration, but the results concerning silent and filled pause frequency were different (Pérez Castillejo & Urzua-Parra, 2023).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Pérez Castillejo & Urzua-Parra, 2023 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Kahng's stepwise multiple regression showed for most L2 fluency measures, both L2-specific cognitive fluency measures and the corresponding L1 fluency measure were significant predictors.

    “the stepwise multiple regression analyses showed that for most L2 fluency measures, both L2-specific cognitive fluency measures and the corresponding L1 fluency measure were found to be significant predictors.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Kahng (2020) source

  • May combine two claims.

    Interpretationcitation

    L2 fluency measures may not be as straightforward indicators of L2 proficiency as previously thought but can be prone to influences from the speaker's personal speaking style.

    “That is, L2 fluency measures may not be as straightforward indicators of L2 proficiency as previously thought but can rather be prone to influences from the speaker's personal speaking style (i.e., the temporal features in their L1 speech).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Premisenone given

    The bulk of L2 speech fluency research has focused on monologic speech.

    “the bulk of L2 speech fluency research has focused on monologic speech, such as picture descriptions based on comic strip prompts.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Premisenone given

    Previous task-based studies on fluency have rarely included L1 speech data from participants along with their L2 production.

    “Importantly, previous taskbased studies on fluency have rarely included L1 speech data from the participants along with their L2 production.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    Huensch and Tracy-Ventura's findings underscore complex interplay between L1 fluency measurements, cross-linguistic differences, and L2 proficiency in influencing L2 fluency.

    “their findings underscore the complex interplay between L1 fluency measurements, cross-linguistic differences, and L2 proficiency in influencing L2 fluency.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Huensch and Tracy-Ventura (2017)

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Premisecitation

    The overall finding is in line with the bulk of L2 speech fluency research that has demonstrated clearer L1-L2 links, and impact of other variables, on speed and breakdown aspects of pausing, while the repair dimension is not equally well understood.

    “This overall finding is in line with the bulk of L2 speech fluency research that has demonstrated clearer L1-L2 links, and impact of other variables, on speed and breakdown aspects of pausing, while the repair dimension is not equally well understood (see, e.g., Gao & Sun, 2024;Peltonen, 2020).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Gao & Sun, 2024 source
    • cites Peltonen, 2020

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Monologic speech samples were transcribed and double-checked by a group of research assistants.

    “were transcribed and double-checked by a group of research assistants as part of course work.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    This study is among the first to show that L1 fluency impacts all dimensions of fluency and that task mode effects differ across fluency dimensions.

    “As studies exploring both L1 speech fluency and task mode effects are rare, our study is among the first to show that while L1 fluency impacts all dimensions of fluency, the effect of task mode differs across different dimensions of fluency.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Studies exploring both L1 speech fluency and task mode effects are rare.

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    All model assumptions were sufficiently met.

    “We made sure that all model assumptions were sufficiently met.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Gao and Sun (2024) meta-analysis found the degree of L1 influence varies across fluency dimensions, strongest for breakdown and weakest for repair.

    “the findings of the meta-analysis suggest that the degree of L1 influence varies across different dimensions of fluency, strongest effects being found for the breakdown fluency dimension and the weakest for repair fluency (Gao & Sun, 2024).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Gao & Sun, 2024 source

  • May combine two claims.

    Interpretationreasoning

    There is compelling evidence that L1 speaking style and task mode impact L2 speech fluency.

    “Taking together the research discussed above, there is compelling evidence demonstrating that L1 speaking style and task mode impact L2 speech fluency”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Michel (2011) found L2 learners produced faster speech and fewer filled pauses and repairs in the dialogic condition.

    “Michel (2011) found that the L2 learners produced faster speech and fewer filled pauses and repairs in the dialogic condition.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Michel (2011) source

  • May combine two claims.

    Premisecitation

    Tavakoli (2016) found statistically significantly more fluent performance in the dialogue on speed, length-based breakdown, and composite measures, but not on frequency or location of silent pauses.

    “The results demonstrated statistically significantly more fluent performance in the dialogue on speed (articulation rate), length-based breakdown (mean length of silent pauses), and composite (speech rate, mean length of run, phonationtime ratio) measures, but not on the frequency or location of silent pauses”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Tavakoli (2016) source

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Particular attention was paid to the comparability of the measures across the two modes.

    “Particular attention was paid to the comparability of the measures across the two modes.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    When predictor variables were non-normally distributed, they were logged.

    “When predictor variables were non-normally distributed, they were logged.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    The order of prompts and languages was counterbalanced in the monologic data collection.

    “The order of the prompts and languages was counterbalanced, and the speech samples were audio-recorded.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    The L1 effect on mean length of L2 SPs is barely measurable for learners with a LexTALE score of 60 (B2), but becomes very strong for learners with scores of 80, 90, and 100 (C1/C2).

    “While the L1 effect is barely measurable for learners with a LT score of 60 (indicating level B2 in the CEFR), it becomes very strong for learners with scores of 80, 90, and 100 (indicating level C1/C2 in the CEFR).”
    Quote in the paperSubstantial claim
    • Rests on an assumption: LexTALE scores of 60, 80, 90, and 100 indicate CEFR levels B2, C1/C2 respectively.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    The order of task prompts and languages was counterbalanced in the dialogic data collection to avoid task order effects.

    “As with the monologic task, the order of the task prompts and the languages was counterbalanced in the data collection to avoid task order effects.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    Open tasks exhibit stronger L1-L2 correlations.

    “their finding of open tasks exhibiting stronger L1-L2 correlations”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Gao & Sun, 2024 source

  • Classified as probably not a substantial claim.

    Study design and conductcitation

    The measures were selected to represent all three fluency dimensions suggested by Skehan (2009, 2014) and one widely used composite measure (speech rate, SR) that combines the speed and breakdown dimensions.

    “To offer as comprehensive view of speech fluency as possible, the measures were selected to represent all three fluency dimensions suggested by Skehan (2009Skehan ( , 2014)), along with one widely used composite measure (speech rate, SR) that combines the speed and breakdown dimensions.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Skehan (2009Skehan ( , 2014)) source

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    Silent pause annotations were manually checked by research assistants, who also manually annotated self-repetitions.

    “The silent pause annotations were manually checked by the research assistants, who also manually annotated the self-repetitions in Praat.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Model performance was assessed through a visual inspection of the residuals and Shapiro-Wilk tests for normal distribution of the residuals.

    “Model performance was assessed through a visual inspection of the residuals and Shapiro-Wilk tests for normal distribution of the residuals.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    All numeric variables were checked for normality with Shapiro-Wilk tests and a visual inspection of histograms and ecdf plots.

    “All numeric variables were checked for normality with Shapiro-Wilk tests and a visual inspection of histograms and ecdf plots.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    Dialogic speech samples were transcribed and double-checked by two MA students, followed by final checks by the first author.

    “were transcribed and double-checked by two MA students of English, followed by final checks by the first author.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Gilabert et al. (2011) found weaker correlations between fluency and L2 proficiency in the dialogic mode compared to the monologic mode.

    “which may account for previous findings of weaker correlations between fluency (measured with speech rate and the frequency of filled pauses) and L2 proficiency in the dialogic mode compared to the monologic mode (Gilabert et al., 2011).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Gilabert et al., 2011 source

  • Classified as probably not a substantial claim.

    Interpretationcitation

    Alignment effects associated with interactive settings could mask or influence the L1-L2 fluency connection.

    “even with potential alignment effects associated with interactive settings that could”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Gilabert et al., 2011 source
    • cites Michel, 2011 source

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

    Study design and conductnone given

    The choices for the monologic and dialogic task prompts were motivated by the respective research traditions on monologic and dialogic fluency, enabling high comparability with previous research.

    “while the choices for the monologic and dialogic task prompts were motivated by the respective research traditions on monologic and dialogic fluency, enabling high comparability with previous research”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    The decision to include between-turn pauses rather than exclude them could have impacted the results.

    “as we opted for measurements including between-turn pauses rather than excluding them, it should be noted that this decision could have impacted the results.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationown data

    The findings complement and extend previous findings on L1 speaking style effects in monologues.

    “our findings complement and extend these previous findings”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Prior studies in this field have mainly revealed effects of L1 speaking style in monologues.

  • May combine two claims.

    Premisecitation

    Tavakoli (2016) found the SPs to be shorter in dialogue but no difference in the frequency of SPs across the two modes.

    “while Tavakoli (2016) found the SPs to be shorter in dialogue but no difference in the frequency of SPs across the two modes”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Tavakoli (2016) source
56 of 56

  • The paper relies on this without support.

    The dialogic task is more open in nature than the monologic one.

    “as the dialogic task is more open in nature than the monologic one.”

  • The paper relies on this without support.

    LexTALE scores of 60, 80, 90, and 100 indicate CEFR levels B2, C1/C2 respectively.

    “While the L1 effect is barely measurable for learners with a LT score of 60 (indicating level B2 in the CEFR), it becomes very strong for learners with scores of 80, 90, and 100 (indicating level C1/C2 in the CEFR).”

  • The paper relies on this without support.

    Studies exploring both L1 speech fluency and task mode effects are rare.

    “As studies exploring both L1 speech fluency and task mode effects are rare”

  • The paper relies on this without support.

    Prior studies in this field have mainly revealed effects of L1 speaking style in monologues.

    “As the studies in this field have, so far, mainly revealed effects of L1 speaking style in monologues”

  • The paper relies on this without support.

    Finnish and English belong to two different language families.

    “the two languages belong to two different language families”
5 of 5

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Monologue articulation-rate coefficient differs between text and table

    Minor

    The text reports the task-mode coefficient as −7.17, while Table 3 reports −7.18 at the same precision.

1 of 1

Cites

Flagged first, then by citations

Research works printed but not linked: 7

  1. Jiránková, 2019, Widening the scope of learner corpus research. Selected papers from the fourth learner corpus research conference, 19
  2. Witton-Davies, G. (2014). The study of fluency and its development in monologue and dialogue [Doctoral dissertation]. Lancaster University.
  3. 10.48316/2uk3V-ISQYH · DOI
  4. Lehtilä, E. (2021). Comparing L2 speech fluency in monologue and dialogue: A quantitative study of Finnish upper secondary school learners of English [MA thesis, University of Turku]. UTUPub. https://www.utupub.fi/handle/10024/151469
  5. 2024, R: A language and environment for statistical computing
  6. Peltonen, P. (2020). Individual and interactional speech fluency in L2 English from a problem-solving perspective: A mixed-methods approach [Doctoral dissertation, University of Turku]. UTUPub. http://urn.fi/URN:ISBN:978-951-29-8137-3
  7. 2001, Common European framework of reference for languages: Learning, teaching, assessment

Cited by

Sorted by citations

Authors
Peltonen, P., Götz, S., & Lintunen, P.
Affiliations
  • University of Turku (FI)
  • Philipps University of Marburg (DE)
Corresponding author
Peltonen, Pauliina
ORCID
Venue
Studies in Second Language Acquisition
Publisher
Cambridge University Press (CUP)
Published
2025-10-08
Volume
47
Issue
5
Pages
1328-1348
ISSN
  • 0272-2631 (ISSN-L)
  • 1470-1545
DOI
10.1017/s0272263125101289
OpenAlex
W4414926633
Semantic Scholar
fb11b6f2909dba78d93c5e5ee58d4d6ca98668d5
Cited by
1
References
48
Citations by year
2026: 1
FWCI
3.73
Type
journal article
Language
en
Open access
Licence
Locations
  • Studies in Second Language Acquisition (publishedVersion, cc-by)
  • UTUPub (University of Turku) (submittedVersion)
Funders
Kulttuurin ja Yhteiskunnan Tutkimuksen Toimikunta (331903, 363643)
Topics
  • Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Phonetics and Phonology Research
  • Social Sciences › Psychology › Developmental and Educational Psychology › Second Language Acquisition and Learning
Keywords
second language fluency, monologic speech, dialogic speech, second language proficiency, speech rate, Finnish learners of English, speaking skills

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-19.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-19.

Cited sources are checked by gpt-6-sol.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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