To ensure smooth communication and collaboration, here are some troubleshooting tips to address common issues:
Check Internet Connection: Verify that you have a stable and reliable internet connection. Use a wired connection when possible, as it tends to be more stable than Wi-Fi. If using Wi-Fi, make sure you have a strong signal.
Update the Browser or App: Ensure that you are using the latest version of the web browser. Developers frequently release updates to address bugs and improve performance.
Clear Browser Cache: Sometimes, cached data can cause conflicts or issues. Clear the browser cache and cookies before joining the meeting.
Test Audio and Video: Before the meeting, check your microphone and camera to ensure they are working correctly. If you are a speaker, you can click on "Start Practice Session" button test to ensure audio and video devices are functioning.
Close Other Applications: Running multiple applications in the background can consume system resources and lead to performance issues. Close unnecessary apps to free up resources for the Dryfta meeting platform.
Restart Your Device: If you encounter persistent issues, try restarting your computer or mobile device. This can help resolve various software-related problems.
Use Supported Browsers: Ensure you are using a browser supported by the meeting platform. Recommended browsers: Chrome, Firefox, Edge, and Brave.
Allow Necessary Permissions: Make sure the Dryfta meeting platform has the required permissions to access your microphone, camera, and other necessary features.
Disable VPN or Firewall: Sometimes, VPNs or firewalls can interfere with the connection to the meeting platform. Temporarily disable them and see if the issue persists.
Switch Devices: If possible, try joining the meeting from a different device to see if the problem is specific to one device.
Reduce Bandwidth Usage: In cases of slow or unstable internet connections, ask participants to disable video or share video selectively to reduce bandwidth consumption.
Update Drivers and Software: Ensure your operating system, audio drivers, and video drivers are up to date. Outdated drivers can cause compatibility issues with the Dryfta meeting platform.
Contact Support: If none of the above steps resolve the issue, reach out to the platform's support team. They can provide personalized assistance and troubleshoot specific problems.
By following these troubleshooting tips, you can tackle many common problems encountered on Dryfta meeting platform and have a more productive and seamless meeting experience.
What is L2 interactional fluency? Current debates and future directions linking theory, method, and assessment
Oral Presentation[SYMP36] Fluency as a multilingual practice: Concepts and challenges03:00 PM - 06:00 PM (Europe/Amsterdam) 2023/07/19 13:00:00 UTC - 2024/07/19 16:00:00 UTC
Fluency is widely studied as a key dimension of second language (L2) oral proficiency. The majority of studies examine L2 speech fluency as a "narrow" construct (Lennon, 1990), often assessed from an individual speaker's perspective, based on monologic speech samples testing underlying processing (cognitive fluency), and referring to L1 standard norms (Magne et al., 2019). Recent interest has shifted to exploring fluency in dialogic contexts (e.g., Tavakoli, 2016; Peltonen, 2020; Wright, 2021) and evaluating L2 speech within a more inclusive perspective using plurilingual norms (e.g., Tavakoli and Wright, 2020). However, so far, there have been few theoretical accounts of defining fluency in an interactional context (but see McCarthy, 2010; Feng, 2022), and discussions on the methodology of examining L2 interactional fluency are scarce.
In this presentation, we discuss L2 interactional fluency from a theoretical and methodological perspective. First, we provide an overview of current approaches to L2 interactional fluency, examining L2 fluency research conducted in interactional settings. Our focus is on the definitions and methods (fluency measures) applied to L2 interactional fluency in these studies. Mixed-methods approaches can be particularly useful in the analysis of multifunctional fluency-related features and can facilitate approaches to fluency that view fluency and disfluency as a continuum (interfluency, Tavakoli & Wright, 2020). We also discuss L2 interactional fluency and its definitions in relation to closely related constructs, such as interactional competence and alignment. We conclude our presentation with an overview of future directions and implications for L2 interactional fluency research, assessment, and teaching, advocating for multimodal measures (Peltonen, 2020b), within a more diverse variationist or "pluriglossic" approach (Wright, 2022).
References
Feng, R. (2022). Cognitive factors influencing utterance fluency in L2 dialogues: Monadic and non-monadic perspectives. Frontiers in Psychology. doi: 10.3389/fpsyg.2022.926367
Magne, V., Suzuki, S., Suzukida, Y., Ilkan, M., Tran, M., & Saito, K. (2019). Exploring the dynamic nature of second language listeners' perceived fluency: A mixed‐methods approach. TESOL Quarterly, 53(4), 1139–1150.
McCarthy, M. (2010). Spoken fluency revisited. English Profile Journal, 1(1), 1–15.
Peltonen, P. (2020a). Individual and interactional speech fluency in L2 English from a problem-solving perspective: A mixed-methods approach. University of Turku. https://urn.fi/URN:ISBN:978-951-29-8137-3
Peltonen, P. (2020b). Gestures as fluency-enhancing resources in L2 interaction: A case study on multimodal fluency. In P. Lintunen, M. Mutta, & P. Peltonen (Eds.), Fluency in L2 learning and use (pp. 111–128). Multilingual Matters.
Tavakoli, P. (2016). Fluency in monologic and dialogic task performance: Challenges in defining and measuring L2 fluency. IRAL, 54, 133–150.
Tavakoli, P., & Wright, C. (2020). Second language speech fluency: From research to practice. Cambridge University Press.
Wright, C. (2021). Effects of task type on L2 Mandarin fluency development. Journal of Second Language Studies, 3(2), 157–179.
Wright, C., & Tavakoli, P. (2016). New directions and developments in defining, analyzing and measuring L2 speech fluency. IRAL, 54, 73–77.
Wright, C. (2022). Diversity in learning, diversity in teaching: The Pluriglossic approach to evaluating interfluency development. Journal of European Second Language Association (in prep).
Presenters Pauliina Peltonen Postdoctoral Researcher, University Of Turku Co-authors
What temporal and dialogic features distinguish between second language oral proficiency levels? The case of oral proficiency interview
Oral Presentation[SYMP36] Fluency as a multilingual practice: Concepts and challenges03:00 PM - 06:00 PM (Europe/Amsterdam) 2023/07/19 13:00:00 UTC - 2024/07/19 16:00:00 UTC
Given the essential role of oral fluency in second language (L2) pedagogy and assessment, scholars have examined L2 oral fluency as one of the primary constructs of oral proficiency (Tavakoli & Hunter, 2018; Tavakoli and Wright, 2020). Previous studies have attempted to identify temporal characteristics of speech that play an essential role in listeners' perception and proficiency assessment, by investigating oral fluency from three different perspectives (Segalowitz, 2010, 2016)-listener-based perceptions (i.e., perceived fluency), objective temporal features (i.e., utterance fluency) and underlying linguistic knowledge (i.e., cognitive fluency). Although these lines of fluency research have offered insights into the construct definition and valid operationalization of L2 oral fluency, L2 fluency research has suffered from the lack of research looking into fluency in dialogic speaking tasks. Fluency in dialogic speaking tasks can be a theoretically different construct from the one in monologic tasks (Peltonen, 2021; Suzuki et al., 2021; Tavakoli, 2016). In addition, to offer insights from previous studies into setting realistic curricular objectives for speaking skills, it is essential to understand which aspects of oral fluency tend to be developmentally ready according to different proficiency levels (cf. Baker-Smemoe et al., 2014; Tavakoli et al., 2020). Taken together, the current study aims to fill this gap in L2 fluency research, examining what temporal and dialogic features can differentiate between the CEFR levels of fluency, using interactional speech data.
A total of 80 Japanese learners of English were recruited, and they completed an oral proficiency interview consisting of seven topics with varying levels of difficulty, such as social media and globalization, determined by the CEFR manual (Council of Europe, 2018). All the interview sessions were conducted via the video conferencing tool, Zoom. Their interview data were annotated for a range of disfluency features, including silent pauses, filler, and self-repair. We calculated a comprehensive set of utterance fluency measures, following previous studies (De Jong et al., 2013; Suzuki et al., 2021; Tavakoli et al., 2020). Three raters received a training session about using the CEFR descriptor of oral fluency and then independently assigned fluency scores (A1 to C2) to each speaker. We employed a Rasch analysis to determine students' CEFR level while controlling for the scoring variability across raters. As a result, our participants' CEFR levels ranged between A2 to C1 levels.
A series of Bayesian ANOVAs showed the main effects of proficiency levels on most temporal and dialogic features, whereas end-clause pause duration and between-turn pause duration may not differ across four CEFR levels. The results of post-hoc tests indicated that articulation rate may distinguish higher proficiency levels (B1 vs. B2, B2 vs. C1), while mid-clause pause ratio can differ between all the adjacent levels from A2 to C1 level. Meanwhile, between-turn pause ratio and mean length of turn only differed between lower levels of proficiency (A2 vs. B1). We will discuss these findings in relation to a potential developmental pattern of dialogic fluency performance in light of L2 speech production mechanisms.
Presenters Shungo Suzuki Assistant Research Professor, Waseda University Co-authors
Multilingual speakers’ perceived fluency: How information about L1 speaking style affects L2 and L3 fluency assessment
Oral Presentation[SYMP36] Fluency as a multilingual practice: Concepts and challenges03:00 PM - 06:00 PM (Europe/Amsterdam) 2023/07/19 13:00:00 UTC - 2024/07/19 16:00:00 UTC
Speech fluency is an essential part of second language (L2) proficiency and assessment. In second language acquisition (SLA) research, fluency has traditionally been examined with respect to three dimensions: objective temporal features of speech (utterance fluency), subjective listener ratings of fluency (perceived fluency), and cognitive processes underlying speech production (cognitive fluency; Segalowitz, 2010). There has also been a growing research interest in the connections between first language (L1) and L2 utterance fluency (e.g., Duran-Karaoz & Tavakoli, 2020; Peltonen, 2018), but the potential influence of L1 speaking style on L2 perceived fluency has not yet been empirically investigated. In addition, examining learners' speech fluency across multiple target languages (L2, L3…) has thus far received little attention (for an exception, see Peltonen & Lintunen, 2022). The present study addresses these gaps by examining the effects of individual speaking style on both L2 and L3 perceived fluency from a multilingual perspective. The study is part of the project "Fluency across Multilingual Speakers" (MultiFluency; funded by the Swedish Cultural Foundation in Finland). The first data set in the study consists of speech samples from Finnish-speaking (n = 20) university students, who all provided monologue samples in Finnish (L1), English (L2), and Swedish (L3). The second data set consists of fluency assessments of the L2 and L3 samples. The study employs a unique research design where half of the raters base their assessments solely on L2/L3 speech (control group), while half have access to the learners' L1 speech (experimental group). The raters also provide comments on how the L1 speech samples affected their ratings of the L2 and L3 samples. The research questions are: 1. To what extent are L2 English and L3 Swedish utterance fluency measures correlated with L2 and L3 fluency ratings? 2. How does information about learners' L1 speaking style influence the raters' L2 and L3 fluency assessments? 3. Which features and themes emerge in the raters' comments regarding the influence of the L1 speech samples on the L2 and L3 fluency assessments? The analyses focus on the correlations between fluency ratings and utterance fluency measures based on the speech samples (articulation rate and frequency and duration of mid-clause silent pauses and corrections) and the differences in ratings between rater groups (experimental vs. control group) across the two target languages (English and Swedish). The raters' comments are also analyzed qualitatively. The assessment data collection will be completed in autumn 2022, and the results will be discussed in the presentation. References: Duran-Karaoz, Z. & Tavakoli, P. (2020). Predicting L2 fluency from L1 fluency behavior: The case of L1 Turkish and L2 English speakers. Studies in Second Language Acquisition, 42(4), 671–695. Peltonen P. (2018). Exploring connections between first and second language fluency: A mixed methods approach. The Modern Language Journal, 102(4), 676–692. Peltonen, P. & Lintunen, P. (2022). Multilingual speakers' L1, L2, and L3 fluency across languages: A study of Finnish, Swedish, and English. Nordand, 17, 48–63. Segalowitz, N. (2010). The cognitive bases of second language fluency. Routledge.
The interplay between L2 speech fluency and L2 willingness to communicate in monologue speech
Oral Presentation[SYMP36] Fluency as a multilingual practice: Concepts and challenges03:00 PM - 06:00 PM (Europe/Amsterdam) 2023/07/19 13:00:00 UTC - 2024/07/19 16:00:00 UTC
Speech fluency is a manifestation of cognitive speech production processes associated with automatic and on-line processing (Kormos, 2006). It is shaped by individual learner characteristics (e.g. Segalowitz, 2010), such as an L2 learner's willingness to communicate in a second language (WTC), understood as an individual learner's readiness to initiate speaking in L2. Psychological, linguistic and contextual antecedents explain both stable, trait-like predisposition and dynamic, state-like nature of WTC (e.g. MacIntyre, 2020). Although trait-like and state-like WTC are complementary, trait-like WTC is more likely to explain systematic variation in speech fluency (Piechurska-Kuciel, 2018). However, speech fluency has rarely been investigated from the perspective of WTC. Moreover, the existing studies have generated inconsistent results regarding the relationship between WTC and the outcomes of L2 speaking, including speech fluency measures. On the one hand, WTC has been found a significant predictor of fluency (e.g. Nematizadeh, 2021). On the other hand, the link between WTC and speaking performance evaluated with temporal fluency measures has not been established in other research (e.g. Kim et al., 2022). These inconclusive results call for further investigations in order to gain more insights into the complex interplay of L2 speech fluency and WTC. The current study is a part of a larger Fluency and Disfluency Features in L2 English (FDF2) project and aims to investigate the relationship between L2 speech fluency and trait-like L2 WTC. Samples of L2 monologue speeches from 64 participants were analysed quantitatively for temporal fluency (speech rate, articulation rate, number of silent pauses, repetitions per minute and filled pauses per minute). The levels of the participants' trait-like L2 WTC were established with the help of an adapted version of the Willingness to Communicate Inventory (WTCI) tapping into L2 WTC and the underlying factors shaping L2 WTC (Mystkowska-Wiertelak & Pawlak, 2017). Correlational analyses were conducted between the fluency measures and L2 WTC. The analyses provided some interesting insights into intricate relationships between various fluency and dysfluency measures and L2 WTC as well as its selected antecedents. The results led to several practical implications for fluency teaching and assessment. References Kim, J., Zhao, H., & Diskin-Holdaway, C. (2022). Willingness to communicate and second language fluency: Korean-speaking short-term sojourners in Australia. Languages, 7(2), 112. Kormos, J. (2006). Speech production and second language acquisition. Mahwah, N.J.: Lawrence Erlbaum Associates. MacIntyre, P. (2020). Expanding the theoretical base for the dynamics of willingness to communicate. Studies in Second Language Learning and Teaching, 10, 111–31. Mystkowska-Wiertelak, A., & Pawlak, M. (2017). Willingness to communicate in instructed second language acquisition: Combining a macro- and micro-perspective. Bristol: Multilingual Matters. Nematizadeh, S. (2021). Willingness to communicate and second language speech fluency: an idiodynamic investigation of attractor states. Journal for the Psychology of Language Learning, 3(1), 26–49. Piechurska-Kuciel, E. (2018). Openness to experience as a predictor of L2 WTC. System 72, 190-200. Segalowitz, N. (2010). Cognitive bases of second language fluency. New York: Routledge.
Presenters Magdalena Szyszka Assistant Professor, University Of Turku, Finland; University Of Opole, Poland
Looking at the relationship between working memory and oral fluency: on the importance of the languages involved in L2 oral production
Oral Presentation[SYMP36] Fluency as a multilingual practice: Concepts and challenges03:00 PM - 06:00 PM (Europe/Amsterdam) 2023/07/19 13:00:00 UTC - 2024/07/19 16:00:00 UTC
Good oral production skills are fundamental to the integration of non-native speakers into their host society. In particular, L2 oral fluency (OF), i.e., the rapid, smooth, accurate translation of communicative intention during on-line processing (Lennon, 2000, p. 26; see also Segalowitz, 2010), has been shown to be of great importance in maintaining listeners' attention (Suzuki & Kormos, 2020). However, although L2 OF may largely depend on L1 OF skills (Tavakoli & Wright, 2020), it still represents a distinct challenge for L2 speakers as it requires a real-time efficient allocation of cognitive resources. Specifically, working memory (WM), which refers to the limited capacity system responsible for the temporary storage and manipulation of information (Baddeley, 2012), has been shown to be most important in speech production (Wen & Li, 2019). However, these cognitive resources are limited and vary from one speaker to another (Kormos, 2006), and may also differentially interact with language forms (Awwad & Tavakoli, 2022; Ellis & Sinclair, 1996), which can differ from the L1 to the L2. To our knowledge, no previous studies have verified whether WM interacts in a distinct manner depending on the speakers' L1 and the language used for L2 production. Therefore, the present communication reports on a study that investigated this relationship. 30 ESL French-speaking and 30 French L2 English speaking adults were subjected to a picture-based narration task in both their L1 and L2. To maximize language production, participants were given two minutes planning time (e.g., Foster & Skehan, 1996). Each narration, which lasted on average three minutes, was recorded. Participants' WM was measured using the Highest-Number Task (Oakhill et al., 2011), a numerical span test known to measure both temporary storage and manipulation of information. Fluency was holistically assessed using a flowchart using a scheme adapted from Turner and Upshur (2002). Three judges independently coded the narrations. An interrater agreement of .89 was obtained. Factorial analysis results show a distinct pattern in the mediating role of WM in the L1-L2 OF relationship. These results are discussed in light of previous studies. References Awwad, A., & Tavakoli, P. (2022). Task complexity, language proficiency and working memory: Interaction effects on second language speech performance. IRAL, 60, 169–196. Baddeley, A. D. (2012). Working memories: Theories, models, and controversies. Annual Review of Psychology, 63, 1-29. Ellis, N. C., & Sinclair, S. (1996). Working memory in the acquisition of vocabulary and syntax: Putting language in good order. Quarterly Journal of Experimental Psychology, 49, 234-250. Foster, P., & Skehan, P. (1996). The influence of planning and task type on second language performance. Studies in Second Language Acquisition, 18, 299–323. Kormos, J. (2006). Speech production and second language acquisition. Mahwah, NJ: Lawrence Erlbaum Associates. Lennon, P. (1990). Investigating fluency in EFL: A quantitative approach. Language Learning, 40, 387-417. Oakhill, J., Yuill, N. et Garnham, A. (2011). The differential relations between verbal, numerical and spatial working memory abilities and children's reading comprehension. International Electronic Journal of Elementary Education, 4, 83–106. Tavakoli, P., & Wright, C. (2020). Second language speech fluency. From research to practice Cambridge University Press. Turner, C. E., & Upshur, J. A. (2002). Rating scales derived from student samples: effects of the scale maker and the student sample on scale content and student scores. TESOL Quarterly, 36, 49–49. Segalowitz, N. (2010). Cognitive bases of second language fluency. New York: Routledge. Wen, Z., & Li, S. (2019). Working memory in L2 learning and processing. In J. Schwieter & A. Benati (Eds.), The Cambridge handbook of language learning (pp. 365-389. Cambridge University Press.
Pauliina Peltonen
Shungo Suzuki
Magdalena Szyszka