Theoretical background

With clear and correct perceptions, human can avoid doing things through emotions. With clear and correct perceptions, the human can complete their work at best. So, what is perception? As defined by Ou (2017), perception means the listener perceives something by understanding and raising awareness through sensory information; it is the process of receiving and collecting the action of taking possession. Similarly, Colman (2006, as cited in Khau et al. 2022) considered perception as a process or product of perceiving things via the human senses. According to Cambridge University Press (2022), perception is the ability to see, understand, etc. clearly. With the importance of perception, making all related stakeholders in an area perceive things similarly is indispensable.

As this study also aims to create a clear picture of oral fluency, the authors would also like to define assessment rubrics to prevent fluency from being judged or rated unfairly. According to Reddy and Andrade (2010), rubrics help students understand the targets for their learning and the quality standard required for the completion of a task. Campbell (2005) said rubrics can be also a form of e-assessment which was advocated by the instructors who said that rubrics help them grade more consistently, reliably, and effectively. Andrade and Du (2005) said that the students were found to satisfy with rubrics that are transparent and fair.

More specifically, this study hopes to see how both teachers and students perceive oral fluency so that more suitable criteria can be brought into assessing oral fluency. Thus, what is oral fluency? Fillmore (1979) stated that to talk fluently, a speaker has to be able to talk at length with few pauses and has to be able to fill time allowance with words. Another definition was suggested by Lennon (1990, as cited in Wood, 2010), who said that level of fluency is not from the speaker themselves, but from the listener’s part. Similarly, when assessing oral fluency, De Wolf et al. (2017) considered the following aspects as necessity for oral fluency: speech rate, articulation rate, number of pauses per minute, phonation-time ratio, filled pauses, dysfluencies, length of utterance and pause duration. What is more, fluency is when someone is good at what they are doing (Foster, 2020). In many cases, assessors perceived that fluency would be assessed based on native speakers’ perception of fluency in L2 speech production (Mora & Valls-Ferrer, 2012; Riggenbach, 1991).

Related studies

As the current study attempts to test how the stakeholders in the EFL context, specifically at Tra Vinh University, Vietnam, perceive oral fluency, the authors would like to read through many of the studies related to the topic. The findings and ideas can help the authors have appropriate research questions and suitable data collection tools for the study.

First, oral fluency can be perceived related to pauses, hesitation, speed rate, and dysfluency. Kormos and Dénes (2004) collected speech samples from 16 Hungarian L2 learners at two levels of proficiency assisted with computer technology. Three experienced native and three non-native teachers were chosen as judges. The source was logical cartoon strips extracted from popular English course books and the speakers were told to narrate in 2– 3 min plus a 1-min plan. It uncovered that fluency is best conceived of as fast, smooth, and accurate performance. Interestingly, the number of filled and unfilled pauses and other disfluency phenomena were not seen to affect fluency perceptions. Time needed for preparation should be brought into discussion prior to having the speaker talk and it seems that the listeners see pauses and other disfluency contexts as natural phenomena. In the same way, Sato (2014) used an individual task and an interactional task to test their oral fluency and to test their perceptions of oral fluency criteria. Four native speakers of English in the field were recruited to rate these students’ tasks. A questionnaire was used to test their perception of oral fluency and then the author continued to test their oral fluency based on four empirically based oral fluency scales. The scores were given to unpruned speech rate, pruned speech rate, individual perceived fluency, and interactional perceived fluency. The assessors used the verbal protocol method to rate 16 individual tasks and 8 interactional tasks: band 1 (e.g., In individual tasks, the speaker speaks very slowly and haltingly with long pauses—within-word and between-word, false starts, reformulations, and/or fillers. Each utterance is short, often consisting of a single word) to band 4 (e.g., The speaker produces fairly long stretches of language and each word is produced quickly—within-word. Pauses are noticeable but the number of pauses between-word is small. In regard to individual performance, the assessors perceived pauses as indications of inability to phrase utterances, insufficient time to formulate sentences, or an inability to get things right the first time. This study has provided the field with clear ideas of criteria used to rate fluency and this set of ideas can be used as a reference. Similarly, Préfontaine et al. (2016) had 40 L2 voluntary participants with different levels of proficiency in French for the study. Eleven French native speakers were chosen as raters. In task 1, the participants told a story with six random pictures, allowing creative performance. In task 2, the participants retold a story about a horseback riding accident from a short text in English. In task 3, an 11-cartoon strip was provided and the participants narrated the story with a clear event sequence. All the three speech samples were analyzed using PRATT, tracking utterance fluency temporal variables. The assessors referred to L2 fluency Assessment Grid (Préfontaine et al. (2016)) to rate the speech samples. It found that raters’ judgments of fluency according to the descriptors in the grid, speed, and pausing were influenced much similarly to the utterance fluency variables, of which mean length of runs and articulation were found to be the most influential factors in raters’ judgments. Again, with clear rating scales, the assessors can do their best and with support from the speech analysis software more evidence can be collected for perception of oral fluency. Van Os et al. (2020) tested the effect of speed rate and delay between questions and answers (various gaps and overlaps) in a dialogue format on fluency judgment for both native and nonnative speakers’ answers to questions. It found that more fluent speakers could deliver faster speech while less fluent speakers delivered slow speech. It also uncovered that an interaction effect between speech rate and delay step. In terms of fast speech judgment, overlaps with an interlocutor was rated as less fluent than gaps (a case of native speakers) while regarding slow speech, overlaps were rated as more fluent than gaps (a case of both native and nonnative speakers). Nonetheless, it can be also noted that when speakers are interacting with each other, one can influence the other’s ideas, so speed rate produced by involved speakers can be influenced, too. Suzuki et al. (2021) conducted a meta-analysis to examine the relationship between utterance fluency and listener-based judgments of perceived fluency by analyzing primary studies. They analyzed 263 effect sizes from 22 studies to calculate the mean effect sizes of the links between utterance and perceived fluency. Perceived oral fluency was strongly associated with speed and pause frequency, moderately with pause duration, and weakly with repair fluency. Moderator analyses uncovered that the utterance–perceived fluency is affected by methodological variables related to how speech samples are prepared for listeners’ judgments and how listeners’ attention is directed in evaluations of fluency.

Second, oral fluency can be influenced by text structure and text complexity, and language proficiency. Skehan and Foster (1999) found task structure and processing conditions on narrative retellings influence oral fluency. They used series Mr. Bean as source for narrative tasks. Two tasks were chosen: a relatively structured narrative and a relatively unstructured narrative. To influence the processing load of the task, the two tasks were performed in four conditions from the most demanding to the least demanding. The degree of task structure was found to mainly influenced fluency; conditions of performing the task influenced complexity and task structure; task preparation affected accuracy. This can be true in reality as more demanding task structures can cause the speaker lots of hesitation or pauses for ideas and language choice and time for preparation prior to speak is not less important. Skehan et al. (2016) carried out a study on comparing first and second language fluency during narrative retelling tasks of varying degrees of tightness in structural organization and specifically investigated a distinction between discourse-based and clause-based fluency. The authors utilized four Mr. Bean video excerpts as the source: It started from no tight structure to the tightest structure and the strongest causal links among parts. Twenty-eight English-low intermediate NNSs and 28 NS speakers were the narrators who watched the videos and narrated. They were tested on fluency, structural complexity, and lexis. They found that if speakers (NNS and NS speakers) produced multi-clausal utterances, they tended to pause less often in the four tasks. In terms of complexity measures, only NSs tended to increase reformulation, repetition, and filled pauses, and mid-clause pausing when producing longer clauses. With regard to lexical measures, only NNS showed less ‘repair’, generally and slightly increased clause-boundary pausing, producing greater fluency. For lexical sophistication, the NS group experienced less frequent lexical items, associated with more end-clause pausing. Again, text structures and text complexity were brought into discussion. Bui and Huang (2018) employed 58 participants speaking Cantonese with similar experience in studying L2 (reaching B2 English according to CEFR). They were asked to perform two very similar tasks about a discussion of a computer virus and a biological virus. Their tasks were recorded and coded for analysis. It uncovered that knowledge of the topic influenced how well they performed. Topic familiarity was predicted to affect their speed and mid-clause pausing. Nonetheless, it should have employed a prescribed rubric and the performance should be rated by trained raters. Zhang (2009) found the majority of Chinese learners of English were unable to speak fluently as they were not exposed to appropriate input and output during language learning. Moreover, while speaking they were thinking more about vocabulary and grammar, so they were not able to speak fast. Low language proficiency also influenced these learners. Most of them find interaction is unreal and does not facilitate them to speak frequently. This study has persuaded that material selection can have its role. Such idea aligns with Rossiter (2009), who said topic familiarity and linguistic aspects influenced the speed of talks.

Third, similar to many definitions of oral fluency, which consider that fluency can be perceived by the listener. Rossiter (2009) recruited 24 ESL intermediate learners and 6 native experts for the study. The learners included 15 novice native speakers and 15 advanced non-native speakers of English. The speakers were asked to complete a questionnaire on their language experience and an eight-frame narrative description task conducted and audio-taped at time 1 and again after 10 weeks, at time 2. The topic was about a couple moving to the country and finally returned to an easier life in the city. The results showed that the novice native speakers gave the highest fluency ratings to the speech samples, followed by the native expert group and the non-native speakers (respectively). Higher fluency ratings at time 2 were generally higher than those of time 1. It was explained that non-native speakers’ judgments were influenced by their ESL teachers’ ways, paying more attention to linguistic features. Then, this study can also suggest that the topic familiarity and frequency of topic exposure can influence oral fluency. Moreover, people who have experienced in learning and teaching a foreign language can find themselves more demanding in use of linguistic aspects. Han et al. (2020) explored the relationship between utterance fluency measures and raters’ perceived fluency ratings of English/Chinese consecutive interpreting in hope to create, rewrite and modify rubrics and scalar descriptors of fluency scales in interpreting. This study, albeit going for interpretation, can be seen as a good one to see if the scales for rating utterance fluency correspond to the assessor’s perception of oral fluency. Muñoz Ocampo (2022) found lack of fluency was identified as the participants’ primary problem throughout the diagnostic phase. Additionally, it was shown that they were unable to achieve language mechanisms, but showed interest in daily life matters. The data were gathered from the four instruments—student transcripts, student self-assessment forms, non-participant observer forms, and teacher journals. It uncovered that students might increase their fluency by actively adopting certain communication methods or explicitly articulating them while completing challenging tasks.

Fourth, to help improve oral fluency, instructors may want to modify their instruction by many ways. Vo (2021) looked at the effects of task kinds and motivation on oral L2 fluency development in higher education in Vietnam. Thirty second-year university students and thirteen professors took part in the study. Close-ended questionnaires for students and instructors as well as semi-structured interview questions for instructors were used. It found task success is just being motivated. Additionally, the results show that performances are generally statistically more fluent in dialogue. Van Os et al. (2020) also investigated oral fluency through interaction and which can either positively or negatively influence involved speakers. Guevara-Betancourt and Albuja (2020) conducted a study to identify the variables that affect the growth of oral competence and fluency in undergraduate English major students who are at an intermediate level. A quantitative approach was used to identify and quantify the factors influencing the oral skill development of the English language and thereby comprehending factors that influence fluency during the target language communication process. A descriptive study and an inductive technique were both used to identify and categorize the components. It found important variables, such as language exposure and the importance of contact both inside and outside of the classroom are the influential factors. Nergis (2021) employed an experimental group of 20 students to test against the other 20 control students. The instruction of 10 sessions for both groups used a list of targeted items (formulaic sequences used for the experimental group and academic vocabulary for the comparison one). Each targeted item was then introduced in real-life academic spoken discourse, which attempted to make learners familiar with the context in which these items will be used in real life and make learning of these items more meaningful to them. All repetition and filled pause markers like ‘um’ and “uhh were eliminated to avoid imitation by learners. To test the effectiveness of the intervention, three tests were used in pretest, posttest, and delayed posttest. It revealed that the two groups enhanced significantly in speed fluency from pretest to posttest and the formulaic sequences group outperformed the control group in pruned speech rate and in the global fluency measure. Effects of formulaic sequences instruction were maintained on delayed posttest. This study has described very specific aspects used to test oral fluency and with appropriate modeling and language input can help learners produce better fluency output.

Overall, many ideas of oral fluency were found. Mainly, hesitation, reformation of speech, pauses, and dysfluency are seen as the most common obstacles. Furthermore, text structures, text complexity, text unfamiliarity and the listener’s perceived oral fluency, language exposure, and language instruction are all considered to affect oral fluency. These theories and literature have led the authors to propose the four following research questions in hope to find more ideas on how Vietnamese EFL teachers and students perceive oral fluency.

  1. 1.

    How do senior Vietnamese EFL students perceive oral fluency?

  2. 2.

    How do Vietnamese EFL teachers (BA) perceive oral fluency?

  3. 3.

    How do Vietnamese EFL teachers (Master) perceive oral fluency?

  4. 4.

    How do Vietnamese EFL teachers (Doctor) perceive oral fluency?

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