2.3. Previous Related Studies in the Field
2.3.2. The Impact of TBI on L2 Speaking Performance
2.3.2.3. The Impact of TBI on the Three CAF Components 128
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The monolgic task was a retelling task in which the participants were provided one minute to prepare for the task and another one minute to perform the task. The dialogic task was a discussion task in which the participants were given one minute to plan for the task and three minutes to report on the task. Students’ performance on both tasks were recorded, coded and scored based on a number of measures including: articulation rate, speech rate, mean length of pauses per 60 seconds, mean number of pauses per 60 seconds, mean number of partial or complete repetitions, hesitations, false starts and reformulations, mean number of filled pauses, mean length of run, phonation time ratio, and number of turns and number of interruptions.
Praat software was used to measure all temporal variables of fluency; such as articulation rate, length of pause and phonation time, while the rest of measures; such as repairs and number of filled pauses, were measured manually.
The results from this study showed that the participants with dialogic tasks outperformed those with monologic tasks on measures like repair, speech speed and length of pauses to a significant degree, while no significant difference was noticed on measures like number and location of pauses. However, despite the positive impact of dialogic tasks on L2 fluency, the researcher provided reasons why monologic tasks were more frequent in L2 fluency research.
According to the researcher, unlike dialogic tasks, monolgic tasks are more controlled tasks, students’ performance on monologic tasks are more predictable and the fluency measuring procedures are more clear and easier to conduct with monologic tasks.
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participants were 72 eighth-grade Chinese students who were divided into two groups with one group exposed to two narrative texts without explicit instruction (TBI) and the other exposed to the same two texts but with explicit instruction (TSLT). The difference between the two groups was that, the participants with explicit instruction were exposed to 10 minutes explanation on the past passive form and how to use it before task performance.
The teacher of both groups read the two narrative texts loudly for three times while the students’ role at this time was confined to being passive listeners to the teacher. After that, the teacher allocated 15 minutes for the students to work in pairs and practice retelling story. The students’ performance on the two assigned tasks was analyzed using measures such as “average pause length” for fluency, “error per 100 words” for accuracy and “length of AS-units” for complexity. The result from the study showed that the students without implicit instruction outperformed those with explicit instruction on the three speaking sub-skills of complexity, accuracy and fluency, and there was no significant difference between the two groups regarding the accurate use of the instructed past passive form. However, despite being ineffective in enhancing accuracy, the results showed increased attempts to use the target grammar by the group with explicit instruction, suggesting using it to improve students’ speaking accuracy.
Vercellotti (2017) conducted a longitudinal study to examine students’ oral performance in terms of complexity, accuracy and fluency by analyzing students’ performance during topic- based speeches recorded monthly over a period of 10 months. Not only this, the study also aimed to examine the relationship between CAF components to check the emergence of trade- off effects during L2 development. According to the trade-off hypothesis, the attention to one area of speaking performance or more may result in a lower performance in the others due to students’ limited attentional capacities. The sixty-six research participants were students from
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three different L1 backgrounds: Arabic (43), Chinese (16) and Korean (7). Those participants were exposed to an intensive English program during which TBI was used as a main teaching strategy. To identify their proficiency levels and place them into instruction levels, a standardized test and two in-house tests were administered. The students’ scores on the in-house listening placement test were considered as the best measurement of their proficiency levels because it was shown through the Pearson correlation analysis that the in-house listening placement test was strongly correlated with placement into instruction level (r = .838). The selected participants were divided into two groups with similar age and proficiency scores as confirmed by a two-tailed t-test (p = .520).
The participants were observed over 3-10 months during the program with a maximum 7 and a minimum of 3 observations for each participant. The participants were assessed through a 2-minute recorded monologue from the tasks studied during the intensive English program.
They were given one minute to plan for their speech during the speaking test but they were not allowed to take notes or use reference materials. The students’ speeches were measured using a rating scale that included the three components of speaking performance: complexity, accuracy and fluency.
Seeking the help of Praat software, the research data was transcribed by a highly qualified native English speaker who had ample experience with transcribing non-native speeches. The data was then coded into clauses and AS-units; that is, clear utterances were coded as AS-units, while the utterance with errors in morphology, syntax and lexis were coded within clauses. Complexity was measured in terms of the mean length of AS-unit in words, fluency was calculated in terms of the mean length of pauses, accuracy was rated based on the percentage of error-free clauses, while lexical diversity was rated using the “vocd” index.
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The data was analyzed using hieratical linear and non-linear growth modeling analogous to linear regression and analysis of covariance (ANCOVA). It was particularly chosen for its ability to display longitudinal data and detect the changes in students’ performance. For each CAF measure, a chi-square test was performed to compare linear and non-linear growth models, and the final model results were fully reported. Initial proficiency, topic and clause length were set to be the independent variables in this study while syntactic complexity, lexical diversity, accuracy and fluency were identified to be the dependent variables.
The results of the study showed a steady linear development in the students’ speaking performance in terms of fluency, accuracy and syntactic complexity, while lexical diversity showed non-linear development; a slight decline at the beginning followed by a steep growth over time. The study also did not detect any trade-off effects between the three CAF components as it showed strong rather than competitive relationships between them.
However, the longitudinal study by Ferrari (2012) in which the researcher investigated the impact of monologic and dialogic tasks on CAF development over a period of four consecutive years between 2005 and 2008 showed adverse results. This study used a systematic data collection procedure that allowed for comparisons across samples while at the same time mitigating the impact of task repetition. The participants, a total of six participants, were four L2 learners of Italian with proficiency levels of B1 and B2 (on the CEFR scale) at the beginning of the study and two native speakers of Italian with proficiency levels of C1 (according to the CEFR scale) at the onset of the study. The L2 participants were from different nationalities:
Nigeria, Eritrea, Ghana and India, and they had different L1 backgrounds of English, Tigrigna, Twi and Punjabi respectively. At the beginning of the study, all participants (all female students) were enrolled at the same vocational secondary school. During the three-year long observation
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period, three of the L2 students continued to study at university level while the fourth student started to work as an accountant in a private company.
The L2 students’ development was tested every three months between 2005 and 2008 (four times a year) while the two Italian students’ performance was assessed twice in 2005 and 2007. At every data collection session, all participants were asked to perform two monologic tasks (story retelling and film picture retelling) and two dialogic tasks (telephone call opening and interview). The independent variables were set to be nativeness, task type, time and group versus individual scores while the dependent variables were identified in this study as complexity, accuracy and fluency. The participants, during the story retelling task, were asked to tell an unfamiliar story to the interviewer and given time to plan before retelling. During the film picture retelling, the participants were asked to watch a short film of ten minutes, then they were allocated time to plan before retelling in front of the interviewer, with both the participants and the interviewer have not seen the short films before. The participants, during the phone calls, were required to make some calls to collect some information about specific topics; such as a book, a DVD, a mobile phone or a CD, using some spoken functions identified as part of the objectives of the task or to organize a trip to a given destination. The participants during the phone calls, around 5 to 7 calls for each participant yearly, were required to call experts, travel agents and shop assistants to make the best possible choices. As for the interview tasks, each participant was asked to make an informative speech with the interviewer who was an Italian L2 teacher. The topics included talking about habits, experiences, home country, family, self and so forth.
The development of CAF triad was assessed in this study based on a number of measures. For example, syntactic complexity was assessed using two quantitative measures of
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subordination (average number of subordinate clauses per AS-unit) and length (average number of words per clause). Accuracy was measured based on the percentage of error-free AS-units.
As for fluency, two measures were used: the average number of silent pauses per AS-unit and the average number of hesitation phenomena (e.g., repetitions, false starts, filled pauses) per AS- unit. The results showed a development on the three CAF constructs over time, and this development was more linear for fluency and non-linear for accuracy (U-shaped growth).
Supporting the developmental prediction hypothesis, the results revealed an increase for clause length coupled with a decrease in subordination ratio. The results also confirmed the trade-off effects between the three CAF components across tasks, more clearly between complexity and fluency on monologic than dialogic tasks.
Using technology with communicative tasks to improve students’ speaking skills in terms of complexity, accuracy and fluency, the study by Trevisol and D’ely (2021) aimed to investigate the impact of TBI with digital storytelling on students’ oral production of more complex, accurate, and fluent language. Fourteen Brazilian students, aging between 18 and 50 years old, with language proficiency levels ranging between basic and intermediate levels, and all from an English teaching program implemented in Bahia state in Brazil, were selected to be the participants of the study. Research tools included a pre-test run right before the experiment, an immediate post-test administered right after the experiment, a delayed-post test conducted within one month after the experiment, as well as a questionnaire to collect some data of qualitative nature from the research participants to understand their perception towards the use of digital technology in TBI classes to improve students’ speaking abilities. To ensure the proper employment of TBI using digital storytelling, the English sessions, a total of 6 sessions over three weeks, were taught by the researcher. During the TBI cycle, some digital storytelling
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tasks were first introduced, then explained by the teacher and then assigned for the students to work on during the second TBI phase. Not only this, a workshop on how to use “movie maker”
software was provided to enhance the participating students’ familiarity with the use of this software to enable them to create their own digital storytelling during the task performance. The students, during the second phase of TBI, were asked to work in groups to complete the given task and to present it before the class. The third stage of TBI cycle was usually allocated to discuss the students’ performance on the assigned tasks, provide constructive feedback and give recommendations for better performance on the next task.
The data of the study was collected from two sources: the first source of which was short oral narratives of one minute produced individually in English and gleaned via WhatsApp using the students’ smartphones. The students were given 10 minutes to prepare for their narratives and allowed to take notes during this time to help them frame their speech but they are not allowed to use these notes during their speech. The second source was fourteen digital storytelling videos of about 2-5 minutes long created individually in English by the participating students.
The CAF components as well as lexical richness were scored using nine measures including the number of subordinate clauses per AS-unit for complexity, the number of errors per AS-unit for accuracy, the following six measures to calculate fluency: the number of words per minute (pruned and unpruned), the number of pauses per AS-unit (filled and unfilled), the percentage of unfilled pauses and the number of self-repairs per AS-unit and finally the proportion and frequency of lexical items for lexical richness. The data was analyzed using some descriptive and inferential statistic tools (e.g., gain scores, standard deviations, means, normality test and Friedman test).
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The results showed a positive change in all participants on, at least, one of the measures after the experiment; that is, L2 students’ oral production was characterized as being more lexically rich, fluent, accurate or complex, even though the difference was not significantly large. The results suggested the need to conduct similar studies over longer periods of time to be able to see a noticeable change in students’ oral performance. The results also exhibited the positive perception of the participants towards the use of digital storytelling during the TBI cycle to improve students’ speaking skills as it enabled them to notice the gap in their speech, assess their own oral performance and reflect on the produced language, recommending the use of digital storytelling as an alternative tool in L2 classes to enhance effective language teaching and learning.
Integrating critical thinking standards into TBI principles, Yaprak and Kaya (2020) investigated the impact of reasoning-gap communicative tasks on students’ speaking performance in terms of complexity, accuracy and fluency. The research participants, a total of sixteen students, were randomly divided into two equal groups of eight students, and each group was further spit into four sub-groups with two students per each. Each sub-group was assigned a task from the four reasoning-gap tasks given to each group. The students were allowed to choose their partners in each sub-group with only the experimental sub-groups were given a special training on critical thinking standards. To help students acquire the linguistic and non- linguistic aspects of language, the four reasoning- gap tasks were designed to include the linguistic, socio-behavioral and cognitive development dimensions. The topics of the four tasks were: gender inequality at workplace, problems of early teen marriage, sharing household chores, and separation and divorce.
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The data was gleaned through recorded samples of classroom interaction and semi- structured interviews and analyzed through a task performance rubric and a web-based “Text- Inspector” language analysis tool. Fluency was scored through four measures of pronunciation (speaking clearly with no mispronunciation), hesitations, repetitions (clauses, phrases, words) and false starts. Accuracy was rated through the number of errors in syntax, morphology and semantics. Complexity was measured through the variety in word choices and the use of different types of sentences (simple, compound, complex, complex/ compound sentences). The measurements used with linguistic complexity were the subordination index (SI) for syntactic complexity and TTR, vocd-D and MTLD for lexical diversity. The students’ cognitive development was measured through five main intellectual standards: breadth (giving personal views towards the topic), logicalness (well-organization and reasonableness of the given information), depth and precision (the ability to provide profound analysis and present the necessary details), clarity (clarity of the message), and accuracy (correct information substantiated with evidence).
Two raters were asked to rate students’ speaking performance and cognitive development, and the high inter-rater reliability between both raters was confirmed (Cronbach’s α=.98). Moreover, Levene’s test was conducted to assure the homogeneity of variance, and the MANOVA test was executed to check the difference in both groups’ performance on complexity, accuracy and fluency variables. Additionally, the “text inspector” language analysis tool was used to analyze the students’ transcribed speeches with regard to lexical diversity, meta-discourse markers and the relation between the vocabulary used and the European vocabulary profiles.
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The findings showed that the participants in the experimental group who were subject to special training on critical thinking standards improved their oral performance in the three performance areas of fluency, accuracy and complexity. By comparing the results of the experimental group to that of the control group, the results exhibited a statistically significant difference between the two groups on accuracy (syntactic, morphological and semantic analyses) and linguistic complexity (syntactic complexity and lexical diversity), but not fluency.
Based on the semi-structured interview results, the experimental group’s participants agreed on the positive impact of critical thinking standards on their oral performance of the target language. Also, according to the qualitative results, critical thinking standards; such as logicalness, accuracy, breadth, depth, clarity and precision, not only motivated the participants to do much effort to achieve communicative success, but also allowed them to negotiate meanings, seek the necessary information and comprehend the entire situation, leading to the improvement of both linguistic and non-linguistic aspects of the target language.
Including some multiple intelligence features (e.g., linguistic, logical-mathematical, music, bodily-kinesthetic, visual-spatial, interpersonal, intrapersonal) into a TBI syllabus, Xu (2021) examined the impact of TBI on students’ speaking performance in terms of the three CAF components. Sixty university students were randomly selected then divided into two equal groups of thirty for the research treatment to answer the question about the impact of the study on the three CAF components while three hundred fifty-nine students were selected to complete a questionnaire about their multiple intelligence preferences. A TBI syllabus with multiple intelligence features was developed and employed to the experimental group while the control group was assigned the same TBI syllabus but without multiple intelligences.
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To elaborate on the study treatment, the study was conducted in three phases: the first phase aimed to identify the participants’ self-perception of multiple intelligence preferences through a questionnaire given out to them. The second phase targeted enhancing students’
speaking performance in terms of complexity, accuracy and fluency by integrating the perceived multiple intelligences into a TBI syllabus for the experimental group while the control group was exposed to TBI through the same TBI syllabus provided for the experimental group but without multiple intelligences. The third phase aimed to measure the difference between the two investigated groups in terms of their oral performance by calculating the data collected from the pre-post tests. The data from the pre-post tests was analyzed using paired sample t-test and independent sample t-tests to check any changes in both groups’ speaking abilities after the experiment and to compare the results of the experimental group to that of the control group at the end of the experiment.
The researcher relied on some measures in calculating students’ speaking performance in terms of the three CAF components. For example, the researcher used six indices to measure complexity: frequency of use of conjunctions, lexical richness (percentage of lexical to structural words), number of turns per minute, amount of subordination (total number of clauses divided by the total number of c-units), percentage of words functioning as lexical verbs and frequency of use of prepositions. Fluency was measured through eight measures: number of repetitions, number of words per run, number of pauses (over one second), mean length of run, number of syllables per minute, number of words per minute, number of reformulations and mean length of pauses (in second). Accuracy was calculated through six measures: number of self-corrections, ratio of indefinite to definite articles, target-like use of verb tenses, percentage of error-free clauses, target-like use of plurals and target-like use of articles.