This report addresses the importance of discussing adolescent learners in regard with their anxiety about foreign or second language (L2) speaking performance. To find implications on how to help adolescents reduce or overcome speaking anxiety in the language classroom, the report reviews extensive literature on 1) the distinct adolescent features that contribute to the development of shyness and communication apprehension; 2) the concept, component sources, and impacts of foreign language learning anxiety; and 3) the causes and effects of L2 speaking anxiety in language learning situations. Based on the review, the report provides implications from studies about language teaching and learning practices to alleviate L2 learning and speaking anxiety. These suggestions focus on meeting adolescents' needs in terms of 1) improving self-esteem, 2) developing coping skills about anxiety, and 3) facilitating a safer and more supportive classroom environment. / text

<p>The theory underlying L2 oral fluency has focused on cognitive processes, particularly proceduralization (Anderson, 1983; Levelt, 1989, 1999) and linguistic constructs, especially vocabulary and grammar (Segalowitz, 2010). Towell, Hawkins, and Bazergui (1996) argued that development of formulaic language enables automatic speech production. However, no research has studied the longitudinal development of L2 oral fluency concurrently with any of the following lexical variables: lexical frequency profile, formulaic language use, and MTLD (a measure of lexical diversity). The purpose of the present study is to clarify the process by which L2 oral fluency, syntax, and vocabulary develop concurrently.</p> <p>Data analysis involved three sequential phases: oral fluency analysis, lexico-syntactic analysis, and discourse analysis. Oral fluency measures were calculated using the transcribed oral test responses of 100 L1-Chinese EAP learners at the beginning and end of a required two-course EAP language and culture sequence at Purdue University. The task completed was a computer-administered, two-minute argumentative speaking task. This study included eight oral fluency measures: speech rate, mean length of speech run, articulation rate, phonation time ratio, mean length of silent pause, mean length of filled pause, silent pause frequency, and filled pause frequency. For the ten participants who made the largest percentage-wise oral fluency gains (in terms of the oral fluency variable associated with the largest effect size of gains), oral transcripts were analyzed to compute descriptive statistics for the three lexical variables mentioned above and three syntactic variables: coordinate clause ratio, dependent clause ratio, and words per T-unit. </p> Results indicated significant change in all oral fluency measures, except mean length of silent pause and mean length of filled pause. The largest gains were made in mean length of speech run. Of the linguistic variables, the largest longitudinal change was associated with coordinate clause ratio. Discourse analysis of the transcripts of large fluency gainers' pre-post responses suggested that large fluency gainers used coordinate clauses to build more sophisticated discourse models in the post-test response than they did in the pre-test response. Implications for L2 oral fluency theory, EAP pedagogy, and L2 oral assessment are discussed.

<div>This dissertation investigates three utterance fluency features and two vocabulary features of 409 speech samples from advanced intermediate and advanced L2 English speakers, who participated in the Oral English Proficiency Test (OEPT) between the year of 2009 and 2015. Among the 409 L2 English speakers, there are 80 L1 Hindi speakers rated as advanced intermediate, 32 L1 Hindi speakers rated as advanced, 286 L1 Mandarin speakers rated as advanced intermediate, and 11 L1 Mandarin speakers rated as advanced.</div><div><br></div><div>Hierarchical Cluster Analysis (HCA) was conducted and presented four different clusters among all the L2 English speakers. The four different clusters are: (1) Low Mean Syllables per Run (MSR), low Speech Rate (SR), very high Pause Rate (PR), medium Measure of Textual Lexical Diversity (MTLD), and medium percentage of words on the Academic Word List (AWL); (2) Medium Mean Syllables per Run (MSR), medium Speech Rate (SR), high Pause Rate (PR), low Measure of Textual Lexical Diversity (MTLD), and low percentage of words on the Academic Word List (AWL); (3) High Mean Syllables per Run (MSR), high Speech Rate (SR), low Pause Rate (PR), medium Measure of Textual Lexical Diversity (MTLD), and medium percentage of words on the Academic Word List (AWL); (4) Medium Mean Syllables per Run (MSR), medium Speech Rate (SR), low Pause Rate (PR), very high Measure of Textual Lexical Diversity, and very high percentage level of words on the Academic Word List (AWL).</div><div>Chi-square results show that L2 English speakers’ cluster membership is strongly associated with both their L1 background and level of L2 oral English proficiency. While most of the advanced intermediate L1 Mandarin speakers are in Cluster 1 and Cluster 2, the majority of the advanced intermediate L1 Hindi speakers concentrate in Cluster 3. A large number of advanced L1 Mandarin speakers and L1 Hindi speakers are also located in Cluster 3.</div><div><br></div><div>Twelve raters were invited to evaluate speech samples representative of the four clusters in terms of accent difference and listener effort. Twelve speakers were selected from the four clusters, whose speech samples have values of the five linguistic features closest to the cluster mean.</div><div><br></div><div>Multi-facet Rasch Measurement (MFRM) results show that L1 Mandarin speakers generally received lower ratings in accent difference and listener effort. The connection among fluency, vocabulary, and accentedness/listener effort, however, functions differently for L1 Mandarin speakers and L1 Hindi speakers. For advanced intermediate L1 Mandarin speakers, those who speak slower and use more diverse vocabulary and more academic words were evaluated to be less accented, meanwhile costing less listener effort. However, advanced intermediate L1 Hindi speakers were rated as less accented and cost less listener effort when they demonstrate higher fluency measures and lower vocabulary measures.</div><div><br></div><div>Advanced L2 English speakers, in contrary, received reverse rating results. The advanced L1 Mandarin speaker, who speaks faster and uses less diverse vocabulary and fewer academic words, was evaluated to be less accented and cost less listener effort. However, the advanced L1 Hindi speaker, who speaks slower and uses more diverse vocabulary and more academic words, was rated as less accented and cost less listener effort.</div><div><br></div><div>This dissertation reemphasizes that holistic rating rubric does not deny the existence of multiple linguistic profiles. Raters are sensitive to different combinations of fluency and vocabulary features even if they have been asked to use a holistic scale. In addition, L2 English speakers may adopt individual strategies to accommodate while delivering, which calls for further pedagogical attention.<br></div><div><br></div>

This study was an investigation of the validity of students' self-assessment of L2 oral performance, the influences of L2 affective variables on their self-assessment bias, and the degree to which the influences of L2 affective variables differ between high and low proficiency learners. The participants were 389 science majors from two private Japanese universities. A questionnaire was administered using items based on the Attitude/Motivational Test Battery (Gardner, 1985), the Foreign Language Classroom Anxiety Scale (Horwtiz et al., 1986), the Rosenberg Self-Esteem Scale (Rosenberg, 1965), Sick and Nagasaka's (2000) Willingness to Communicate Scale, and items designed to measure motivation adapted from Gardner, Tremblay, and Masgoret (1997), Yashima (2002), Irie (2005), and Matsuoka (2006). A factor analysis identified seven factors in the questionnaire data: Self-Esteem, L2 Speaking Anxiety, L2 Willingness to Communicate, Attitude Toward Learning to Speak English, L2 Speaking Motivational Intensity, Desire to Learn to Speak English, and L2 Speaking Self-Confidence. The scales were further validated using the Rasch rating scale model. Student oral interviews were recorded and rated by five English teachers using an oral assessment scale based on the Kanda English Proficiency Test (Bonk & Ockey, 2003).Immediately after the interviews were completed, the participants were asked to consider how they perceived their own speaking performance and they rated their own performance from their memory using the same oral assessment scale that the teacher raters used. The oral assessment scale included the descriptions of the oral performances that match each level. The participants read the descriptions of each level and chose a level that they thought matched their own performance. The study produced four main findings. First, a multi-faceted Rasch analysis revealed that the participants rated their own L2 speaking more severely than the teacher raters and that the students' self-assessments were neither reliable nor consistent. Second, self-assessment bias measures were calculated and used to test a hypothesized structural model of how affective factors influenced self-assessment bias. The hypothesized model showed poor fit to the data, possibly due to the poor reliability of the self-assessment measures. Multiple regression analyses conducted as a follow-up analysis revealed that participants with greater Desire to Learn to Speak English tended to underestimate and those with greater L2 Speaking Self-Confidence tended to overestimate their own speaking performance. Third, 106 participants whose self-ratings were similar to the teachers' ratings were compared with other students in order to examine their distinctive features. However, no significant differences in L2 oral proficiency or affective variable measures were found between the two. Therefore, those whose self-assessments agreed with teachers could have resulted in some agreements that occurred by chance alone. Finally, 100 higher proficiency students were compared with 100 lower proficiency students and the results showed that the higher proficiency students with greater Desire to Learn to Speak English generally underestimated their L2 speaking proficiency, while those with higher Self-Esteem and greater L2 Speaking Self-Confidence tended to overestimate it. Lower proficiency students with greater L2 Speaking Self-Confidence tended to overestimate their L2 speaking proficiency. The results suggest that the self-assessment of L2 speaking might not be a sufficiently reliable or consistent assessment tool. Therefore, if teachers are considering including self-assessment in a speaking class, self-assessment training should be conducted. Additionally, giving L2 learners more opportunities to speak the L2 can help them notice gaps between their productions and those of proficient speakers, which might lead to more accurate self-assessment. Second, although some studies utilized only one teacher-rater, five teacher raters in this study displayed a great deal of diversity and exhibited unique bias patterns, so multiple raters should be employed and Facets analyses should be employed because the multi-faceted Rasch model provides person ability estimates that are adjusted for rater bias. Finally, the use of multi-faceted Rasch analysis is useful for examining oral data because unlike raw scores, multi-faceted Rasch analysis provides detailed information concerning speaker ability, rater severity, and category difficulty. Moreover, while most researchers have utilized self-assessment raw scores, in this study bias measures of self-assessment were calculated using Facets, which indicated that the bias measures produced different outcomes compared with self-assessment scores. / Teaching & Learning

In an attempt to investigate the impact of planning on second language (L2) oral production, an experimental study that contrasted the effects of two types of pre-task planning (strategic planning vs. rehearsal) on the L2 oral task performance of 64 Japanese university EFL learners under different modality (aural vs. written) and language (L1 vs. L2) conditions of pre-task input was conducted. The main aim was to determine whether strategic planning (i.e., silent preparation) and rehearsal (i.e., active practice) before L2 oral tasks differentially impact performance in terms of fluency, complexity, and accuracy. An additional aim was to examine the effects on performance of providing pre-task input to assist planning. Furthermore, I elicited the learners’ perceptions of the value of the pre-task input toward assisting their oral task performance via 5-point Likert scale post-task questionnaires. No difference was found between strategic planning and rehearsal in their effects on L2 oral task performance regarding fluency, complexity, or accuracy. This result suggests that, when it comes to pre-task planning, L2 teachers can generally have their learners engage in either strategic planning or rehearsal without differentially impacting their task performance. Concerning the provision of pre-task input, the L1 and L2 input induced commensurate levels of fluency and complexity. However, the L2 input led to significantly greater accuracy of oral production than did the L1 input. This finding is important as it suggests that L2 learners can possibly acquire something from the input provided to them in the course of pre-task planning. Moreover, the post-task questionnaire results corroborated this finding as the participants indicated that the L2 input significantly enhanced their accuracy and also helped them use a wider range of vocabulary during the tasks. Thus, if the aim of a teaching or testing situation is oriented toward fluency, the results indicate that it makes no difference whether pre-task input is in learners’ L1 or L2. In contrast, if the aim is oriented toward accuracy, then teachers and testers should provide L2 input in order to facilitate optimal performance. / Language Arts