Impact of Multimodal Feedback and Formulaic Sequences on Improving Fluency of English Learners on Computer-Based Speaking Assessments
Impact of Multimodal Feedback and Formulaic Sequences on Improving Fluency of English Learners on Computer-Based Speaking Assessments
dc.contributor.advisor | Albakry, Mohammed | |
dc.contributor.author | Francois, Jennifer | |
dc.contributor.committeemember | Kim, Jwa | |
dc.contributor.committeemember | Fields, Stacy | |
dc.date.accessioned | 2021-07-14T01:03:37Z | |
dc.date.available | 2021-07-14T01:03:37Z | |
dc.date.issued | 2021 | |
dc.date.updated | 2021-07-14T01:03:37Z | |
dc.description.abstract | While recent research has shown that multimodal feedback and use of formulaic sequences (FS) are effective in improving student performance on writing tasks, there is a dearth of studies on the impact of these aspects on computer-based academic speaking assessments. This dissertation seeks to fill this gap by examining the impact of both multimodal feedback and formulaic sequences (FS) on improving performance and fluency of adolescent English Learners (ELs) on computer-based speaking assessments. Students in this interactive sequential mixed methods study were randomly assigned to a group receiving asynchronous feedback or a group receiving synchronous video feedback. Both groups were evaluated using the WIDA Speaking Interpretive Rubric that analyzes speech holistically at the word/phrase level, sentence level, and discourse level. Students then engaged in a second speaking task and were evaluated using the same rubric. Results indicated that both groups showed significant overall improvements: asynchronous feedback (n = 12, Task One Mdn = 3.00, Task Two Mdn = 4.50, Z = 3.07, p < .001, r = .89) and synchronous feedback (n = 12, Task One Mdn = 3.00, Task Two Mdn = 3.83, Z = 2.59, p = .008, r = .75), with the asynchronous feedback group out-performing the synchronous feedback group. Furthermore, regression analysis indicated that formulaic sequences significantly predicted speech fluency (β = 1.01, t(46) = 9.65, p < .001). Formulaic sequences also explained a significant proportion of variance in fluency scores (R2 = .67, F(1, 46) = 93.20, p < .001). Results from this study can inform and optimize remote and face-to-face (F2F) instruction in academic speaking and the implications include not only potentially improving EL students’ skills on standardized measures of academic speaking performance, but also enhancing their linguistic skills in general education classes and improving their college and career readiness. | |
dc.description.degree | Ph.D. | |
dc.identifier.uri | https://jewlscholar.mtsu.edu/handle/mtsu/6468 | |
dc.language.rfc3066 | en | |
dc.publisher | Middle Tennessee State University | |
dc.source.uri | http://dissertations.umi.com/mtsu:11469 | |
dc.subject | Academic feedback | |
dc.subject | Academic speech fluency | |
dc.subject | English as a Second Language | |
dc.subject | Formulaic sequences | |
dc.subject | Remote learning | |
dc.subject | SLA | |
dc.subject | English as a second language | |
dc.subject | Secondary education | |
dc.subject | Educational technology | |
dc.thesis.degreelevel | doctoral | |
dc.title | Impact of Multimodal Feedback and Formulaic Sequences on Improving Fluency of English Learners on Computer-Based Speaking Assessments |
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