Effects of Group Dynamic Assessment on L2 Chinese learners’ literacy development: Learners’ responsiveness to interactive mediation

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Yu-Ting Kao

AbstractDynamic Assessment (DA), an innovative assessment approach, has begun to attract attention as a conceptualization of assessment that emphasizes the social interactive role of learning. Although DA receives attention in the field of language testing/assessment, its feasibility in engaging larger cohorts of individuals is concerned. This shortcoming of DA leads to the application of Group Dynamic Assessment (G-DA). This study examined the extent to which mediation provided through G-DA frameworks – concurrent and cumulative – supported a group of language learners’ literacy development. It investigates five intermediate L2 Chinese learners’ rhetorical awareness via their performance on Chinese reading and writing tasks. One Chinese rhetorical structures, the ‘Qi-cheng-zhuan-he’ approach, was selected because it is considered the most difficult learning point for Chinese learners. Findings were reported: 1) the mediation provided to the participants through both concurrent and cumulative G-DA approaches promoted their understanding of the ‘Qi-cheng-zhuan-he’ approach, 2) the more times a participant engaged as the primary interactant, the better learning outcome he/she would present, 3) individual participant had different developmental level and thus showed various extent of responsiveness to the teacher’s mediation; yet, their active participation, either verbal or nonverbal behaviors, would foster their learning performance. Pedagogical applications are discussed.

2021 ◽  
Vol 20 ◽  
pp. 72-89
Author(s):  
Mahboobeh Saadat ◽  
Omid Mallahi

The present study employed a cumulative format of Group Dynamic Assessment (G-DA), an assessment approach that integrates instruction into assessment, and adopted an interactionist approach to DA to conduct a semester-long mediation program in a writing course, which aimed at improving the writing ability of 15 (8 males and seven females) intermediate proficiency level sophomore students of English Language and Literature, in a State University in Iran. The students’ performances on non-dynamic writing pre- and post-tests and nine in-class dynamic writing tasks, completed during the DA sessions, were compared using independent samples t-test and mixed between-within subjects analysis variance (ANOVA), respectively. More specifically, the participants were divided into the two groups of more-skilled and less-skilled student writers, and then their performance was compared. The results indicated that the mediation offered had been highly effective in improving the writing competence of both groups of more- and less-skilled writers. They have been equally able to benefit from the mediation received and resolve their problems in writing. In addition, the dominant patterns of tutor mediational and learner reciprocity moves from a recorded DA intervention session were identified to see how they can lead to the learners’ writing development.


Author(s):  
Yue Zhang ◽  
Zhizhang Hu ◽  
Susu Xu ◽  
Shijia Pan

AbstractIn this paper, we introduce AutoQual, a mobile-based assessment scheme for infrastructure sensing task performance prediction under new deployment environments. With the growth of the Internet-of-Things (IoT), many non-intrusive sensing systems have been explored for various indoor applications, such as structural vibration sensing. This indirect sensing approach’s learning performance is prone to deployment variance when signals propagate through the environment. As a result, current systems heavily rely on expert knowledge and manual assessment to achieve effective deployments and high sensing task performance. In order to mitigate this expert effort, we propose to systematically study factors that reflect deployment environment characteristics and methods to measure them autonomously. We present AutoQual that measures a series of assessment factors (AFs) reflecting how the deployment environment impacts the system performance. AutoQual outputs a task-oriented sensing quality (TSQ) score by integrating measured AFs trained from known deployments as a prediction of untested system’s performance. In addition, AutoQual achieves this assessment without manual effort by leveraging co-located mobile sensing context to extract structural vibration signal for processing automatically. We evaluate AutoQual by using it to predict untested systems’ performance over multiple sensing tasks. We conduct real-world experiments and investigate 48 deployments in 11 environments. AutoQual achieves less than 0.10 average absolute error when auto-assessing multiple tasks at untested deployments, which shows a $$\le 0.018$$ ≤ 0.018 absolute error difference compared to the manual assessment approach.


Zona Próxima ◽  
2019 ◽  
pp. 82-99
Author(s):  
Lizeth Katherine Vergara Cabarcas ◽  
◽  
José Luis López Caraballo ◽  
Dilson Javier Castellon Barrios ◽  
Carlos Alberto Vásquez Rossi ◽  
...  

1993 ◽  
Vol 14 (5) ◽  
pp. 6-18 ◽  
Author(s):  
Asha K. Jitendra ◽  
Edward J. Kameenui

2021 ◽  
Vol 12 ◽  
Author(s):  
Fuyun Wu ◽  
Jun Lyu ◽  
Yanan Sheng

English as a verb-medial language has a short-before-long preference, whereas Korean and Japanese as verb-final languages show a long-before-short preference. In second language (L2) research, little is known regarding how L1 processing strategies affect the ultimate attainment of target structures. Existing work has shown that native speakers of Chinese strongly prefer to utter demonstrative-classifier (DCL) phrases first in subject-extracted relatives (DCL-SR-N) and DCLs second in object-extracted relatives (OR-DCL-N). But it remains unknown whether L2 learners with typologically different language backgrounds are able to acquire native-like strategies, and how they deviate from native speakers or even among themselves. Using a phrase-assembly task, we investigated advanced L2-Chinese learners whose L1s were English, Korean, and Japanese, because English lacks individual classifiers and has postnominal relative clause (RC), whereas Korean and Japanese have individual classifiers and prenominal RCs. Results showed that the English and Korean groups deviated from the native controls’ asymmetric pattern, but the Japanese group approximated native-like performance. Furthermore, compared to the English group, the Korean and Japanese groups favored the DCL-second configuration in SRs and ORs. No differences were found between the Korean and Japanese groups. Overall, our findings suggest that L1 processing strategies play an overarching role in L2 acquisition of asymmetric positioning of DCLs in Chinese RCs.


Author(s):  
Hsiu-Jen Cheng

This chapter aims to introduce the integration of TPACK into a Chinese pre-service teacher training program and discuss its outcomes and challenges. First, the concept of TPACK was introduced and relevant TPACK research and its constraints in the previous studies were discussed. Through the partnership between a Chinese pre-service teacher training program in Taiwan and a Chinese learning program in the States, the author developed a Teaching and Learning Model, entitled TL-TPACK model, integrating practicum, course design, advisors, peer cooperation, and reflections—five training strategies to ensure the training and learning outcome. At the end of the chapter, an empirical Chinese pre-service teacher training study applying the TL-TPACK model was conducted to investigate pre- service teachers' seven TPACK competences and Chinese learners' learning performance. Finally, research implications and suggestions for future studies were discussed.


2019 ◽  
Vol 1 (2) ◽  
pp. 154-183 ◽  
Author(s):  
Qiong Li

Abstract This study examined second language (L2) Chinese learners’ developmental patterns of pragmatic competence in two computer-mediated communication (CMC) conditions: (1) CMC with data-driven instruction embedded in the course of CMC and (2) CMC without data-driven instruction. Learners’ pragmatic competence was operationalized as their ability to use a Chinese sentence final particle (SFP) ne during CMC with a native speaker partner. The study investigated: (1) whether learners (as a group) developed their use of ne over time in the two CMC conditions, and (2) how individual learners changed their use of ne (if any) in the two conditions. The quantitative analysis (token and type frequency of ne) revealed that CMC itself did not promote learners’ use of ne. However, it promoted learners’ production of ne when data-driven instruction was incorporated into CMC. Supporting the quantitative findings, the qualitative analysis showed that one learner in the CMC with data-driven instruction outperformed his counterpart in the CMC without data-driven instruction group in the diverse use of ne.


FORUM ◽  
2020 ◽  
Vol 18 (2) ◽  
pp. 197-230
Author(s):  
Mahboubeh Shorofi ◽  
Mohammad Saleh Sanatifar ◽  
Mansoor Tavakoli

Abstract For training translators in academic settings, the notion of translation bilingual sub-competence is fundamental. However, little research has addressed the practical methods for developing the trainees’ translation bilingual sub-competence. The present study investigated the impact of Group Dynamic Assessment on trainees’ translation bilingual sub-competence development and the ways it helps them develop their bilingual sub-competence. Vygotsky’s Zone of Proximal Development and PACTE translation competence model served as the theoretical framework for the study. Methodologically, a mixed-methods study was designed. For the quantitative phase, a semi-experimental method, and for the qualitative phase, interviews were administered. The results confirmed that implementing a Group Dynamic Assessment developed the trainees’ translation bilingual sub-competence. The findings of the study can be used in professional development and in-service courses for the academic staff and could pave the way for further empirical research in translation pedagogy.


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