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Investigating student teachers’ TPACK development for corpus technology and their self-efficacies for independent language learning and teaching: a mixed method study

Empirical corpus-based studies have demonstrated many positive outcomes in learners’ development of various language skills. However, frontline language teachers in primary and secondary schools are unfamiliar with corpus technology, mainly due to the lack of technological, pedagogical and content knowledge (TPACK) training in corpus technology. To address this knowledge gap, we have recently developed a corpus-based language pedagogy (CBLP) that blends language pedagogy with corpus technology. This proposal aims to frame training in corpus technology for student teachers within the TPACK framework to foster CBLP for effective teaching using corpus technology. This research will also provide a theoretical model by investigating how student teachers in Hong Kong and Mainland China receive TPACK training in corpus technology, and how this can influence their self-efficacies for independent language learning and teaching.


年份: 2023 - 2025

項目負責人 -

馬清博士

研究員: PI

Tonal effects on articulation: Acoustic analysis, ultrasound data, and articulatory synthesis

This project seeks to investigate the relationship between tongue movement and tone in speech production – two parts of articulation formerly considered independent from each other. We look at consonant-vowel coordination in Cantonese and Mandarin, two languages with respectively six and four lexical tones, under different tone and speech rate conditions. Both acoustic (formant) and articulatory (high temporal resolution ultrasound tongue imaging) data will be collected for analysis, followed by analysis-by-synthesis using VocalTractLab. Our findings will shed new lights on (i) our understanding of speech production, (ii) individual differences in articulatory control, and demonstrate (iii) the use of articulatory synthesis as a convenient tool for hypothesis-testing in articulation research.


年份: 2023 - 2025

項目負責人 -

李烱樂博士

研究員: PI

跨語言韻律比較模型

Two problems have remained unresolved in speech prosody research. The first one is that there are numerous rival theories that have coexisted for decades -- supporters for one do not necessarily understand the others well. The second one is that in the absence of a universally accepted framework, field linguists working with a new language could propose prosodic analyses not otherwise satisfactory to fellow researchers, in part also due to field-related practical challenges compared with lab settings. Computational modelling can be a useful tool for addressing these problems. This project seeks to promote computational modeling of fundamental frequency as a tool for (i) theory comparison and (ii) hypothesis testing and analysis *for field linguists*. Here we specifically target linguists without background in computer science or statistics.


年份: 2021 - 2023

項目負責人 -

李烱樂博士

研究員: PI

英語學術寫作的診斷性評估:通過結構方程建模研究自我調節控制和篇章整合策略的中介效應

Writing from sources is an important academic literacy skill essential for university students to succeed in academia. Nonetheless, because it involves a set of complex cognitive, metacognitive, and self-regulatory processes and strategies, it is extremely challenging. Existing research primarily focused on the cognitive processes of sourcebased writing, adopting qualitative and case-study based methods. While the research generated a nuanced understanding of the intricate mental struggles and issues during the reading-to-write process, it did not investigate the contextual and behavioural aspects of the process, such as the regulation of time, environment and motivation. There is also a paucity of research adopting quantitative means to connect important antecedent, process and outcome variables to generate a comprehensive picture with sufficient clarify to guide practice and further research. The proposed study will attempt to address the above gaps in the literature.


年份: 2021 - 2023

項目負責人 -

謝琴博士

研究員: PI

設有少數族裔語言提示的粵拼中文輸入法

年份: 2021 - 2023

項目負責人 -

劉擇明博士

研究員: PI