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356 results on '"Nguyen, Duyen Thi"'

16. Vocabulary Demands of Academic Spoken English Revisited: A Case of University Lectures and TED Presentations

Author

Trang, Nguyen Huynh, Nguyen, Duyen Thi Bich, and Ha, Hung Tan

Abstract

The article shines light upon the differences in the vocabulary demands of academic spoken discourse between three broad scientific disciplines: Life Sciences, Physical Sciences, and Social Sciences. By employing the Academic Word List (AWL) and British National Corpus/Corpus of Contemporary American English (BNC/COCA) wordlist, the present study analyzed data of the transcripts from 160 university lectures, 39 seminars, and 600 TED talks. Results from the analysis of the 2.5-million-token corpus demonstrated an order of lexical difficulty in which Life Sciences and Social Sciences were the most and least lexically demanding fields of study, correspondingly. Research findings also indicated a strong supportive relationship between the AWL and the BNC/COCA wordlist. Learners with limited vocabulary knowledge at 1,000 and 2,000 levels could significantly increase their lexical coverage for academic lectures, seminars, and presentations with the support of the AWL. For disciplines with low lexical demands like Social Sciences, the vocabulary knowledge of nearly 2,570 word families (BNC/COCA 2,000 + AWL) could help students understand 95.07% of the running words in universities lectures and seminars. Research findings offer implications for vocabulary teaching and learning.

Published
2023
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46. What is the best predictor of word difficulty? A case of data mining using random forest.

Author

Ha, Hung Tan, Nguyen, Duyen Thi Bich, and Stoeckel, Tim

Subjects
*DATA mining, *RANDOM forest algorithms, *VOCABULARY, *EMPIRICAL research, *DATA analysis
Abstract

Word frequency has a long history of being considered the most important predictor of word difficulty and has served as a guideline for several aspects of second language vocabulary teaching, learning, and assessment. However, recent empirical research has challenged the supremacy of frequency as a predictor of word difficulty. Accordingly, applied linguists have questioned the use of frequency as the principal criterion in the development of wordlists and vocabulary tests. Despite being informative, previous studies on the topic have been limited in the way the researchers measured word difficulty and the statistical techniques they employed for exploratory data analysis. In the current study, meaning recall was used as a measure of word difficulty, and random forest was employed to examine the importance of various lexical sophistication metrics in predicting word difficulty. The results showed that frequency was not the most important predictor of word difficulty. Due to the limited scope, research findings are only generalizable to Vietnamese learners of English. [ABSTRACT FROM AUTHOR]

Published
2024
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47. An Organic–Inorganic Superlattice with Nanocrystal‐Amorphous Composite Nanolayers for Ultrahigh Thermoelectric Performance.

Author

Palani, Indirajith, Nguyen, Duyen Thi, Kim, Jongchan, Nguyen, Quang Khanh, Nguyen, Long Van, Song, Da Som, Lim, Jong Sun, Kim, Chang Gyon, Cho, Kyeongjae, and Sung, Myung Mo

Subjects
*HEAT recovery, *SEEBECK coefficient, *THERMAL conductivity, *COMPOSITE materials, *COMPOSITE structures
Abstract

Thermoelectric materials play a crucial role in converting heat into electricity, offering significant potential for applications in waste heat recovery and cooling. Herein, an innovative approach that combines an organic–inorganic hybrid superlattice structure with nanocrystal‐amorphous composite nanolayers is introduced. The nanocrystal‐amorphous composite enhances the Seebeck coefficient resulting in a notable twofold improvement in the power factor. The superlattice, alternating self‐assembled organic monolayers and inorganic nanolayers, effectively reduces lattice thermal conductivity by creating multiple interfaces that scatter phonons effectively. The integration of the nanocrystal‐amorphous composite nanolayers into the superlattice provides a dual advantage, simultaneously boosting the power factor and suppressing thermal conductivity. This synergistic effect leads to exceptional thermoelectric performance in the 4‐mercaptophenol/Sb2Te3 superlattice, with achieved figure of merit (ZT) values of 3.48 at 300 K and reaching a peak ZT value exceeding 4.0 at 400 K while surpassing 2.5 over the temperature range from 300 to 500 K. These results suggest that this innovative approach paves the way for the development of highly efficient thermoelectric materials, propelling efforts toward more energy‐efficient and environmentally friendly solutions. [ABSTRACT FROM AUTHOR]

Published
2024
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49. Bridging to Mathematical Modelling: Vietnamese Students' Response to Different Levels of Authenticity in Contextualized Tasks

Author

Tran, Dung, Nguyen, Duyen Thi, Nguyen, An Thi Tan, Nguyen, Giang-Nguyen Thi, and Ta, Phuong Minh

Abstract

To address the upcoming reform curriculum initiative following competency-based learning in Vietnam, this study examines how variations of a contextualized task allow students to experience the mathematical modelling process. We explore how Grade 10 students respond to tasks with different levels of authenticity when they first attempt such tasks. Adapting the Theory of Authentic Task Situations, we designed variations of the Goat Cage task and implemented them with six small groups of students. Results showed that the modelling processes that the students progressed through differed in mathematical models used and real-world considerations, with diverse approaches when solving the more-authentic variation. Not all phases of the modelling process were observed explicitly when they engaged in the tasks. Students showed a positive disposition towards tasks with more authentic contextual information. The study suggests ways to adapt contextualized tasks to make them more authentic, which allows students to experience a holistic modelling process.

Published
2020
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