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Huiying Cai on Muck Rack

Huiying Cai

As seen in: MDPI, SAGE Publishing, Dialnet - Universidad de La Rioja
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Articles

What makes listening comprehension difficult?: A feature-based machine learning approach to understanding item difficulty

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By Huiying Cai, Xun Yan, Ping-Lin Chuang
| Dialnet - Universidad de La Rioja
Understanding what makes second language (L2) listening comprehension difficult is crucial for advancing language learning and assessment. In L2 listening assessment, a key challenge is developing items with targeted difficulty levels. This difficulty can be influenced by textual and acoustic features from different item segments (i.e. stimuli, stems, and options) embedded in a multi-layered structure, along with task-related features.
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Triangulating NLP-based analysis of rater comments and MFRM: An innovative approach to investigating raters’ application of rating scales in writing assessment - Huiying Cai, Xun Yan, 2023

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By Huiying Cai, Xun Yan
| SAGE Publishing
Get full access to this article View all access and purchase options for this article. References Baker B. A. (2012). Individual differences in rater decision-making style: An exploratory mixed-methods study. Language Assessment Quarterly, 9(3), 225–248. https://doi.org/10.1080/15434303.2011.637262 Ballard L. (2017). The effects of primacy on rater cognition: An eye-tracking study (Publication No. 1897079271) [Doctoral dissertation, Michigan State University]. ProQuest Dissertations and Theses Global.
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Sustainability | Free Full-Text | Does Teachers’ Intention Translate to Actual Usage? Investigating the Predictors of K-12 Teachers’ Usage of Open Educational Resources in China

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By Xin Li, Lung-Hsiang Wong, Huiying Cai, Haixia Dong
| MDPI
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
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