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60 resources
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Kafeng Wang, Pengyang Wang, Chengzhong x...|Mar 10th, 2022|journalArticleKafeng Wang, Pengyang Wang, Chengzhong x...Mar 10th, 2022
Automated Feature Engineering (AFE) refers to automatically generate and select optimal feature sets for downstream tasks, which has achieved great success in real-world applications. Current AFE methods mainly focus on improving the effectiveness of the produced features, but ignoring the low-efficiency issue for large-scale deployment. Therefore, in this work, we propose a generic framework to improve the efficiency of AFE. Specifically, we construct the AFE pipeline based on reinforcement...
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Qiao Wang|Jun 21st, 2022|journalArticleQiao WangJun 21st, 2022
This study searched for open-source semantic similarity tools and evaluated their effectiveness in automated content scoring of fact-based essays written by English-as-a-Foreign-Language (EFL) learners. Fifty writing samples under a fact-based writing task from an academic English course in a Japanese university were collected and a gold standard was produced by a native expert. A shortlist of carefully selected tools, including InferSent, spaCy, DKPro, ADW, SEMILAR and Latent Semantic...
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Cong Wang, Xiufeng Liu, Lei Wang|Apr 10th, 2021|journalArticleCong Wang, Xiufeng Liu, Lei WangApr 10th, 2021
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Cong Wang, Xiufeng Liu, Lei Wang|Sep 9th, 2020|journalArticleCong Wang, Xiufeng Liu, Lei WangSep 9th, 2020
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EdArXiv|Jun 2nd, 2023|reportEdArXivJun 2nd, 2023
Coaching, which involves classroom observation and expert feedback, is a widespread and fundamental part of teacher training. However, the majority of teachers do not have access to consistent, high quality coaching due to limited resources and access to expertise. We explore whether generative AI could become a cost-effective complement to expert feedback by serving as an automated teacher coach. In doing so, we propose three teacher coaching tasks for generative AI: (A) scoring transcript...
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Lijuan Wang, Miaomiao Zhao|Mar 10th, 2024|conferencePaperLijuan Wang, Miaomiao ZhaoMar 10th, 2024
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EdArXiv|Jun 2nd, 2023|reportEdArXivJun 2nd, 2023
Coaching, which involves classroom observation and expert feedback, is a widespread and fundamental part of teacher training. However, the majority of teachers do not have access to consistent, high quality coaching due to limited resources and access to expertise. We explore whether generative AI could become a cost-effective complement to expert feedback by serving as an automated teacher coach. In doing so, we propose three teacher coaching tasks for generative AI: (A) scoring transcript...
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Rose Wang, Dorottya Demszky|Jun 2nd, 2023|preprintRose Wang, Dorottya DemszkyJun 2nd, 2023
Coaching, which involves classroom observation and expert feedback, is a widespread and fundamental part of teacher training. However, the majority of teachers do not have access to consistent, high quality coaching due to limited resources and access to expertise. We explore whether generative AI could become a cost-effective complement to expert feedback by serving as an automated teacher coach. In doing so, we propose three teacher coaching tasks for generative AI: (A) scoring transcript...
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EdArXiv|Jun 2nd, 2023|reportEdArXivJun 2nd, 2023
Coaching, which involves classroom observation and expert feedback, is a widespread and fundamental part of teacher training. However, the majority of teachers do not have access to consistent, high quality coaching due to limited resources and access to expertise. We explore whether generative AI could become a cost-effective complement to expert feedback by serving as an automated teacher coach. In doing so, we propose three teacher coaching tasks for generative AI: (A) scoring transcript...
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Jin Wang, Wenxiang Fan|May 6th, 2025|journalArticleJin Wang, Wenxiang FanMay 6th, 2025
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Using Multi-label Classification Neural Network to Detect Intersectional DIF with Small Sample SizesYale Quan, Chun Wang|Mar 10th, 2025|journalArticleYale Quan, Chun WangMar 10th, 2025
This study introduces InterDIFNet, a multilabel classification neural network for detecting intersectional differential item functioning (DIF) in educational and psychological assessments, with a focus on small sample sizes. Unlike traditional marginal DIF methods, which often fail to capture the effects of intersecting identities and require large samples, InterDIFNet models uniform and non-uniform DIF across multiple intersectional groups simultaneously. The method utilizes an optimized...
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Xinyi Lu, Xu Wang|Jul 9th, 2024|conferencePaperXinyi Lu, Xu WangJul 9th, 2024
Evaluating the quality of automatically generated question items has been a long standing challenge. In this paper, we leverage LLMs to simulate student profiles and generate responses to multiple-choice questions (MCQs). The generative students' responses to MCQs can further support question item evaluation. We propose Generative Students, a prompt architecture designed based on the KLI framework. A generative student profile is a function of the list of knowledge components the student has...
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Zihao Zhou, Maizhen Ning, Qiufeng Wang|Mar 10th, 2023|conferencePaperZihao Zhou, Maizhen Ning, Qiufeng WangMar 10th, 2023
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Rania Abdelghani, Yen-Hsiang Wang, Xingd...|Jun 30th, 2023|journalArticleRania Abdelghani, Yen-Hsiang Wang, Xingd...Jun 30th, 2023
In order to train children's ability to ask curiosity-driven questions, previous research has explored designing specific exercises relying on providing semantic and linguistic cues to help formulate such questions. But despite showing pedagogical efficiency, this method is still limited as it relies on generating the said cues by hand, which can be a very costly process. In this context, we propose to leverage advances in the natural language processing field (NLP) and investigate the...
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Zichao Wang, Andrew Lan, Richard Baraniu...|Mar 10th, 2021|conferencePaperZichao Wang, Andrew Lan, Richard Baraniu...Mar 10th, 2021
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Yu Wang, Madhu Gopalakrishnan, Yoav Berg...|Mar 10th, 2025|presentationYu Wang, Madhu Gopalakrishnan, Yoav Berg...Mar 10th, 2025
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Ting Wang, Ying Du, Karen Hoeve|Mar 10th, 2025|conferencePaperTing Wang, Ying Du, Karen HoeveMar 10th, 2025
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Ting Wang, Ying Du, Karen Hoeve|Mar 10th, 2025|presentationTing Wang, Ying Du, Karen HoeveMar 10th, 2025
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Yu Wang, Madhumitha Gopalakrishnan, Yoav...|Mar 10th, 2025|conferencePaperYu Wang, Madhumitha Gopalakrishnan, Yoav...Mar 10th, 2025
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Tianqi Wang, Hiroaki Funayama, Hiroki Ou...|Mar 10th, 2021|journalArticleTianqi Wang, Hiroaki Funayama, Hiroki Ou...Mar 10th, 2021