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检索条件"丛书名=Lecture notes in artificial intelligence,"

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A Structural Priming Study of the Information Function of the Chinese Ba Construction 24th

A Structural Priming Study of the Information Function of th...

引用

24th Chinese Lexical Semantics Workshop (CLSW)

作者： Chen, Bingxian Hsu, Yu-Yin Hong Kong Polytech Univ Dept Chinese & Bilingual Studies Hung Hom Kowloon Hong Kong Peoples R China

ISBN: (纸本)9789819705856;9789819705863

Much research on the function of the ba construction in Mandarin Chinese has been conducted. However, there is a controversy about the ba NP regarding whether it expresses a topic denotation, a focus denotation, or neither. To study its information function, the present study has adopted a structural priming paradigm in a self-paced reading experiment to investigate whether Mandarin native speakers' reaction times (RTs) when reading ba sentences can be influenced after reading a priming sentence of the following three types: topic, focus, and subject-verb-object (SVO). The results revealed that the information conditions had a significant effect on the RT of processing the ba sentence (p<.001), while the RT for the ba NP in the condition of the priming focus sentences was significantly faster than the others. As priming effects occurred in the condition of priming focus sentences, processing the ba NP may be more similar to processing focus than to topic and canonical sentences in language comprehension.

关键词： The Ba Construction Structural Priming Information Function

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Exploring Teachers' Perception of artificial intelligence: The Socio-emotional Deficiency as Opportunities and Challenges in Human-AI Complementarity in K-12 Education 25th

Exploring Teachers' Perception of Artificial Intelligence: T...

引用

25th International Conference on artificial intelligence in Education (AIED)

作者： Oh, Soon-young Ahn, Yongsu Michigan State Univ E Lansing MI 48823 USA Univ Pittsburgh Pittsburgh PA 15260 USA

ISBN: (纸本)9783031642982;9783031642999

In schools, teachers play a multitude of roles, serving as educators, counselors, decision-makers, and members of the school community. With recent advances in artificial intelligence (AI), there is increasing discussion about how AI can assist, complement, and collaborate with teachers. To pave the way for better teacher-AI complementary relationships in schools, our study aims to expand the discourse on teacherAI complementarity by seeking educators' perspectives on the potential strengths and limitations of AI across a spectrum of responsibilities. Through a mixed method using a survey with 100 elementary school teachers in South Korea and in-depth interviews with 12 teachers, our findings indicate that teachers anticipate AI's potential to complement human teachers by automating administrative tasks and enhancing personalized learning through advanced intelligence. Interestingly, the deficit of AI's socio-emotional capabilities has been perceived as both challenges and opportunities. Overall, our study demonstrates the nuanced perception of teachers and different levels of expectations over their roles, challenging the need for decisions about AI adoption tailored to educators' preferences and concerns.

关键词： Teachers' perception of AI Teacher-AI complementarity Teachers' role Human-AI complementarity

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A First Step in Using Machine Learning Methods to Enhance Interaction Analysis for Embodied Learning Environments 25th

A First Step in Using Machine Learning Methods to Enhance In...

引用

25th International Conference on artificial intelligence in Education (AIED)

作者： Fonteles, Joyce Davalos, Eduardo Ashwin, T. S. Zhang, Yike Zhou, Mengxi Ayalon, Efrat Lane, Alicia Steinberg, Selena Anton, Gabriella Danish, Joshua Enyedy, Noel Biswas, Gautam Vanderbilt Univ Nashville TN 37240 USA Indiana Univ Bloomington IN 47405 USA

ISBN: (纸本)9783031642982;9783031642999

Investigating children's embodied learning in mixed-reality environments, where they collaboratively simulate scientific processes, requires analyzing complex multimodal data to interpret their learning and coordination behaviors. Learning scientists have developed Interaction Analysis (IA) methodologies for analyzing such data, but this requires researchers to watch hours of videos to extract and interpret students' learning patterns. Our study aims to simplify researchers' tasks, using Machine Learning and Multimodal Learning Analytics to support the IA processes. Our study combines machine learning algorithms and multimodal analyses to support and streamline researcher efforts in developing a comprehensive understanding of students' scientific engagement through their movements, gaze, and affective responses in a simulated scenario. To facilitate an effective researcher-AI partnership, we present an initial case study to determine the feasibility of visually representing students' states, actions, gaze, affect, and movement on a timeline. Our case study focuses on a specific science scenario where students learn about photosynthesis. The timeline allows us to investigate the alignment of critical learning moments identified by multimodal and interaction analysis, and uncover insights into students' temporal learning progressions.

关键词： Multimodal learning analytics Embodied learning Machine learning Interaction analysis

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A Study on the Use and Integration of the Network Buzzword 'Run' 24th

A Study on the Use and Integration of the Network Buzzword '...

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24th Chinese Lexical Semantics Workshop (CLSW)

作者： Li, Quan Jinan Univ Coll Chinese Language & Culture Guangzhou Peoples R China

ISBN: (纸本)9789819705825;9789819705832

In 2022, the network buzzword Run(.) was widely used on the online platform in Puatonghua circles. Its phonetic form is derived from the pinyinisation of the Englishword 'run', and its meaning ismainly transplanted from the meaning of 'run', most of the time with the additional meaning of displacement from [-comfortable] to [+comfortable], and in use there are two main variants of the meaning 'to escape' and 'to move abroad'. At the same time, the term quickly spread to other Chinese communities through online media, but its integration performance has significant community differences. The use and development of Run has the characteristics of explosive and no time difference, which is a vivid portrayal of social life and the psychology of netizens. The fact that it radiates and spreads outward reflects the language ecology of global Chinese language integration and coordination from one side.

关键词： Run Network Buzzwords Chinese integration

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Deep-IRT with a Temporal Convolutional Network for Reflecting Students' Long-Term History of Ability Data 25th

Deep-IRT with a Temporal Convolutional Network for Reflectin...

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25th International Conference on artificial intelligence in Education (AIED)

作者： Tsutsumi, Emiko Nishio, Tetsurou Ueno, Maomi Hosei Univ 3-7-2 Kajino Cho Koganei Tokyo 1848584 Japan Sundai Adv Teaching Technol 1-7-4 KandasurugadaiChiyoda Ku Tokyo 1010062 Japan Univ Electrocommun 1-5-1 Chofugaoka Chofu Tokyo 1828585 Japan

ISBN: (纸本)9783031643019;9783031643026

This study proposes a new Deep-IRT with a temporal convolutional network for knowledge tracing. The proposed method stores a student's latent multi-dimensional abilities at each time point and estimates the latent ability which comprehensively reflects the long-term history of ability data. To demonstrate the performance of the proposed method, we conducted experiments using benchmark datasets and simulation data. Results indicate that the proposed method improves the performance prediction accuracy of earlier Deep-IRT methods while maintaining high parameter interpretability. The proposed method exceeds the performance of earlier methods especially when the student's ability fluctuates according to past abilities.

关键词： Deep Learning Item Response Theory Knowledge Tracing

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Probability Distribution of Dependency Distance of Mongolian Nouns 24th

Probability Distribution of Dependency Distance of Mongolian...

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24th Chinese Lexical Semantics Workshop (CLSW)

作者： Dulan Dabhurbayar Inner Mongolia Normal Univ Zhaowuda Rd 81 Hohhot 010022 Peoples R China Inner Mongolia Univ Coll Rd 235 Hohhot 010021 Peoples R China

ISBN: (纸本)9789819705856;9789819705863

Based on the written and spoken language treebanks, this paper applies quantitative linguistics methods to statistically analyze Mongolian nouns and their dependency distance distributions. The results showed that the proportion of nouns in the Mongolian written language treebank was 35.58%, and the proportion of nouns and pronouns was 39.61%. In the Mongolian spoken language treebank, the proportion of nouns was 22.11%, and the proportion of nouns and pronouns was 33.12%. These findings closely align with results from prior research, further confirming the regularity of the proportion of nouns in human natural language. In terms of dependency distance distributions, the distributions of noun dependency distances in both the written and spoken treebanks fit the right-truncated Waring distribution and right-truncated modified Zipf-Alekseev distribution. This result is consistent with previous research. Moreover, the "long tail effect" can be seen from the fitting results, that is, as the dependency distance increases, its frequency decreases. This implies that there is also a tendency to minimize dependency distances in nouns.

关键词： Noun Dependency Distance Quantitative Study

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Investigating the Predictive Potential of Large Language Models in Student Dropout Prediction 25th

Investigating the Predictive Potential of Large Language Mod...

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25th International Conference on artificial intelligence in Education (AIED)

作者： Aboukacem, Abdelghafour Berrada, Ismail Bergou, El Houcine Iraqi, Youssef Mekouar, Loubna Mohammed VI Polytech Univ Coll Comp Ben Guerir Morocco

ISBN: (纸本)9783031642982;9783031642999

In the landscape of educational analytics, the usage of Machine Learning (ML), Deep Learning (DL), and Survival Analysis (SA), for student dropout prediction often encounters challenges in effectively detecting dropout cases and explaining dropout reasons. This is due to many challenges such as data imbalance, data processing issues, cold start problem, and the limited explainability of the predictive models. This paper explores the usage of Large Language Models (LLMs) for dropout prediction to tackle the previous challenges. We introduce an approach that leverages the adaptability and contextual understanding of LLMs to discern subtle indicators of potential dropout risks. In particular, we employ a Retrieval Augmented Generation (RAG)-assisted few-shot learning paradigm and prompt engineering to transfer the knowledge of LLMs. An intensive experimentation of our approach has been conducted using real-life Moroccan student data containing academic, demographic, and socio-economic information, to predict yearly school dropouts. Our findings highlight that LLMs outperform baseline ML models while showing the ability to produce textual analysis of students' data. Thus, LLMs have a promising potential to be employed as student dropout prediction assistants in educational institutions hoping to mitigate this phenomenon.

关键词： Student dropout prediction Large Language Models Few-shot learning Retrieval Augmented Generation

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Analyzing Biases in Popular Answer Selection Datasets on Neural-Based QA Models 27th

Analyzing Biases in Popular Answer Selection Datasets on Neu...

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27th International Conference on Text, Speech, and Dialogue (TSD)

作者： Chuy, Chang Nian Ding, Cherie Hu, Qinmin Vivian Toronto Metropolitan Univ Toronto ON Canada

ISBN: (纸本)9783031705625;9783031705632

The amount of information available on the internet has increased exponentially over the past decade. This digitization leads to the need of automated answering system to extract useful information from different sources. Due to the high demand of automated answering systems, many large-scale QA datasets and QA models have been introduced to the field to satisfy this need. In this work, we aim to explore and shed light upon the composition of the most popular QA datasets by comparing them through statistical distribution analyses and their biases. We collect multiple open QA datasets which cover different aspects of QA features, and highlight the differences of each QA dataset and its bias by comparing its effect on multiple baseline neural QA models. Our goal is to provide a clear understanding on the relationship of QA datasets and QA models, and offer a solid foundation for future research to enhance this growing field.

关键词： Question Answering QA Datasets Answer Selection model Deep Learning model Neural-based QA model

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A Study on the Position of Preposition-Objects Structures in Kongzijiayu 24th

A Study on the Position of Preposition-Objects Structures in...

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24th Chinese Lexical Semantics Workshop (CLSW)

作者： Ke, Yonghong Beijing Normal Univ Res Ctr Folklore Class & Chinese Characters Beijing 100875 Peoples R China Res Ctr Collat & Standardizat Chinese Characters Beijing Peoples R China

ISBN: (纸本)9789819705856;9789819705863

The position of preposition-object structures has changed significantly from ancient to modern Chinese. A comprehensive description and analysis of the positional relationship between preposition-object structures and the predicate components in Kongzijiayu (hereinafter, Jiayu) and comparisons with the Zuozhuan, Mozi, and Shiji can provide more proof in support of the key question of when the completion of Jiayu occurred and contribute to the accurate and in-depth interpretation of its text. We analyzed 15 prepositions in 1634 sentences in Jiayu, and the preposition-object structures in Jiayu occur mainly after the predicate components, accounting for 58.02%, which is very close to the prevalence in Mozi. The prepositions that can appear only before predicate components are Cong ((sic)), Yin ((sic)), Dang ((sic)), Yong ((sic)), Zhi ((sic)), Hou ((sic)) Dui ((sic)) and Jiang ((sic)), the prepositions that can appear only after predicate components are Hu ((sic)) and Zhu ((sic)), and the prepositions that can appear both before and after predicate components are Yu ((sic)), Yi ((sic)), Zi ((sic)), Wei ((sic)) and Zai ((sic)). When prepositional-object structures introduce time, tools/methods/conditions/basis/etc., cause/purpose and indirect objects, these are usually located before the predicate components. When prepositional-object structures introduce objects, location or the content of instruction or speech, these structures usually come after the predicate components. Only when the predicate component is monosyllabic are the preposition-object structures usually after the predicate components, accounting for 77.52% of instances. When the predicate component is polysyllabic, the preposition-object structure usually occurs before the predicate component. The proportion of preposition-object structures before the predicate components in Jiayu is between that of the Mozi and the Shiji and very close to that of Mozi, which may be related to the time when it was written

关键词： Kongzijiayu preposition-object structures predicate components position

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Let's Talk About Business: A Corpus-Based Study of 'Business' Related Near-Synonyms and Their Teaching in Chinese as a Second Language 24th

Let's Talk About Business: A Corpus-Based Study of 'Business...

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24th Chinese Lexical Semantics Workshop (CLSW)

作者： Zhong, Yin Rao, Yujing Hong Kong Univ Sci & Technol Ctr Language Educ Kowloon Clear Water Bay Hong Kong Peoples R China

ISBN: (纸本)9789819705856;9789819705863

The inherent semantic relatedness and closeness of near-synonyms pose difficulties to second language (L2) learners in comprehending and applying lexical knowledge in real situations. Previous studies have shown a sophisticated corpus-based method of distinguishing Chinese near-synonyms from a more 'theoretical-based' approach, the application of corpora in learning near-synonyms in an L2 classroom, however, is underexplored. This study reports both the 'theoretical-based' and 'pedagogical-application' of using corpora in studying 'business' related near-synonyms, and a significant gap between the 'theory' and the 'application' is identified. Our findings not only affirm the 'theoretical-based' method in capturing subtle nuances of near-synonyms but suggest implications of 'pedagogical-application' in teaching and learning near-synonyms with corpora.

关键词： Near-synonyms Corpus-based Blended Learning Sketch Engine BCC Corpus Lexical Semantics Teaching Chinese as a Second Language

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