113 Result(s)
within
**ya Lu
Artificial Intelligence
Data Mining and Knowledge Discovery
User Interfaces and Human Computer Interaction
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Chapter and Conference Paper
PBChat: Enhance Student’s Problem Behavior Diagnosis with Large Language Model
Student’s problem behaviors are undesirable behaviors encompass actions that deviate from established school standards, potentially impacting students’ overall well-being and academic success significantly. Di...
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Chapter and Conference Paper
Automated Long Answer Grading with RiceChem Dataset
This research paper introduces a new area of study in the field of educational Natural Language Processing (NLP): Automated Long Answer Grading (ALAG). Distinguishing itself from traditional Automated Short An...
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Chapter and Conference Paper
An Intelligent System for Chinese Dance Creation Using Generative Artificial Intelligence
We present an innovative and practical system for creating Chinese dance using generative artificial intelligence techniques. A full-attention cross-modal transformer is utilized to generate 3D dance motions t...
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Chapter and Conference Paper
Empowering Education with LLMs - The Next-Gen Interface and Content Generation
We propose the first annual workshop on Empowering Education with LLMs - the Next-Gen Interface and Content Generation. This full-day workshop explores ample opportunities in leveraging humans, AI, and learnin...
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Chapter and Conference Paper
A Student-Teacher Multimodal Interaction Analysis System for Classroom Observation
Classroom observation is an effective way for teachers to improve professional development, and the analysis of student-teacher interactions is critical and significant to classroom observation. However, the t...
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Chapter and Conference Paper
Improving the Item Selection Process with Reinforcement Learning in Computerized Adaptive Testing
Item selection is the key process for computerized adaptive testing (CAT) to effectively assess examinees’ knowledge states. Existing item selection algorithms mainly rely on information metrics, suffering two...
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Chapter and Conference Paper
A Personalized Learning Path Recommendation Method for Learning Objects with Diverse Coverage Levels
E-learning has resulted in the proliferation of educational resources, but challenges remain in providing personalized learning materials to learners amidst an abundance of resources. Previous personalized lea...
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Chapter and Conference Paper
Technology Ecosystem for Orchestrating Dynamic Transitions Between Individual and Collaborative AI-Tutored Problem Solving
It might be highly effective if students could transition dynamically between individual and collaborative learning activities, but how could teachers manage such complex classroom scenarios? Although recent work...
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Chapter and Conference Paper
Introducing Response Time into Guessing and Slip** for Cognitive Diagnosis
Cognitive diagnostic model (CDM) aims to estimate learners’ cognitive states utilizing different techniques so that personalized educational interventions can be provided. The deterministic inputs noisy and ga...
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Chapter and Conference Paper
A Generic Interpreting Method for Knowledge Tracing Models
To interpret the deep learning based knowledge tracing models (DLKT), we introduce a generic method with four-step procedure. The proposed method and procedure are generally applicable to the DLKT models with ...
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Chapter and Conference Paper
An Intelligent Multimodal Dictionary for Chinese Character Learning
Chinese character learning is difficult, as the character’s definitions in dictionary are simple but abstract. The image representations of Chinese character’s definitions are easy to understand and helpful to...
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Chapter and Conference Paper
Out-of-Domain Semantics to the Rescue! Zero-Shot Hybrid Retrieval Models
The pre-trained language model (eg, BERT) based deep retrieval models achieved superior performance over lexical retrieval models (eg, BM25) in many passage retrieval tasks. However, limited work has been done to...
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Chapter and Conference Paper
Multi-modal Sentiment and Emotion Joint Analysis with a Deep Attentive Multi-task Learning Model
Emotion is seen as the external expression of sentiment, while sentiment is the essential nature of emotion. They are tightly entangled with each other in that one helps the understanding of the other, leading...
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Chapter and Conference Paper
NRCP-Miner: Towards the Discovery of Non-redundant Co-location Patterns
Co-location pattern mining, which refers to discovering neighboring spatial features in geographic space, is an interesting and important task in spatial data mining. However, in practice, the usefulness of pr...
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Chapter and Conference Paper
Assessment2Vec: Learning Distributed Representations of Assessments to Reduce Marking Workload
Reducing instructors workload in online and large-scale learning environments could be one of the most important factors in educational systems. To address this challenge, techniques such as Artificial Intelli...
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Chapter and Conference Paper
Back to the Origin: An Intelligent System for Learning Chinese Characters
Learning Chinese characters is a challenging task for both native and foreign beginners. One major reason is that most Chinese characters in writing are distinct from each other and lack of directly phonetic c...
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Chapter and Conference Paper
SRecGAN: Pairwise Adversarial Training for Sequential Recommendation
Sequential recommendation is essentially a learning-to-rank task under special conditions. Bayesian Personalized Ranking (BPR) has been proved its effectiveness for such a task by maximizing the margin between...
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Chapter and Conference Paper
Pregnancy-Related Information Seeking in Online Health Communities: A Qualitative Study
Pregnancy often imposes risks on women’s health. Consumers are increasingly turning to online resources (e.g., online health communities) to look for pregnancy-related information for better care management. T...
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Chapter and Conference Paper
SANS: Setwise Attentional Neural Similarity Method for Few-Shot Recommendation
Recommender systems generate personalized recommendations for users based on their historical data. However, if some users have few interactions in the training data, i.e., few-shot users, recommendations for ...
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Chapter and Conference Paper
URIM: Utility-Oriented Role-Centric Incentive Mechanism Design for Blockchain-Based Crowdsensing
Crowdsensing is a prominent paradigm that collects data by outsourcing to individuals with sensing devices. However, most existing crowdsensing systems are based on centralized architecture which suffers from ...
