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Intelligent Tutoring Systems have become critically important in future learning environments. Knowledge Tracing (KT) is a crucial part of that system. It is about inferring the skill mastery of students and predicting their performance to…

Computers and Society · Computer Science 2021-12-22 Sein Minn , Jill-Jenn Vie , Koh Takeuchi , Hisashi Kashima , Feida Zhu

Tracing a student's knowledge growth given the past exercise answering is a vital objective in automatic tutoring systems to customize the learning experience. Yet, achieving this objective is a non-trivial task as it involves modeling the…

Computers and Society · Computer Science 2024-10-04 Seif Gad , Sherif Abdelfattah , Ghodai Abdelrahman

Knowledge Tracing aims to assess student learning states by predicting their performance in answering questions. Different from the existing research which utilizes fixed-length learning sequence to obtain the student states and regards KT…

Machine Learning · Computer Science 2024-07-31 Ke Cheng , Linzhi Peng , Pengyang Wang , Junchen Ye , Leilei Sun , Bowen Du

Graphs can model complex relationships between objects, enabling a myriad of Web applications such as online page/article classification and social recommendation. While graph neural networks(GNNs) have emerged as a powerful tool for graph…

Machine Learning · Computer Science 2023-02-28 Zemin Liu , Xingtong Yu , Yuan Fang , Xinming Zhang

This study introduces a novel method that employs tag annotation coupled with the ChatGPT language model to analyze student learning behaviors and generate personalized feedback. Central to this approach is the conversion of complex student…

Artificial Intelligence · Computer Science 2025-01-14 Yizhou Zhou , Mengqiao Zhang , Yuan-Hao Jiang , Xinyu Gao , Naijie Liu , Bo Jiang

Cognitive diagnosis aims to gauge students' mastery levels based on their response logs. Serving as a pivotal module in web-based online intelligent education systems (WOIESs), it plays an upstream and fundamental role in downstream tasks…

Artificial Intelligence · Computer Science 2024-04-18 Shuo Liu , Junhao Shen , Hong Qian , Aimin Zhou

Infographic is a type of information visualization that uses graphic design to enhance human ability to identify patterns and trends. It is popularly used to support spread of information. Yet, there are few studies that investigate how…

With increasing popularity in online learning, a surge of E-learning platforms have emerged to facilitate education opportunities for k-12 (from kindergarten to 12th grade) students and with this, a wealth of information on their learning…

Human-Computer Interaction · Computer Science 2019-09-24 Meng Xia , Huan Wei , Min Xu , Leo Yu Ho Lo , Yong Wang , Rong Zhang , Huamin Qu

Curriculum learning--ordering training examples in a sequence to aid machine learning--takes inspiration from human learning, but has not gained widespread acceptance. Static strategies for scoring item difficulty rely on indirect proxy…

Machine Learning · Computer Science 2026-03-17 Zhenwei Tang , Amogh Inamdar , Ashton Anderson , Richard Zemel

Noisy data, non-convex objectives, model misspecification, and numerical instability can all cause undesired behaviors in machine learning systems. As a result, detecting actual implementation errors can be extremely difficult. We…

Software Engineering · Computer Science 2017-06-28 Daniel Selsam , Percy Liang , David L. Dill

We profiled three aspects of MOOCs from the perspective of viewing behaviors, the most prominent and common ones of MOOC learning. They were learner classification, course attraction, teaching order and learning order. Based on viewing…

Physics Education · Physics 2018-04-16 Zheng Xie , Xiao Xiao , Jianping Li , Jinying Su

In the context of higher education's evolving dynamics post-COVID-19, this paper assesses the impact of new pedagogical incentives implemented in a first-year undergraduate computing module at University College London. We employ a mixed…

Computers and Society · Computer Science 2024-03-25 Laura J. Johnston , Takoua Jendoubi

Multi-relational graph clustering has demonstrated remarkable success in uncovering underlying patterns in complex networks. Representative methods manage to align different views motivated by advances in contrastive learning. Our empirical…

Machine Learning · Computer Science 2024-07-25 Zhixiang Shen , Haolan He , Zhao Kang

This full paper in the research track evaluates the usage of data logged from cybersecurity exercises in order to predict students who are potentially at risk of performing poorly. Hands-on exercises are essential for learning since they…

Charts provide visual representations of data and are widely used for analyzing information, addressing queries, and conveying insights to others. Various chart-related downstream tasks have emerged recently, such as question-answering and…

Computation and Language · Computer Science 2024-03-15 Ahmed Masry , Mehrad Shahmohammadi , Md Rizwan Parvez , Enamul Hoque , Shafiq Joty

In this paper, we propose an end-to-end graph learning framework, namely Iterative Deep Graph Learning (IDGL), for jointly and iteratively learning graph structure and graph embedding. The key rationale of IDGL is to learn a better graph…

Machine Learning · Computer Science 2020-10-26 Yu Chen , Lingfei Wu , Mohammed J. Zaki

An Intelligent Tutoring System (ITS) has been shown to improve students' learning outcomes by providing a personalized curriculum that addresses individual needs of every student. However, despite the effectiveness and efficiency that ITS…

Computers and Society · Computer Science 2020-09-22 Byungsoo Kim , Hongseok Suh , Jaewe Heo , Youngduck Choi

An educational system, the tutor-web (http://tutor-web.net), has been developed and used for educational research. The system is accessible and free to use for anyone having access to the Web. It is based on open source software and the…

Applications · Statistics 2013-10-18 Anna Helga Jonsdottir , Gunnar Stefansson

Course selection is a crucial activity for students as it directly impacts their workload and performance. It is also time-consuming, prone to subjectivity, and often carried out based on incomplete information. This task can, nevertheless,…

Human-Computer Interaction · Computer Science 2021-04-02 Gonzalo Gabriel Méndez , Luis Galárraga , Katherine Chiluiza

In-context learning (ICL) enhances large language models (LLMs) by incorporating demonstration examples, yet its effectiveness heavily depends on the quality of selected examples. Current methods typically use text embeddings to measure…

Artificial Intelligence · Computer Science 2025-12-02 Jiale Fu , Yaqing Wang , Simeng Han , Jiaming Fan , Xu Yang
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