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As large language models continue to advance, their application in educational contexts remains underexplored and under-optimized. In this paper, we address this gap by introducing the first diverse benchmark tailored for educational…

Computation and Language · Computer Science 2026-01-07 Bin Xu , Yu Bai , Huashan Sun , Yiguan Lin , Siming Liu , Xinyue Liang , Yaolin Li , Zhuangzhi Dong , Jingren Zhang , Yufan Deng , Xinyu Zou , Yang Gao , Heyan Huang

Dialogue systems dealing with multi-domain tasks are highly required. How to record the state remains a key problem in a task-oriented dialogue system. Normally we use human-defined features as dialogue states and apply a state tracker to…

Computation and Language · Computer Science 2020-05-27 Shuke Peng , Xinjing Huang , Zehao Lin , Feng Ji , Haiqing Chen , Yin Zhang

In the context of text classification, the financial burden of annotation exercises for creating training data is a critical issue. Active learning techniques, particularly those rooted in uncertainty sampling, offer a cost-effective…

Computation and Language · Computer Science 2024-06-19 Hamidreza Rouzegar , Masoud Makrehchi

Automated Essay scoring has been explored as a research and industry problem for over 50 years. It has drawn a lot of attention from the NLP community because of its clear educational value as a research area that can engender the creation…

Computation and Language · Computer Science 2023-11-14 Yann Hicke , Tonghua Tian , Karan Jha , Choong Hee Kim

Feedback is one of the most crucial components to facilitate effective learning. With the rise of large language models (LLMs) in recent years, research in programming education has increasingly focused on automated feedback generation to…

Computers and Society · Computer Science 2025-09-05 Niklas Scholz , Manh Hung Nguyen , Adish Singla , Tomohiro Nagashima

High-quality and consistent annotations are fundamental to the successful development of robust machine learning models. Traditional data annotation methods are resource-intensive and inefficient, often leading to a reliance on third-party…

Computer Vision and Pattern Recognition · Computer Science 2024-02-12 Amir Ziai , Aneesh Vartakavi

The feedback provided by current testing education tools about the deficiencies in a student's test suite either mimics industry code coverage tools or lists specific instructor test cases that are missing from the student's test suite.…

Software Engineering · Computer Science 2020-11-30 Lucas Cordova , Jeffrey Carver , Gursimran Walia , Noah Gershmel

Managing extensive context remains a critical bottleneck for Large Language Models (LLMs), particularly in applications like long-document question answering and autonomous agents where lengthy inputs incur high computational costs and…

Computation and Language · Computer Science 2026-01-06 Yiqing Zhou , Yu Lei , Shuzheng Si , Qingyan Sun , Wei Wang , Yifei Wu , Hao Wen , Gang Chen , Fanchao Qi , Maosong Sun

Developers increasingly take to the Internet for code snippets to integrate into their programs. To save developers the time required to switch from their development environments to a web browser in the quest for a suitable code snippet,…

Software Engineering · Computer Science 2017-08-03 Brock Angus Campbell , Christoph Treude

Encoder-decoder based neural architectures serve as the basis of state-of-the-art approaches in end-to-end open domain dialog systems. Since most of such systems are trained with a maximum likelihood~(MLE) objective they suffer from issues…

Dialogue data has been a key source for understanding learning processes, offering critical insights into how students engage in collaborative discussions and how these interactions shape their knowledge construction. The advent of Large…

Computation and Language · Computer Science 2025-04-29 Ying Na , Shihui Feng

Code Large Language Models (Code LLMs) have demonstrated outstanding performance in code-related tasks. Several instruction tuning approaches have been proposed to boost the code generation performance of pre-trained Code LLMs. In this…

Computation and Language · Computer Science 2024-02-15 Yejie Wang , Keqing He , Guanting Dong , Pei Wang , Weihao Zeng , Muxi Diao , Yutao Mou , Mengdi Zhang , Jingang Wang , Xunliang Cai , Weiran Xu

Audio-visual learning seeks to enhance the computer's multi-modal perception leveraging the correlation between the auditory and visual modalities. Despite their many useful downstream tasks, such as video retrieval, AR/VR, and…

Human-Computer Interaction · Computer Science 2023-07-31 Zheng Zhang , Zheng Ning , Chenliang Xu , Yapeng Tian , Toby Jia-Jun Li

The prevalence of e-learning systems and on-line courses has made educational material widely accessible to students of varying abilities and backgrounds. There is thus a growing need to accommodate for individual differences in e-learning…

Artificial Intelligence · Computer Science 2019-07-30 Avi Segal , Kobi Gal , Guy Shani , Bracha Shapira

`Linguistic annotation' covers any descriptive or analytic notations applied to raw language data. The basic data may be in the form of time functions - audio, video and/or physiological recordings - or it may be textual. The added…

Computation and Language · Computer Science 2007-05-23 Steven Bird , Mark Liberman

The e-learning community has been producing and using video content for a long time, and in the last years, the advent of MOOCs greatly relied on video recordings of teacher courses. Video annotations are information pieces that can be…

Computers and Society · Computer Science 2014-04-18 Olivier Aubert , Yannick Prié , Camila Canellas

The Center for Expanded Data Annotation and Retrieval (CEDAR) aims to revolutionize the way that metadata describing scientific experiments are authored. The software we have developed--the CEDAR Workbench--is a suite of Web-based tools and…

End-user programmers create software to solve problems, yet the problem-solving knowledge generated in the process often remains tacit within the software artifact. One approach to exposing this knowledge is to enable the end-user to…

Software Engineering · Computer Science 2009-08-11 Matthew Dinmore

Flipped learning is a method that flips in/out class activities to make lectures learner-centered. In flipped learning, comments from learners on preparation material are useful information for instructors to consider before deciding…

Computers and Society · Computer Science 2020-07-30 Shintaro Uchiyama , Hayato Okumoto , Mitsuo Yoshida , Yuko Ichikawa , Kyoji Umemura

In this paper we present the Open Software Services for Classrooms and Research (OSSCAR) platform. OSSCAR provides an open collaborative environment to develop, deploy and access educational resources in the form of web applications. To…

Physics Education · Physics 2022-10-05 Dou Du , Taylor J. Baird , Sara Bonella , Giovanni Pizzi