基于认知诊断和学习行为分析的多层次学习预警方法

IF 2 3区 计算机科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computer Supported Cooperative Work-The Journal of Collaborative Computing Pub Date : 2023-05-24 DOI:10.1109/cscwd57460.2023.10152579
Hua Ma, Wen Zhao, Zixu Jiang, Peiji Huang, Wen-sheng Tang, Hongyu Zhang
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引用次数: 0

摘要

学习预警对于应对学生的学习风险具有重要意义。现有的研究未能对学生学习状态的波动进行建模,也未能对不同层次的学生提供多层次的预警。针对这些问题,提出了一种将认知诊断与学习行为分析相结合的学习预警方法来预测网络学习环境中的高危学生。该方法从学习质量、学习投入、潜在学习状态和历史学习绩效四个维度对学生的学习过程进行建模。使用卷积神经网络和长短期记忆网络来探索学生的潜在学习特征。然后,运用Adaboost算法预测学生的学习成绩。在预测成绩的基础上,设计评价规则,为学生提供多层次的学习预警。实验结果表明,该方法能够有效、准确地预测出学生的学业风险。
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A Multi-level Approach to Learning Early Warning based on Cognitive Diagnosis and Learning Behaviors Analysis
Learning early warning is of great significance for coping with students' learning risks. The existing research fails in modeling the fluctuation of students' learning states and providing the multi-level early warning for students at different levels. To address them, a new approach of learning early warning is proposed to predict at-risk students in e-learning environment by combining cognitive diagnosis with learning behaviors analysis. In this approach, the students' learning process is modeled from four dimensions, i.e., learning quality, learning engagement, latent learning state, and historical learning performance. The convolutional neural network and long short-term memory network are used to explore the students' latent learning features. Then, the Adaboost algorithm is applied to predict students' learning performance. Based on the predicted performance, the evaluation rules are designed to provide multi-level learning early warning for students. Finally, the experiments demonstrate that the proposed method could predict at-risk students efficiently and accurately.
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来源期刊
Computer Supported Cooperative Work-The Journal of Collaborative Computing
Computer Supported Cooperative Work-The Journal of Collaborative Computing COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
6.40
自引率
4.20%
发文量
31
审稿时长
>12 weeks
期刊介绍: Computer Supported Cooperative Work (CSCW): The Journal of Collaborative Computing and Work Practices is devoted to innovative research in computer-supported cooperative work (CSCW). It provides an interdisciplinary and international forum for the debate and exchange of ideas concerning theoretical, practical, technical, and social issues in CSCW. The CSCW Journal arose in response to the growing interest in the design, implementation and use of technical systems (including computing, information, and communications technologies) which support people working cooperatively, and its scope remains to encompass the multifarious aspects of research within CSCW and related areas. The CSCW Journal focuses on research oriented towards the development of collaborative computing technologies on the basis of studies of actual cooperative work practices (where ‘work’ is used in the wider sense). That is, it welcomes in particular submissions that (a) report on findings from ethnographic or similar kinds of in-depth fieldwork of work practices with a view to their technological implications, (b) report on empirical evaluations of the use of extant or novel technical solutions under real-world conditions, and/or (c) develop technical or conceptual frameworks for practice-oriented computing research based on previous fieldwork and evaluations.
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