Exploring the Continuous Learning Willingness Under the Risk of Data Breach in Online Learning System: A Fuzzy-Set QCA Approach

Jiang, Yuwei; Liu, Qingtang; Yu, Song; Ma, Jingjing; Wu, Linjing

doi:10.1109/iset55194.2022.00028

Cited by 1 publication

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“…This can be done by adjusting teaching methods, updating teaching materials, or improving the educational environment. These measures aim to promote more comprehensive and effective teaching [12][13][14][15]. Thirdly, for individual students, enhancing their learning willingness and resilience not only contributes to their short-term academic success but also affects their long-term career and life plans.…”

Section: Introductionmentioning

confidence: 99%

Using Autonomous Learning Mode to Improve Students’ Learning Willingness and Resilience

2023

Int. J. Emerg. Technol. Learn.

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In China, English teaching has become a key part of the education system at all levels. However, despite the significant resources invested in the education system, many students lack the necessary motivation and perseverance to learn. The interactive autonomous learning mode is a newly emerged educational approach that aims to enhance students’ motivation and resilience in learning through interaction and self-motivation. Existing works mostly focus on qualitative analysis and case studies; however, few have comprehensively considered the multiple factors or the future trend. To address this research gap, this paper proposes three novel research methods: predicting future learning willingness using a grey prediction model, evaluating the effectiveness of a learning resilience enhancement strategy using the TOPSIS analysis method, and analyzing the relationship between learning willingness and learning resilience enhancement using an improved grey relation projection method. These methods not only provide a comprehensive and accurate analytical framework, but they also contribute to educational reform and teaching practice.

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Section: Introductionmentioning

confidence: 99%

Using Autonomous Learning Mode to Improve Students’ Learning Willingness and Resilience

2023

Int. J. Emerg. Technol. Learn.

View full text Add to dashboard Cite

show abstract

Exploring the Continuous Learning Willingness Under the Risk of Data Breach in Online Learning System: A Fuzzy-Set QCA Approach

Cited by 1 publication

References 22 publications

Using Autonomous Learning Mode to Improve Students’ Learning Willingness and Resilience

Using Autonomous Learning Mode to Improve Students’ Learning Willingness and Resilience

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