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Research on MOOC Teaching Mode in Higher Education Based on Deep Learning
Yuan Tian1, Yingjie Sun1, Lijing Zhang1
1Aviation University of Air Force, Changchun, Jilin 130022, China.
Computational Intelligence and Neuroscience
|February 8, 2022
Summary
This study developed a personalized learning resource recommendation platform for Massive Open Online Courses (MOOCs). It uses deep neural networks and user data to enhance MOOC platform management and improve learning experiences.
Area of Science:
- Computer Science
- Educational Technology
- Data Mining
Background:
- Internet dependency for communication and data recording.
- Need for improved management of Massive Open Online Course (MOOC) resources.
- Limitations of traditional MOOC resource management methods.
Purpose of the Study:
- To enhance MOOC platform resource management.
- To build a personalized learning resource recommendation platform.
- To improve user services through data mining and recommendation systems.
Main Methods:
- Combining relevant datasets and recommendation techniques.
- Implementing a deep neural network algorithm.
- Simulating and recommending learning resources based on historical learner data.
Main Results:
- Initial realization of a personalized learning resource recommendation platform.
- Demonstration of recommendation effects through resource customization.
- Improved teaching management for MOOC platforms.
Conclusions:
- Deep neural networks effectively support personalized learning resource recommendations.
- The developed platform enhances MOOC resource management and user experience.
- Personalized recommendations are key to effective online learning and platform management.
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