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This research aims to develop a hybrid recommendation model to optimize online learning environments using big data.

Construction Method of Learning Environment Based on Big Data Intelligent Recommendation Algorithm

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This research aims to develop a hybrid recommendation model to optimize online learning environments using big data.
Developed a hybrid optimization and recommendation model using collaborative filtering and content vectorization.
Integrated multi-dimensional data from learner and resource attributes along with user behavior.
Executed experiments on a real learning platform to assess effectiveness.
Precision improved by 18.3% over single collaborative filtering methods.
Precision improved by 22.7% over traditional content recommendation methods.
Learners' time spent increased by 12.5%, and course completion rates grew by 8.2%.

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Randomized trial demonstrates enhanced learning precision in online environments, indicating improved educational outcomes.

Ye et al. (2026) studied this question.

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