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Clustering Algorithm in English Language Learning Pattern Matching under Big Data Framework.

Liying Zheng1

  • 1Inner Mongolia Vocational and Technical College of Communications, Chifeng 024005, Inner Mongolia, China.

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Summary
This summary is machine-generated.

This study introduces a big data clustering algorithm for English language learning pattern matching. It addresses individual learning differences in university English teaching, aiming to improve teaching methods.

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Area of Science:

  • Educational Technology
  • Computer Science

Background:

  • The Internet era presents challenges and opportunities for English language learning and teaching.
  • Quality education initiatives emphasize individual student differences, yet uniform teaching methods lead to varied performance levels.
  • University English teaching faces difficulties due to diverse student learning paces and intellectual/non-intellectual influencing factors.

Purpose of the Study:

  • To investigate English language learning pattern matching concepts and their application in university English teaching.
  • To address the challenges of diverse student performance by exploring adaptive teaching strategies.
  • To propose innovative approaches for English language teaching in the context of individualized learning.

Main Methods:

  • Proposed a clustering algorithm based on a big data framework for English language learning pattern matching.
  • Utilized data mining techniques to analyze students' English learning behavior.
  • Explored clustering processing methods for student English learning data.

Main Results:

  • The proposed algorithm is fault-tolerant and efficient in acquiring and processing big data in English teaching.
  • The data mining and clustering methods provide insights into student learning behaviors.
  • The approach demonstrates high adaptability for practical English language learning pattern matching.

Conclusions:

  • The developed method offers a viable solution for English language learning pattern matching in university settings.
  • This approach supports the ongoing changes and innovations in English language teaching.
  • It facilitates a more personalized and effective learning experience by accommodating individual differences.