March 3, 2026Open Access

An evaluation of online English teaching learning effectiveness based on decision tree classification algorithm

Key Points

The decision tree classification algorithm shows effectiveness in evaluating online English learning.
Key metrics indicate significant variations in learning outcomes based on instructional methods used.
Analysis employed decision tree algorithms to assess various aspects of online teaching effectiveness.
These findings suggest enhanced targeted strategies for improving online English education.

Abstract

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

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Authors

Yingying Qi

Journals

International Journal of Continuing Engineering Education and Life-Long Learning

An evaluation of online English teaching learning effectiveness based on decision tree classification algorithm

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