Design and Implementation of Intelligent Analysis Software for Teaching Behavior Based on near-Field Speech

EasyChair Preprint no. 11490

Abstract

The use of a finer-grained classroom language analysis coding form facilitates a more in-depth analysis of teachers' classroom language behavior. This study uses a finer-grained T-coding system to encode texts converted from teachers' near-field recordings, makes a preliminary exploration of multiple methods of visual teacher teaching strategies for coding sequences, and writes Python scripting software based on machine learning algorithms. This software can effectively assist teachers in self-observation and improve teaching quality.

Keyphrases: classroom analysis, component, T-seda coding, Teaching Behaviour

@Booklet{EasyChair:11490,
  author = {Zhenyue Sun and Yun Cheng and Ming Yu and Yaoyao Dai},
  title = {Design and Implementation of Intelligent Analysis Software for Teaching Behavior Based on near-Field Speech},
  howpublished = {EasyChair Preprint no. 11490},

  year = {EasyChair, 2023}}