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Interventions in STEM Education Through Speech Recognition-Based Learning Analysis

delete2024-12-13
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PRE
AI
C
Chia‐Ju Lin
W
Wei‐Sheng Wang
H
Hsin‐Yu Lee
Y
Yueh‐Min Huang *
T
Ting-Ting Wu
DOI:10.1177/07356331241307904delete
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摘要

摘要

En 中文
This study uses a quasi-experimental design to explore the role of natural language processing (NLP) and speech recognition technologies in supporting teacher interventions during collaborative STEM activities. The Speech Recognition Keywords Analysis System (SRKAS) was developed to extract keywords from student discussions, enabling real-time monitoring and timely teacher support. The study compares proactive and passive interventions, focusing on their effects on student engagement, anxiety, and confidence. Results show that proactive interventions enhance engagement, reduce anxiety, and increase confidence by providing immediate assistance. These findings highlight the value of technology-enhanced teaching strategies in collaborative learning and offer insights for improving student outcomes in STEM education.
Keyword:
STEM education
speech recognition
intervention
anxiety and confidence
engagement

期刊

Journal of Educational Computing Research 封面图
Journal of Educational Computing Research
IF:
4.9
论文数:
1.6K
被引数:
4.0K

机构

N
National Cheng Kung University
学者数:
2.6W
论文数: 2.3W
被引数: 1.7W
N
national yunlin university science & technology
学者数:
3.2K
论文数: 3.3K
被引数: 1
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