A Study on the Transformation of English Teachers’ Roles in Human-Machine Collaboration Modes

This study explores the issue of role transformation for English teachers in human-machine collaboration models, with a particular focus on the application of speech synthesis technology in English teaching and its impact on teacher roles.A mixed-methods research approach was employed, combining questionnaire surveys and indepth interviews to analyze data from 40 university English teachers and 200 students.Significant gaps were identified between expectations and reality regarding the modern teaching role enabled by technology.The expected proportion of teachers acting as "classroom activity facilitators" (87.5%) was significantly higher than the actual proportion (45%), and the expected proportion of teachers acting as "self-directed learners" exceeded the actual proportion by 24 percentage points.Regarding students' understanding of the transformation of teachers' roles, over 70% of respondents chose affirmative answers.However, in a survey on the specific content and methods of the transformation of teachers' roles, 49% of students indicated that they were not very familiar with the specific content and methods of the transformation.In terms of teachers' role transformation in the cognitive dimension, 65% of teachers believe that teachers should assume the role of student guides after the role transformation, while 47.5% of teachers believe that teachers should act as students' partners.The proportion of teachers who believe that teachers should remain in the dominant or authoritative role is zero.

Publication Details

Journal
International journal for housing science and its applications.
Published
2025-08-15
DOI
https://doi.org/10.70517/ijhsa464207
Primary Topic
Educational Reforms and Innovations
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Study on the Transformation of English Teachers’ Roles in Human-Machine Collaboration Modes

International journal for housing science and its applications.
Educational Reforms and Innovations
article

A Study on the Transformation of English Teachers’ Roles in Human-Machine Collaboration Modes

article en

Abstract

This study explores the issue of role transformation for English teachers in human-machine collaboration models, with a particular focus on the application of speech synthesis technology in English teaching and its impact on teacher roles.A mixed-methods research approach was employed, combining questionnaire surveys and indepth interviews to analyze data from 40 university English teachers and 200 students.Significant gaps were identified between expectations and reality regarding the modern teaching role enabled by technology.The expected proportion of teachers acting as "classroom activity facilitators" (87.5%) was significantly higher than the actual proportion (45%), and the expected proportion of teachers acting as "self-directed learners" exceeded the actual proportion by 24 percentage points.Regarding students' understanding of the transformation of teachers' roles, over 70% of respondents chose affirmative answers.However, in a survey on the specific content and methods of the transformation of teachers' roles, 49% of students indicated that they were not very familiar with the specific content and methods of the transformation.In terms of teachers' role transformation in the cognitive dimension, 65% of teachers believe that teachers should assume the role of student guides after the role transformation, while 47.5% of teachers believe that teachers should act as students' partners.The proportion of teachers who believe that teachers should remain in the dominant or authoritative role is zero.

International journal for housing science and its applications.Vol. 46(4)
Openalex Percentile: Top 71%
Educational Reforms and Innovations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.