Reshaping Teachers' Roles in Intelligent Physical Education and Job Crafting: A Multimethod Approach

Summary

This protocol details a mixed-methods approach to investigate the cognitive, task-based, and relational dilemmas physical education teachers face when adapting their roles within Intelligent Physical Education environments and proposes strategic relief paths.

Abstract

This study examines the dilemmas physical education teachers face in reshaping their professional roles within Intelligent Physical Education (IPE) and proposes evidence-based relief strategies. Using a mixed-methods approach, a simple random sampling technique was employed for the quantitative phase, resulting in a usable sample size of N = 126 respondents. Moreover, for the qualitative phase, a purposive sampling strategy was employed, and five physical education teachers were selected for interviews. We integrated quantitative survey data with in-depth qualitative interviews to explore dimensions of job crafting. Our findings reveal significant cognitive, task-based, and relational challenges in adapting to innovative educational environments. Quantitative analysis reveals crucial predictive factors influencing these adaptation challenges, while qualitative data highlight insufficient understanding of AI applications, inadequate institutional support, and deficient technological infrastructure as key barriers. Teachers also expressed concerns about maintaining meaningful teacher-student relationships amid technological transformation. The study demonstrates that teachers' successful adaptation depends on systemic support rather than individual effort alone. We propose comprehensive strategies, including conceptual training, infrastructure development, and ethical guidelines, to facilitate effective job crafting. These findings contribute to understanding educator adaptation in technologically transforming educational landscapes and offer practical guidance for implementing intelligent physical education reforms.

Introduction

The development of artificial intelligence is radically transforming education because of its rapid development¹. The national plans promote this change, including the plans of China by New Generation Artificial Intelligence Development Plan and China Education Modernization 2035². This change is not the use of technology as a mere tool in the field of physical education (PE). Its objective is to develop intelligent solutions that allow individual training of students, feedback in real-time, and health monitoring³. This new area is called Intelligent Physical Education (IPE), where data provided b....

Protocol

This study was conducted in accordance with recognized ethical guidelines for social science research. Prior to commencement, the research protocol, including the informed consent forms, survey instrument, and interview questions, was reviewed. All participants were provided with a detailed information sheet outlining the study's purpose, the voluntary nature of their participation, their right to withdraw at any time without penalty, and the measures in place to ensure anonymity and confidentiality. Written informed consent was obtained from every participant before data collection began.

Ensuring the best ethical standards possible wa....

Results

Quantitative findings
Descriptive statistics
Descriptive statistics can be described as the introductory phase to the quantitative data analysis process, a quick overview of the fundamental characteristics of the information in the study. They are vital in estimating the normative nature (variation or distribution), central tendency, and variability of the sample, which enables readers to understand how applicable the research results are and to find the context with.......

Discussion

Discussion on quantitative findings
The insightful quantitative results of this research provide empirical evidence that sheds light on the multifaceted nature of the job-crafting dilemma among physical education teachers in intelligent education. The regression analysis provides the most robust and nuanced insights, revealing that perceived institutional support and technological self-efficacy emerge as the most statistically significant and influential predictors of teachers' cognitive dilemm.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Computer with AI Support Tools		—	Required for data analysis and AI-based lesson design
Digital Audio Recorder			Used to record teacher interviews
Intelligent Assessment System		—	Preferred AI application mentioned by teachers
Intelligent Education Platform		—	Mentioned as part of AI teaching tools used by teachers
Interview Protocol Document	Self-developed	—	Semi-structured guide for interviews
Learning Analytics Platform		—	Referenced as an AI-enabled teaching analysis tool
NVivo	QSR International	Version 12	Used for qualitative thematic coding
Online Questionnaire	Self-developed	—	Used to collect responses from 126 PE teachers
SPSS (Statistical Software)	IBM	Version 27	Used for quantitative data analysis