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◆ Journal of Visualized Experiments2026-01-16· Nonprobability sampling

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

Zhao Jia, Dandan Tang, Linmin Mei, Xiaoyu Lu, Xiaorong Bai

原始摘要(英文原文)· Original 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.
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