Technology-Driven Transformation of Physical Education and Sports: Implications for Teaching, Coaching, and Athlete Development
Acceptance: 01/04/2026
Published: 23/04/2026
Abstract
The integration of emerging technologies into physical education (PE) and sports is reshaping how physical skills are taught, coached, and developed. In both India and globally, wearables, AI, big data analytics, and immersive technologies (AR/VR) are being deployed to personalize instruction, enhance performance, and broaden access. For example, smartwatches and fitness trackers now provide real-time physiological feedback in PE classes. Artificial intelligence enables coaches to generate data-driven training plans and even identify latent talent (e.g. AI-based talent ID deployed at Paris 2024). Policies like India’s National Education Policy 2020 and UNESCO’s Quality Physical Education framework explicitly support technology-enhanced learning (NEP 2020 repositions PE for holistic development). However, challenges such as the digital divide, data privacy, and the need for teacher and coach training are significant barriers. This paper employs a thematic literature review (focusing on 2023–2024 sources) to analyze how technology is transforming PE teaching, coaching innovation, and athlete development, drawing on Indian contexts and global best practices (e.g. IOC’s Olympic AI Agenda, WHO activity guidelines). The review finds that technology can greatly improve engagement, assessment, and individualized learning in PE, while also revolutionizing elite coaching with analytics and simulation. Ensuring equitable access, ethical data use, and updated policy frameworks will be critical for realizing these benefits.
Keynote: Physical Education, Sports Technology, Coaching, Athlete Development, NEP 2020, Artificial Intelligence, Wearable Technology
Author Name:
Dr. Ankur Singh Saini , Dr. Sandeep Kumar Dwivedi
Pages:
55-62
DOI Number:
10.5281/zenodo.19674140
Reference
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Writer Name
Dr. Ankur Singh Saini , Dr. Sandeep Kumar Dwivedi
Pages
55-62
DOI Numbers
10.5281/zenodo.19674140
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