Smartwatch-Enabled Data Analytics for AI-Based Evaluation of Teaching and Learning Processes

Deepali Kayande, Swetta Kukreja

2025

Abstract

The importance of the teaching-learning process in shaping outcomes is critical, necessitating the development of new evaluation methods for effective implementation. This paper presents a framework for evaluating and optimizing a smart teaching-learning ecosystem, utilizing data analytics and AI methodologies facilitated by smartwatches. Wearable technology captures real-time physiological and behavioral metrics (e.g., heart rate, physical activity, and attention levels) from students during classroom instruction. Artificial intelligence algorithms analyze this data to assess engagement, cognitive load, and responsiveness to various instructional methods. These insights are synthesized into actionable feedback for educators, providing information that can enhance pedagogical strategies that align more closely with learner needs. This facilitates the examination of trends and anomalies among various learner types to improve inclusivity in education. This study illustrates the practicality of employing data analytics alongside wearable technology to develop a comprehensive methodology for evaluating learning and teaching effectiveness. The preliminary results demonstrate the system's ability to provide accurate, scalable, and real-time insights, advancing beyond statistical analyses to support evidence-based educational interventions. This solution represents a significant advancement in modernizing academic assessment and integrating technology and pedagogy.

Paper Citation

in Harvard Style

Kayande D. and Kukreja S. (2025). Smartwatch-Enabled Data Analytics for AI-Based Evaluation of Teaching and Learning Processes. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 367-373. DOI: 10.5220/0013592600004664

in Bibtex Style

@conference{incoft25,
author={Deepali Kayande and Swetta Kukreja},
title={Smartwatch-Enabled Data Analytics for AI-Based Evaluation of Teaching and Learning Processes},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT},
year={2025},
pages={367-373},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013592600004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT
TI - Smartwatch-Enabled Data Analytics for AI-Based Evaluation of Teaching and Learning Processes
SN - 978-989-758-763-4
AU - Kayande D.
AU - Kukreja S.
PY - 2025
SP - 367
EP - 373
DO - 10.5220/0013592600004664
PB - SciTePress