Smart Learning by Design: A Framework for IoT-Driven Adaptive Classrooms and Inclusive Education

This research presents a novel conceptual framework for inclusive education by integrating Internet of Things (IoT)-driven real-time environmental and behavioral monitoring with adaptive teaching strategies. Unlike traditional methods, our model leverages sensor-based data collection to analyze classroom conditions, teacher mobility, and student interactions, enabling dynamic adjustments that aim to enhance engagement and inclusivity. While the framework is theoretical and has not yet undergone experimental validation, we discuss how optimizing spatial configurations, voice dynamics, and movement patterns could support student participation, particularly for learners with diverse needs. Pilot implementations and empirical testing are planned for future research. By merging data-driven insights with educators’ expertise, our approach offers a scalable vision for creating responsive, inclusive learning environments that proactively address barriers to education.

Authors

Institutions

Publication Details

Journal
Education Sciences
Published
2025-10-09
DOI
https://doi.org/10.3390/educsci15101338
Primary Topic
Smart Cities and Technologies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Smart Learning by Design: A Framework for IoT-Driven Adaptive Classrooms and Inclusive Education

Livia Petti, Filippo Bruni, Paolo Lucattini, Lorenzo Mucchi et al.
Education Sciences
Smart Cities and Technologies
article

Smart Learning by Design: A Framework for IoT-Driven Adaptive Classrooms and Inclusive Education

Livia Petti, Filippo Bruni, Paolo Lucattini, Lorenzo Mucchi, Sara Jayousi
article en

Abstract

This research presents a novel conceptual framework for inclusive education by integrating Internet of Things (IoT)-driven real-time environmental and behavioral monitoring with adaptive teaching strategies. Unlike traditional methods, our model leverages sensor-based data collection to analyze classroom conditions, teacher mobility, and student interactions, enabling dynamic adjustments that aim to enhance engagement and inclusivity. While the framework is theoretical and has not yet undergone experimental validation, we discuss how optimizing spatial configurations, voice dynamics, and movement patterns could support student participation, particularly for learners with diverse needs. Pilot implementations and empirical testing are planned for future research. By merging data-driven insights with educators’ expertise, our approach offers a scalable vision for creating responsive, inclusive learning environments that proactively address barriers to education.

Education SciencesVol. 15(10)
University of Molise (IT), Polo Universitario Città di Prato (IT), University of Florence (IT)
European Commission, Fondazione Cassa di Risparmio di Firenze
Openalex Percentile: Top 59%
Smart Cities and Technologies
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.