A Comprehensive Meta-Analysis of IoT Integration for Data-Driven Decision Making in Education

2024

Full text Open access: Hybrid Metadata (CSL-JSON)
DOI 10.4018/979-8-3693-5498-8.ch002
Data confidence 85 high
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

This chapter systematically reviews the literature on using internet of things (IoT) technologies to enable data-driven decision-making in educational institutions. As educational environments become increasingly complex, the ability to collect, analyze, and act upon data is crucial for institutional improvement. IoT technologies offer opportunities for educational leaders to optimize various aspects of campus operations, enhance student experiences, and improve administrative efficiency. The chapter explores IoT adoption in education, highlighting key technological advancements and their data collection and analysis applications. This chapter examines how IoT-generated data can inform resource allocation, facility management, and student services decisions. This chapter also addresses the challenges and barriers to integrating IoT in educational decision-making, including issues related to data privacy, security, and the need for robust data governance frameworks.