Unveiling the Evolution of Educational Technologies: A Patent-Based Clustering and Life Cycle Analysis

The rapid evolution of educational technology (EdTech) has transformed learning environments, offering unprecedented opportunities for personalized, adaptive, and immersive education. Despite the increasing adoption of these innovations, the EdTech field lacks comprehensive, data-driven analyses to systematically categorize proprietary technologies and assess their developmental trajectories. Addressing this gap, this study employs a dataset of 85,267 patents to map the technological landscape of EdTech through patent mining, clustering, and technology life cycle analysis. Using natural language processing and clustering techniques, 15 distinct technology clusters were identified, including Learning Management Systems, Virtual and Augmented Reality, Adaptive Learning Systems, and Educational Robotics. Each cluster was further analyzed using logistic regression to determine its stage within the technology life cycle—emerging, growth, maturity, or saturation. Key findings indicate that Interactive Display Technologies have reached saturation, while Adaptive Learning Systems and Virtual and Augmented Reality are in active growth, highlighting their transformative potential for future innovations. The study also integrates the SAMR model to evaluate how these technologies align with pedagogical goals, distinguishing between those that enhance existing practices and those that redefine educational experiences.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3554741
Citations
5
Primary Topic
Intellectual Property and Patents
Type
article
Field-Weighted Citation Impact
13.80
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article

Unveiling the Evolution of Educational Technologies: A Patent-Based Clustering and Life Cycle Analysis

Navid Mohammadi, Mehrdad Maghsoudi, Mohammad Sabet, Mahdi Soghi
5 citations
IEEE Access
Intellectual Property and Patents
13.80
article

Unveiling the Evolution of Educational Technologies: A Patent-Based Clustering and Life Cycle Analysis

Navid Mohammadi, Mehrdad Maghsoudi, Mohammad Sabet, Mahdi Soghi
article en
5 citations

Abstract

The rapid evolution of educational technology (EdTech) has transformed learning environments, offering unprecedented opportunities for personalized, adaptive, and immersive education. Despite the increasing adoption of these innovations, the EdTech field lacks comprehensive, data-driven analyses to systematically categorize proprietary technologies and assess their developmental trajectories. Addressing this gap, this study employs a dataset of 85,267 patents to map the technological landscape of EdTech through patent mining, clustering, and technology life cycle analysis. Using natural language processing and clustering techniques, 15 distinct technology clusters were identified, including Learning Management Systems, Virtual and Augmented Reality, Adaptive Learning Systems, and Educational Robotics. Each cluster was further analyzed using logistic regression to determine its stage within the technology life cycle—emerging, growth, maturity, or saturation. Key findings indicate that Interactive Display Technologies have reached saturation, while Adaptive Learning Systems and Virtual and Augmented Reality are in active growth, highlighting their transformative potential for future innovations. The study also integrates the SAMR model to evaluate how these technologies align with pedagogical goals, distinguishing between those that enhance existing practices and those that redefine educational experiences.

IEEE AccessVol. 13
University of Tehran (IR), Shahid Beheshti University (IR)
Responsible consumption and production
Openalex Percentile: Top 2%
Intellectual Property and Patents
13.80
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