Harnessing generative AI for educational innovation: a TRIZ-PLR perspective

Abstract This study investigates the transformative potential of Generative Artificial Intelligence (GenAI) in education using the TRIZ-Patent Literature Review (TRIZ-PLR) framework. By analysing patents related to GenAI, this study identifies technological challenges, inventive solutions, and their...

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Main Authors: Muhammad Saqib Iqbal, Zulhasni Abdul Rahim, Qudrattullah Omerkhel
Format: Article
Language:English
Published: Springer 2025-07-01
Series:Discover Applied Sciences
Subjects:
Online Access:https://doi.org/10.1007/s42452-025-07467-3
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author Muhammad Saqib Iqbal
Zulhasni Abdul Rahim
Qudrattullah Omerkhel
author_facet Muhammad Saqib Iqbal
Zulhasni Abdul Rahim
Qudrattullah Omerkhel
author_sort Muhammad Saqib Iqbal
collection DOAJ
description Abstract This study investigates the transformative potential of Generative Artificial Intelligence (GenAI) in education using the TRIZ-Patent Literature Review (TRIZ-PLR) framework. By analysing patents related to GenAI, this study identifies technological challenges, inventive solutions, and their implications for educational practices. The findings highlight advances in adaptive learning systems, optimised virtual classrooms, and predictive analytics, demonstrating how GenAI can improve personalised learning, student engagement, and academic performance. This study provides actionable information for educators, administrators, and technology developers, highlighting the importance of ethical considerations and equitable implementation. The study concludes with recommendations for scaling GenAI solutions in education, while addressing future research needs. 
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institution Kabale University
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publishDate 2025-07-01
publisher Springer
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series Discover Applied Sciences
spelling doaj-art-20e1bf8d0fc944dfb9daeef2ef77cc312025-08-20T03:46:21ZengSpringerDiscover Applied Sciences3004-92612025-07-017711310.1007/s42452-025-07467-3Harnessing generative AI for educational innovation: a TRIZ-PLR perspectiveMuhammad Saqib Iqbal0Zulhasni Abdul Rahim1Qudrattullah Omerkhel2NUST Business School, National University of Sciences & TechnologyInternational Institute of Technology, Universiti Teknologi MalaysiaComputer Science Faculty, Kabul Education UniversityAbstract This study investigates the transformative potential of Generative Artificial Intelligence (GenAI) in education using the TRIZ-Patent Literature Review (TRIZ-PLR) framework. By analysing patents related to GenAI, this study identifies technological challenges, inventive solutions, and their implications for educational practices. The findings highlight advances in adaptive learning systems, optimised virtual classrooms, and predictive analytics, demonstrating how GenAI can improve personalised learning, student engagement, and academic performance. This study provides actionable information for educators, administrators, and technology developers, highlighting the importance of ethical considerations and equitable implementation. The study concludes with recommendations for scaling GenAI solutions in education, while addressing future research needs. https://doi.org/10.1007/s42452-025-07467-3Generative artificial intelligenceTRIZPatent analysisTechnological innovationEducationPedagogical theories
spellingShingle Muhammad Saqib Iqbal
Zulhasni Abdul Rahim
Qudrattullah Omerkhel
Harnessing generative AI for educational innovation: a TRIZ-PLR perspective
Discover Applied Sciences
Generative artificial intelligence
TRIZ
Patent analysis
Technological innovation
Education
Pedagogical theories
title Harnessing generative AI for educational innovation: a TRIZ-PLR perspective
title_full Harnessing generative AI for educational innovation: a TRIZ-PLR perspective
title_fullStr Harnessing generative AI for educational innovation: a TRIZ-PLR perspective
title_full_unstemmed Harnessing generative AI for educational innovation: a TRIZ-PLR perspective
title_short Harnessing generative AI for educational innovation: a TRIZ-PLR perspective
title_sort harnessing generative ai for educational innovation a triz plr perspective
topic Generative artificial intelligence
TRIZ
Patent analysis
Technological innovation
Education
Pedagogical theories
url https://doi.org/10.1007/s42452-025-07467-3
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