New Era of Smart Classrooms-Innovation and Autonomous Learning Enhancement in Linear Algebra Courses Driven by Artificial Intelligence

Artificial Intelligence (AI) offers innovative solutions to address the teaching challenges of linear algebra courses caused by their high level of abstraction, such as students’ difficulties in comprehension, lack of interest, and weak self-directed learning abilities. This study proposes empowering educators to reconstruct teaching models through three key strategies: building intelligent teaching platforms (enabling personalized resource recommendations, learning path planning, and real-time feedback), leveraging data-driven instructional decisions (to dynamically optimize teaching content), and deploying intelligent tutoring systems (with virtual assistants to explain abstract concepts). Meanwhile, to tackle challenges such as data privacy, teachers’ adaptability to technology, and integration of educational resources, it is necessary to enhance data security mechanisms, strengthen teacher training, and promote inter-institutional collaboration. Future development will move toward multimodal interaction (e.g., VR/AR to enhance visual intuition) and interdisciplinary integration, advancing AI from a supporting tool to a core driving force of educational innovation, ultimately serving the goal of cultivating high-quality, versatile talents.

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Publication Details

Journal
Education Reform and Development
Published
2025-09-30
DOI
https://doi.org/10.26689/erd.v7i9.12114
Primary Topic
Technology-Enhanced Education Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

New Era of Smart Classrooms-Innovation and Autonomous Learning Enhancement in Linear Algebra Courses Driven by Artificial Intelligence

Qingrong Zou
Education Reform and Development
Technology-Enhanced Education Studies
article

New Era of Smart Classrooms-Innovation and Autonomous Learning Enhancement in Linear Algebra Courses Driven by Artificial Intelligence

Qingrong Zou
article en

Abstract

Artificial Intelligence (AI) offers innovative solutions to address the teaching challenges of linear algebra courses caused by their high level of abstraction, such as students’ difficulties in comprehension, lack of interest, and weak self-directed learning abilities. This study proposes empowering educators to reconstruct teaching models through three key strategies: building intelligent teaching platforms (enabling personalized resource recommendations, learning path planning, and real-time feedback), leveraging data-driven instructional decisions (to dynamically optimize teaching content), and deploying intelligent tutoring systems (with virtual assistants to explain abstract concepts). Meanwhile, to tackle challenges such as data privacy, teachers’ adaptability to technology, and integration of educational resources, it is necessary to enhance data security mechanisms, strengthen teacher training, and promote inter-institutional collaboration. Future development will move toward multimodal interaction (e.g., VR/AR to enhance visual intuition) and interdisciplinary integration, advancing AI from a supporting tool to a core driving force of educational innovation, ultimately serving the goal of cultivating high-quality, versatile talents.

Education Reform and DevelopmentVol. 7(9)
Beijing Information Science & Technology University (CN)
Beijing Information Science and Technology University
Openalex Percentile: Top 69%
Technology-Enhanced Education Studies
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