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Title: Design and application research of an AI teaching assistant for enhancing classroom instructional capabilities based on analysis of classroom audio and video

Authors: Tingyu Luan; Jinyi Huang; Ze Zhang

Addresses: College of Applied Technology, Dalian Ocean University, Wafangdian, Dalian, 116300, Liaoning, China ' College of Arts and Design, Guangxi Science and Technology Normal University, Laibin 546100, Guangxi, China ' School of Open Education, Chengde Open University, Chengde 067000, Hebei, China

Abstract: This paper addresses the limitations of traditional classroom teaching analysis - which relies heavily on manual labour, is inefficient, and lacks quantifiable metrics - by proposing an AI teaching research assistant design based on multimodal audio-visual data analysis. By automatically identifying and analysing elements such as teacher-student discourse, classroom interactions, and the sequencing of teaching activities, the assistant enables intelligent segmentation of teaching segments, quantitative assessment of teaching behaviours, and visual feedback. Application research demonstrates that the system objectively identifies teaching strengths and weaknesses, providing teachers with precise, personalised recommendations for enhancing instructional capabilities. This effectively promotes evidence-based teaching reflection and professional development, offering a viable pathway for innovating intelligent teaching research models.

Keywords: classroom audio-visual materials; classroom teaching competency; AI teaching research assistant; design and application research.

DOI: 10.1504/IJRIS.2026.155617

International Journal of Reasoning-based Intelligent Systems, 2026 Vol.18 No.19, pp.1 - 15

Received: 27 Jan 2026
Accepted: 20 Feb 2026
Published online: 07 Aug 2026 *