Article: Innovative practice of AI-driven intelligent assessment system in university course teaching reform Journal: International Journal of Information and Communication Technology (IJICT) 2026 Vol.27 No.10 pp.63 - 89 Abstract: This research explores the implementation of intelligent evaluation systems powered by artificial intelligence within the context of university teaching reform. By integrating convolutional neural networks with interactive internet of things - enabled systems, the study demonstrates significant improvements in student performance, grading efficiency, and learning outcomes. AI advancements are driving a major transformation in higher education, enabling efficient assessment and personalised learning opportunities. While previous research has examined AI in intelligent tutoring, adaptive learning, and automated assessments, comprehensive studies on its integration into higher education remain limited. Employing a mixed-method approach, this study collected data from 120 students before and after the intervention, using both quantitative tests and qualitative surveys to ensure thorough analysis. Results indicate that student satisfaction increased, grading time was reduced by over 40%, and test performance improved by 6%. The findings reveal that AI integration was positively received by both faculty and students. Inderscience Publishers - linking academia, business and industry through research

Title: Innovative practice of AI-driven intelligent assessment system in university course teaching reform

Authors: Minghui Sun; Jilai Liu

Addresses: School of Management and Economics, Hebei North University, Zhangjiakou, Hebei, 075000, China ' Flamma Honkai (Dalian) Pharmaceutical Co., Ltd., Dalian, Liaoning, 116000, China

Abstract: This research explores the implementation of intelligent evaluation systems powered by artificial intelligence within the context of university teaching reform. By integrating convolutional neural networks with interactive internet of things - enabled systems, the study demonstrates significant improvements in student performance, grading efficiency, and learning outcomes. AI advancements are driving a major transformation in higher education, enabling efficient assessment and personalised learning opportunities. While previous research has examined AI in intelligent tutoring, adaptive learning, and automated assessments, comprehensive studies on its integration into higher education remain limited. Employing a mixed-method approach, this study collected data from 120 students before and after the intervention, using both quantitative tests and qualitative surveys to ensure thorough analysis. Results indicate that student satisfaction increased, grading time was reduced by over 40%, and test performance improved by 6%. The findings reveal that AI integration was positively received by both faculty and students.

Keywords: artificial intelligence; AI; intelligent assessment; higher education reform; convolutional neural networks; CNNs; IoT-assisted systems; student performance.

DOI: 10.1504/IJICT.2026.151684

International Journal of Information and Communication Technology, 2026 Vol.27 No.10, pp.63 - 89

Received: 30 Sep 2025
Accepted: 29 Nov 2025
Published online: 13 Feb 2026 *

Title: Innovative practice of AI-driven intelligent assessment system in university course teaching reform

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