Article: Development and testing of a teaching quality assessment and examination data collection system based on artificial intelligence Journal: International Journal of Continuing Engineering Education and Life-Long Learning (IJCEELL) 2026 Vol.36 No.9 pp.40 - 56 Abstract: Conventional teaching quality assessment and data collection are time-consuming and inefficient, and they cannot easily meet people's needs in the current situation of massive data. The development of a new system can save time and improve efficiency in teaching and is conducive to mining abundant teaching data information, thus providing additional directions for teaching strategies. The efficiency of data processing and decision-making in the education field can be improved by introducing artificial intelligence and a decision-making algorithm, and the shortcomings of existing teaching quality evaluation and data collection methods can be resolved. Through an analysis of system requirements, this study employs artificial intelligence to develop a new teaching quality assessment system and compares it with the conventional system. Compare the accuracy, evaluation frequency, data collection efficiency, and running speed of the two systems. Comparison results show that accuracy, number of evaluations, online rate, and running speed increased by 14.2%, 39.1%, 26.3%, and 61.5%, respectively. The new system based on artificial intelligence has numerous advantages in teaching quality evaluation and data collection and can meet current needs. Inderscience Publishers - linking academia, business and industry through research

Title: Development and testing of a teaching quality assessment and examination data collection system based on artificial intelligence

Authors: Huihui Yin

Addresses: Harbin University, Harbin, 150086, Heilongjiang, China

Abstract: Conventional teaching quality assessment and data collection are time-consuming and inefficient, and they cannot easily meet people's needs in the current situation of massive data. The development of a new system can save time and improve efficiency in teaching and is conducive to mining abundant teaching data information, thus providing additional directions for teaching strategies. The efficiency of data processing and decision-making in the education field can be improved by introducing artificial intelligence and a decision-making algorithm, and the shortcomings of existing teaching quality evaluation and data collection methods can be resolved. Through an analysis of system requirements, this study employs artificial intelligence to develop a new teaching quality assessment system and compares it with the conventional system. Compare the accuracy, evaluation frequency, data collection efficiency, and running speed of the two systems. Comparison results show that accuracy, number of evaluations, online rate, and running speed increased by 14.2%, 39.1%, 26.3%, and 61.5%, respectively. The new system based on artificial intelligence has numerous advantages in teaching quality evaluation and data collection and can meet current needs.

Keywords: system development; data collection system; teaching quality assessment; artificial intelligence; data mining.

DOI: 10.1504/IJCEELL.2026.153590

International Journal of Continuing Engineering Education and Life-Long Learning, 2026 Vol.36 No.9, pp.40 - 56

Received: 19 Feb 2025
Accepted: 08 Dec 2025
Published online: 18 May 2026 *

Title: Development and testing of a teaching quality assessment and examination data collection system based on artificial intelligence

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