Article: Construction of an adaptive model for English learning tasks based on cognitive diagnosis in a smart classroom Journal: International Journal of Information and Communication Technology (IJICT) 2025 Vol.26 No.33 pp.38 - 56 Abstract: Accurate instruction has become the main need with the development of smart classrooms. Although cognitive diagnostic tests can show students' cognitive status, it is primarily applied for static assessment, which is challenging to satisfy the dynamic adaptation requirements of English learning activities. This work, therefore, concentrates on the smart classroom scenario and builds a cognitive diagnosis-based adaptive model for English learning activities (CD-ELAM). The model realises the exact identification of students' cognitive state and the dynamic optimisation of task pushing by combining four modules: cognitive state modelling, task feature expression, task regulating mechanism and personalised learning strategies, so forming a closed-loop task adaptation mechanism. In terms of cognitive diagnosis accuracy and learning effect improvement, the experimental results reveal that CD-ELAM beats the current approaches; moreover, it has good adaptability and practicality. Inderscience Publishers - linking academia, business and industry through research

Title: Construction of an adaptive model for English learning tasks based on cognitive diagnosis in a smart classroom

Authors: Gang Shen; Tao Feng

Addresses: School of Foreign Studies, Suqian University, Suqian 223800, China ' School of Foreign Studies, Suqian University, Suqian 223800, China

Abstract: Accurate instruction has become the main need with the development of smart classrooms. Although cognitive diagnostic tests can show students' cognitive status, it is primarily applied for static assessment, which is challenging to satisfy the dynamic adaptation requirements of English learning activities. This work, therefore, concentrates on the smart classroom scenario and builds a cognitive diagnosis-based adaptive model for English learning activities (CD-ELAM). The model realises the exact identification of students' cognitive state and the dynamic optimisation of task pushing by combining four modules: cognitive state modelling, task feature expression, task regulating mechanism and personalised learning strategies, so forming a closed-loop task adaptation mechanism. In terms of cognitive diagnosis accuracy and learning effect improvement, the experimental results reveal that CD-ELAM beats the current approaches; moreover, it has good adaptability and practicality.

Keywords: smart classroom; cognitive diagnosis; adaptive learning; English learning tasks.

DOI: 10.1504/IJICT.2025.148652

International Journal of Information and Communication Technology, 2025 Vol.26 No.33, pp.38 - 56

Received: 27 Jun 2025
Accepted: 23 Jul 2025
Published online: 17 Sep 2025 *

Title: Construction of an adaptive model for English learning tasks based on cognitive diagnosis in a smart classroom

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