Title: Improved multilevel scaled cognitive diagnostic model as an aid in mental health education

Authors: Bo Wang; Qian Ren

Addresses: College of Electronic Information and Electrical Engineering, Shangluo University, Shangluo, Shaanxi, China ' College of Economics and Management, Shangluo University, Shangluo, Shaanxi, China

Abstract: In mental health education, there are differences in the level of knowledge and skill acquisition among students that cannot be assessed by a simple two-level scale. To this end, this study proposes an improved multi-level scoring cognitive diagnosis model based on deterministic input noise and gate model, and applies it to the personalised exercise recommendation of mental health education. In order to improve the evaluation of students' skill mastery level, the practice skill matrix is improved. In addition, considering the different requirements of skill levels for different problems, weight functions are introduced to ensure more accurate measurement feedback. The experimental results indicated that the proposed model is more reliable, with recommendation accuracy rates of 52.43%, 54.45% and 53.78%, respectively. This was significantly higher than other models and had a significant positive effect on student achievement. The model provides a new cognitive diagnostic tool for mental health education.

Keywords: cognitive diagnostic model; mental health education; exercise recommendation; performance prediction.

DOI: 10.1504/IJWMC.2025.143023

International Journal of Wireless and Mobile Computing, 2025 Vol.28 No.1, pp.47 - 57

Received: 24 Aug 2023
Accepted: 06 Apr 2024
Published online: 02 Dec 2024 *

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