Improved multilevel scaled cognitive diagnostic model as an aid in mental health education Online publication date: Mon, 02-Dec-2024
by Bo Wang; Qian Ren
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 28, No. 1, 2025
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.
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